Novel design of cryptographic architecture of nanorouter using quantum-dot cellular automata nanotechnology

The article introduces a revolutionary Nanorouter structure, which is a crucial component in the Nano communication regime. To complete the connection, many key properties of Nanorouters are investigated and merged. QCA circuits with better speed and reduced power dissipation aid in meeting internet standards. Cryptography based on QCA design methodologies is a novel concept in digital circuit design. Data security in nano-communication is crucial in data transmission and reception; hence, cryptographic approaches are necessary. The data entering the input line is encrypted by an encoder, and then sent to the designated output line, where it is decoded and transferred. The Nanorouter is offered as a data path selector, and the proposed study analyses the cell count of QCA and the circuit delay. In this manuscript, novel designs of (4:1)) Mux and (1:4) Demux designs are utilized to implement the proposed nanorouter design. The proposed (4:1) Mux design requires 3-5% fewer cell counts and 20-25% fewer area, and the propsoed (1:4) Demux designs require 75-80% fewer cell counts and 90-95% fewer area compared to their latest counterparts. The QCAPro utility is used to analyse the power consumption of several components that make up the router. QCADesigner 2.0.3 is used to validate the simulation results and output validity.

Super-resolution deep neural network (SRDNN) based multi-image steganography for highly secured lossless image transmission

Information exchange and communication through the Internet are one of the most crucial aspects of today's information technology world. The security of information transmitted online has grown to be a critical concern, particularly in the transfer of medical data. To overcome this, the data must be delivered securely without being altered or lost. This can be possibly done by combining the principles of cryptography and steganography. In the recent past, steganography is used with simpler methods like the least significant bit manipulation technique, in order to encode a lower-resolution image into a higher-resolution image. Here, we attempt to use deep neural networks to combine many two-dimensional colour images of the same resolution into a single cover image with the same resolution. In this technique, many secret images are concealed inside a single cover image using deep neural networks. The embedded cover image is then encrypted using a 3D chaotic map for diffusion and elliptic curve cryptography (ECC) for confusion to increase security.Supporting the fact that neural networks experience losses, the proposed system recovers up to 93% of the hidden image concealed in the original image. As the secret image features are identified and combined along with the cover image, the time complexity involved in the security process is minimized by 78% compared to securing the original data.

A medical image encryption scheme based on Mobius transformation and Galois field

Data security and privacy are considered to be the biggest problems faced by service providers who have worked with public data for a long time. A key element of modern encryption that is utilized to increase textual confusion is the Substitution box (S-box) and the algebraic strength of the S-box has a significant impact on how secure the encryption method is. In this article, we present a unique method that uses a linear fractional transformation on a finite field to produce cryptographically robust S-boxes. Firstly, we choose a specific irreducible polynomial of degree 8 in Z 2 [ x ] to construct G F ( 2 8 ) . Later, we used the action of P G L ( 2 , G F ( 2 8 ) ) on G F ( 2 8 ) to generate a robust S-box. The effectiveness of the built-in S-box was evaluated using several criteria including non-linearity, differential uniformity, strict avalanche criteria, linear approximation probability, and bit independence criterion. The proposed S-box's characteristics are compared to those of most recent S-boxes to confirm the higher performance. Additionally, the S box was used to encrypt images to show its usefulness for multimedia security applications. We performed several tests, including contrast, correlation, homogeneity, entropy, and energy, to evaluate the success of the encryption technique. The proposed method for ciphering an image is very effective, as proven by its comparison with several S boxes.

Capturing Doublet Intermediate Emitters by Chemically Crosslinking Confinement towards Spatiotemporal Encryption

Photoluminescence is one of the most meticulous ways to manipulate light energy. Typical photoluminescent emitters are mostly stable substances with a pure photophysical process of spontaneous photon-emission from their excited states. Intermediate emitters are elusive attributing to their synchronous energy transfer process including photophysical and incomplete photochemical pathways. An intermediate emitter containing radicals is more difficult to be observed due to its inherent chemical reactivity. Here, these challenges are overcome by spontaneously formed space limitations in polymer crosslinking networks meanwhile chemically active intermediates are captured. These doublet intermediates exhibit unique long-wavelength emissions under chemically crosslinking confinement conditions, and their luminous mechanism provides a novel perspective for designing intermediate emitters with liquid-crystal character and photoresponsive features towards spatiotemporal encryption, promising for the detection of photochemical reactions and the development of fascinating luminescent systems.

Efficient Visible-Light-Activated Ultra-Long Room-Temperature Phosphorescence Triggered by Multi-Esterification

The development of ultra-long room-temperature phosphorescence (UL-RTP) in processable amorphous organic materials is highly desirable for applications in flexible displays, anti-counterfeiting, and bio-imaging. However, achieving efficient UL-RTP from amorphous materials remains a challenging task, especially with activation by visible light and a bright afterglow. Here we report a general and rational molecular-design strategy to enable efficient visible-light-excited UL-RTP by multi-esterification of a rigid large-plane phosphorescence core. Notably, multi-esterification minimizes the aggregation-induced quenching and accomplishes a 'four birds with one stone' possibility in the generation and radiation process of UL-RTP: i) shifting the excitation from ultraviolet light to blue-light through enhancing the transition dipole moment of low-lying singlet-states, ii) facilitating the intersystem crossing process through the incorporation of lone-pair electrons, iii) boosting the decay process of long-lived triplet excitons resulting from a significantly increased transition dipole moment, and iv) reducing the intrinsic triplet nonradiative decay by substitution of high-frequency vibrating hydrogen atoms. All these factors synergistically contribute to the most efficient and stable visible-light-stimulated UL-RTP (lifetime up to 2.01 s and efficiency up to 35.4 % upon excitation at 450 nm) in flexible films using multi-esterified coronene, which allows high-tech applications in single-component time-delayed white light-emitting diodes and information technology based on flashlight-activated afterglow encryption.

An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm

Data stored on physical storage devices and transmitted over communication channels often have a lot of redundant information, which can be reduced through compression techniques to conserve space and reduce the time it takes to transmit the data. The need for adequate security measures, such as secret key control in specific techniques, raises concerns about data exposure to potential attacks. Encryption plays a vital role in safeguarding information and maintaining its confidentiality by utilizing a secret key to make the data unreadable and unalterable. The focus of this paper is to tackle the challenge of simultaneously compressing and encrypting data without affecting the efficacy of either process. The authors propose an efficient and secure compression method incorporating a secret key to accomplish this goal. Encoding input data involves scrambling it with a generated key and then transforming it through the Burrows-Wheeler Transform (BWT). Subsequently, the output from the BWT is compressed through both Move-To-Front Transform and Run-Length Encoding. This method blends the cryptographic principles of confusion and diffusion into the compression process, enhancing its performance. The proposed technique is geared towards providing robust encryption and sufficient compression. Experimentation results show that it outperforms other techniques in terms of compression ratio. A security analysis of the technique has determined that it is susceptible to the secret key and plaintext, as measured by the unicity distance. Additionally, the results of the proposed technique showed a significant improvement with a compression ratio close to 90% after passing all the test text files.

Federated learning for 6G-enabled secure communication systems: a comprehensive survey

Machine learning (ML) and Deep learning (DL) models are popular in many areas, from business, medicine, industries, healthcare, transportation, smart cities, and many more. However, the conventional centralized training techniques may not apply to upcoming distributed applications, which require high accuracy and quick response time. It is mainly due to limited storage and performance bottleneck problems on the centralized servers during the execution of various ML and DL-based models. However, federated learning (FL) is a developing approach to training ML models in a collaborative and distributed manner. It allows the full potential exploitation of these models with unlimited data and distributed computing power. In FL, edge computing devices collaborate to train a global model on their private data and computational power without sharing their private data on the network, thereby offering privacy preservation by default. But the distributed nature of FL faces various challenges related to data heterogeneity, client mobility, scalability, and seamless data aggregation. Moreover, the communication channels, clients, and central servers are also vulnerable to attacks which may give various security threats. Thus, a structured vulnerability and risk assessment are needed to deploy FL successfully in real-life scenarios. Furthermore, the scope of FL is expanding in terms of its application areas, with each area facing different threats. In this paper, we analyze various vulnerabilities present in the FL environment and design a literature survey of possible threats from the perspective of different application areas. Also, we review the most recent defensive algorithms and strategies used to guard against security and privacy threats in those areas. For a systematic coverage of the topic, we considered various applications under four main categories: space, air, ground, and underwater communications. We also compared the proposed methodologies regarding the underlying approach, base model, datasets, evaluation matrices, and achievements. Lastly, various approaches' future directions and existing drawbacks are discussed in detail.

Bioinspired multichannel colorful encryption through kirigami activating grating

Optical encryption, exploiting degrees of freedom of light as parameters to encode and decode information, plays an indispensable role in our daily life. Responsive structural color materials can give real-time visible feedback to external stimuli and provide ideal candidates for optical encryption. However, the development of existing responsive structural color materials is hindered by poor repeatability and long feedback time. Meanwhile, there are only few strategies to exploit structural colors in multichannel information encryption. Herein, bioinspired by the structural color variation due to a change in angle arising from the movement of animal's scales or feathers, we developed a general multichannel information encryption strategy using a two-dimensional deformable kirigami arranging orientations of the grating arrays by design. The kirigami grating sheet shows rapid, repeatable, and programmable color change. This strategy utilizes the topological space deformation to guide the change of optical property, which suggests new possibilities for spatial and spectral encryption as well as mechano-sensing and camouflage.

Photo-controllable Luminescence from Radicals Leading to Ratiometric Emission Switching via Dynamic Intermolecular Coupling

The development of photoinduced luminescent radicals with dynamic emission color is still challenging. Herein we report a novel molecular radical system (TBIQ) that shows photo-controllable luminescence, leading to a wide range of ratiometric color changes via light excitation. The conjugated skeleton of TBIQ is decorated with steric-demanding tertiary butyl groups that enable appropriate intermolecular interaction to make dynamic intermolecular coupling possible for controllable behaviors. We reveal that the helicenic pseudo-planar conformation of TBIQ experiences a planarization process after light excitation, leading to more compactly stacked supermolecules and thus generating radicals via intermolecular charge transfer. The photo-controllable luminescent radical system is employed for a high-level information encryption application. This study may offer unique insight into molecular dynamic motion for optical manufacturing and broaden the scope of smart-responsive materials for advanced applications.

An Overview on Security and Privacy of Data in IoMT Devices: Performance Metrics, Merits, Demerits, and Challenges

The Internet of Medical Things (IoMT) emerges with new trendsetter device applications, where it defines the incorporation of medical devices with the Internet of Things (IoT). The healthcare sector continues to encounter challenging obstacles that have an impact on the quality of treatment provided to patients. To get rid of this problem, IoMT is being deployed to achieve the high reliability and efficiency of the health system. The IoMT devices are superimposed with clinical information as they contain the details of patient health data, address, and other patient identifiers. By containing such amount of sensitive information, it becomes cumbersome to preserve data privacy and security. Due to inadequate security and privacy precautions, patient health data is susceptible to leakage, which has a direct impact on the patient's life. In addition, the majority of medical devices are susceptible to cyberattacks, putting patient information at risk. Inadequate control of life-support equipment can have a devastating effect on patient outcomes. Thus, this survey intends to review the various security models of IoMT devices using standard techniques to support health care systems. It provides a wide range of literature reviews regarding IoMT systems and compares them with traditional methodologies. This review work exhibits the motivation for current technologies to maintain the security and privacy of patients' data with IoMT devices. The systematic review entails background on security in IoMT devices, techniques for security, usage of diverse validation measures, and also discusses the problems and motivation for future research work.

Multiplex heteroatoms doped carbon nano dots with enhanced catalytic reduction of ionic dyes and QR code security label for anti-spurious applications

Herein, a simple hydrothermal approach was used to make multiplex heteroatoms doped carbon dots from Tinospora cordifolia miers plant extract. Their ability to the catalytic activity of dyes and anti-spurious applications was evaluated. The formation of NBCNDs and source of (T. cordifolia miers) study the optical properties, and functional groups are investigated using UV-Visible spectroscopy and FT-IR techniques. The synthesized NBCNDs structure and elemental compositions were examined via HR-TEM, XRD, and XPS, respectively. According to the HRTEM images, the average particle size of the NBCNDs was around 4.3± 1 nm, with d-spacing of 0.19 nm. The obtained NBCNDs were exposed under 395 nm UV light to emit bluish-green tuneable fluorescence with QY (quantum yield) of 23.7%. The prepared NBCNDs as a potential catalyst for the AYR and CV dye reduction process using freshly prepared NaBH₄, with determined rate constant values at 0.1220 and 0.1521 min^-1, respectively. Lastly, we constructed a quick response (QR) code security label for anti-spurious applications using stencil techniques. The "confidential info" was encrypted using a QR code digital system, and the decryption was read using a smartphone under 365 nm light irradiation.

Deepfake attack prevention using steganography GANs

BACKGROUND

Deepfakes are fake images or videos generated by deep learning algorithms. Ongoing progress in deep learning techniques like auto-encoders and generative adversarial networks (GANs) is approaching a level that makes deepfake detection ideally impossible. A deepfake is created by swapping videos, images, or audio with the target, consequently raising digital media threats over the internet. Much work has been done to detect deepfake videos through feature detection using a convolutional neural network (CNN), recurrent neural network (RNN), and spatiotemporal CNN. However, these techniques are not effective in the future due to continuous improvements in GANs. Style GANs can create fake videos with high accuracy that cannot be easily detected. Hence, deepfake prevention is the need of the hour rather than just mere detection.

METHODS

Recently, blockchain-based ownership methods, image tags, and watermarks in video frames have been used to prevent deepfake. However, this process is not fully functional. An image frame could be faked by copying watermarks and reusing them to create a deepfake. In this research, an enhanced modified version of the steganography technique RivaGAN is used to address the issue. The proposed approach encodes watermarks into features of the video frames by training an "attention model" with the ReLU activation function to achieve a fast learning rate.

RESULTS

The proposed attention-generating approach has been validated with multiple activation functions and learning rates. It achieved 99.7% accuracy in embedding watermarks into the frames of the video. After generating the attention model, the generative adversarial network has trained using DeepFaceLab 2.0 and has tested the prevention of deepfake attacks using watermark embedded videos comprising 8,074 frames from different benchmark datasets. The proposed approach has acquired a 100% success rate in preventing deepfake attacks. Our code is available at https://github.com/shahidmuneer/deepfakes-watermarking-technique.

Time Efficient Image Encryption-Decryption for Visible and COVID-19 X-ray Images Using Modified Chaos-Based Logistic Map

In this pandemic situation, radiological images are the biggest source of information in healthcare and, at the same time, one of the foremost troublesome sources to analyze. Clinicians now-a-days must depend to a great extent on therapeutic image investigation performed by exhausted radiologists and some of the time analyzed and filtered themselves. Due to an overflow of patients, transmission of these medical data becomes frequent and maintaining confidentiality turns out to be one of the most important aspects of security along with integrity and availability. Chaos-based cryptography has proven a useful technique in the process of medical image encryption. The specialty of using chaotic maps in image security is its capability to increase the unpredictability and this causes the encryption robust. There are large number of literature available with chaotic map; however, most of these are not useful in low-precision devices due to their time-consuming nature. Taking into consideration of all these facts, a modified encryption technique is proposed for 2D COVID-19 images without compromising security. The novelty of the encryption procedure lies in the proposed design which is split into mainly three parts. In the first part, a variable length gray level code is used to generate the secret key to confuse the intruder and subsequently it is used as the initial parameter of both the chaotic maps. In the second part, one-stage image pixels are shuffled using the address code obtained from the sorting transformation of the first logistic map. In the final stage, a complete diffusion is applied for the whole image using the second chaotic map to counter differential and statistical attack. Algorithm validation is done by experimentation with visual image and COVID-19 X-ray images. In addition, a quantitative analysis is carried out to ensure a negligible data loss between the original and the decrypted image. The strength of the proposed method is tested by calculating the various security parameters like correlation coefficient, NPCR, UACI, and key sensitivity. Comparison analysis shows the effectiveness for the proposed method. Implementation statistics shows time efficiency and proves more security with better unpredictability.

Complex entropy based encryption and decryption technique for securing medical images

During medical picture transmission, the most pressing concern is security. Medical images must be encrypted since they are extremely sensitive. Watermarking, digital fingerprinting/signature, and encoding are some of the available image security techniques. Images and movies, for example, must be highly encrypted and decoded without losing any content information. Medical photos, for example, require extra protection, and protecting medical images is a critical issue when medical images and related patient information are transferred over public networks. This research work proposes a visual encryption strategy to secure medical pictures before being transmitted or stored in the cloud. This technique makes such pictures of unauthorized people unavailable and also maintains confidentiality, a prime safety requirement. The process made use of a pixel shuffling-based encryption technique and a secret key created from the image. In this research, we encrypted the medical image using modified Arnold Map Encryption and generated secret key values. Therefore, the image is encrypted, and henceforth it is decrypted as well. So this work gave us the encrypted image and decrypted image/original image as well. The modified Arnold Map Encryption tries to add more randomness, thus increasing the entropy of the image and thus makes it harder to decrypt. The modified Arnold Map Encryption is also compared to other algorithms such as Hyper Chaotic, Secure Hash Algorithm-13 (SHA-13), Ten Logistic Maps, Bakers Map, HenonMap, Cross Chaos Map, and 2D Logistic Map and shows better results in terms of encryption speed and Number of Pixel Change Rate (NPCR) value.

WatMIF: Multimodal Medical Image Fusion-Based Watermarking for Telehealth Applications

Over recent years, the volume of big data has drastically increased for medical applications. Such data are shared by cloud providers for storage and further processing. Medical images contain sensitive information, and these images are shared with healthcare workers, patients, and, in some scenarios, researchers for diagnostic and study purposes. However, the security of these images in the transfer process is extremely important, especially after the COVID-19 pandemic. This paper proposes a secure watermarking algorithm, termed WatMIF, based on multimodal medical image fusion. The proposed algorithm consists of three major parts: the encryption of the host media, the fusion of multimodal medical images, and the embedding and extraction of the fused mark. We encrypt the host media with a key-based encryption scheme. Then, a nonsubsampled contourlet transform (NSCT)-based fusion scheme is employed to fuse the magnetic resonance imaging (MRI) and computed tomography (CT) scan images to generate the fused mark image. Furthermore, the encrypted host media conceals the fused watermark using redundant discrete wavelet transform (RDWT) and randomised singular value decomposition (RSVD). Finally, denoising convolutional neural network (DnCNN) is used to improve the robustness of the WatMIF algorithm. The simulation experiments on two standard datasets were used to evaluate the algorithm in terms of invisibility, robustness, and security. When compared with the existing algorithms, the robustness is improved by 20.14%. Overall, the implementation of proposed watermarking for hiding fused marks and efficient encryption improved the identity verification, invisibility, robustness and security criteria in our WatMIF algorithm.

ATP-Induced Emergent Circularly Polarized Luminescence and Encryption

Biomimetic ATP-driven supramolecular assembly is important to understand various biological processes and dissipative systems. Here, we report an ATP-driven chiral assembly exhibiting circularly polarized luminescence (CPL) via the interaction of an achiral terpyridine-based Zn^II complex with nucleotides. It was found that while the metal complexes could co-assemble with the nucleotides to form fluorescent assemblies, only a combination of furan-substituted terpyridine complex and ATP showed an intense CPL with a dissymmetry factor (g_lum ) as high as 0.20. This means that the complex could recognize ATP using CPL as a readout signal, thus providing an example of ATP encryption. Interestingly, when ATP was transferred into ADP or AMP under enzymatic hydrolysis, the CPL decreases or disappears. Addition of ATP generates CPL again, thus producing an ATP-induced CPL system. This work presents the first example of ATP-induced CPL and encryption.

Double Lock Label Based on Thermosensitive Polymer Hydrogels for Information Camouflage and Multilevel Encryption

Developing extra safety encryption technologies to prevent information leakage and combat fakes is in high demand but is challenging. Herein, we propose a "double lock" strategy based on both lower critical solution temperature (LCST) and upper critical solution temperature (UCST) polymer hydrogels for information camouflage and multilevel encryption. Two types of hydrogels were synthesized by the method of random copolymerization. The number of -CO-NH₂ groups in the network structure of the hydrogels changed the enthalpic or entropic thermo-responsive hydrogels, and ultimately precisely controlled their phase transition temperature. The crosslink density of the polymer hydrogels governs the diffusion kinetics, resulting in a difference in the time for their color change. The combination of multiple LCST and UCST hydrogels in one label realized information encryption and dynamic information identification in the dimensions of both time and temperature. This work is highly interesting for the fields of information encryption, anti-counterfeiting, and smart responsive materials.

SEMRES - A Triple Security Protected Blockchain Based Medical Record Exchange Structure

BACKGROUND AND OBJECTIVE

COVID-19, a serious infectious disease outbreak started in the end of 2019, has caused a strong impact on the overall medical system, which reflects the gap in the volume and capacity of medical services and highlights the importance of clinical data ex-change and application. The most important concerns of medical records in the medical field include data privacy, data correctness, and data security. By realizing these three goals, medical records can be made available to different hospital information systems to achieve the most complete medical care services. The privacy and protection of health data require detailed specification and usage requirements, which is particularly important for cross-agency data exchange.

METHODS

This research is composed of three main modules. "Combined Encryption and Decryption Architecture", which includes the hybrid double encryption mechanism of AES and RSA, and encrypts medical records to produce "Secured Encrypted Medical Record". "Decentralize EMR Repository", which includes data decryption and an exchange mechanism. After a data transmission is completed, the content verification and data decryption process will be launched to confirm the correctness of the data and obtain the data. A blockchain architecture is used to store the hash value of the encrypted EMR, and completes the correctness verification of the EMR after transmission through the hash value.

RESULTS

The results of this study provide an efficient triple encryption mechanism for electronic medical records. SEMRES ensures the correctness of data through the non-repudiation feature of a blockchain open ledger, and complete integrated information security protection and data verification architecture, in order that medical data can be exchanged, verified, and applied in different locations. After the patient receives medical services, the medical record is re-encrypted and verified and stored in the patient's medical record. The blockchain architecture is used to ensure the verification of non-repudiation of medical service, and finally to complete the payment for medical services.

CONCLUSIONS

The main aim of this study was to complete a security architecture for medical data, and develop a triple encryption authentication architecture to help data owners easily and securely share personal medical records with medical service personnel.

Achieving data privacy for decision support systems in times of massive data sharing

The world is suffering from a new pandemic of Covid-19 that is affecting human lives. The collection of records for Covid-19 patients is necessary to tackle that situation. The decision support systems (DSS) are used to gather that records. The researchers access the patient's data through DSS and perform predictions on the severity and effect of the Covid-19 disease; in contrast, unauthorized users can also access the data for malicious purposes. For that reason, it is a challenging task to protect Covid-19 patient data. In this paper, we proposed a new technique for protecting Covid-19 patients' data. The proposed model consists of two folds. Firstly, Blowfish encryption uses to encrypt the identity attributes. Secondly, it uses Pseudonymization to mask identity and quasi-attributes, then all the data links with one another, such as the encrypted, masked, sensitive, and non-sensitive attributes. In this way, the data becomes more secure from unauthorized access.

A deep learning based steganography integration framework for ad-hoc cloud computing data security augmentation using the V-BOINC system

In the early days of digital transformation, the automation, scalability, and availability of cloud computing made a big difference for business. Nonetheless, significant concerns have been raised regarding the security and privacy levels that cloud systems can provide, as enterprises have accelerated their cloud migration journeys in an effort to provide a remote working environment for their employees, primarily in light of the COVID-19 outbreak. The goal of this study is to come up with a way to improve steganography in ad hoc cloud systems by using deep learning. This research implementation is separated into two sections. In Phase 1, the "Ad-hoc Cloud System" idea and deployment plan were set up with the help of V-BOINC. In Phase 2, a modified form of steganography and deep learning were used to study the security of data transmission in ad-hoc cloud networks. In the majority of prior studies, attempts to employ deep learning models to augment or replace data-hiding systems did not achieve a high success rate. The implemented model inserts data images through colored images in the developed ad hoc cloud system. A systematic steganography model conceals from statistics lower message detection rates. Additionally, it may be necessary to incorporate small images beneath huge cover images. The implemented ad-hoc system outperformed Amazon AC2 in terms of performance, while the execution of the proposed deep steganography approach gave a high rate of evaluation for concealing both data and images when evaluated against several attacks in an ad-hoc cloud system environment.

Performance comparison between Chaos and quantum-chaos based image encryption techniques

Today's digital era has undertaken most of the responsibilities of public and private sectors, not only the industries or big organizations dependent on the internet but individual's household needs also lying on it. To make the data transmission/reception confidential and secure for both internet users and internet service providers, a large number of researches have been done in this field. It has proved that cryptography is the best solution for solving this purpose. Mostly, digital images are continuously transferring on the network rather than texts. Enciphering a digital image is a much bulkier and a complex task. It has been evident from many types of research that chaotic logistic map-based equations provide a great level of randomness. Hence Chaotic logistic maps-based image encryption techniques (also called chaos techniques) were implemented to obtain highly random cipher images. On the other hand, time consumption must be as low as it can be possible to sustain real-time communication. Presently, the advanced encryption schemes based on quantum technology have enhanced efficiency and security because of having a large key-space and less time complexity along with randomness. The quantum-chaos based encryption is done by utilizing uncertainty principles of quantum mechanics on logistic maps. This paper is an effort to compare chaos and quantum chaos-based image encryption schemes. MATLAB 2016a software is used for the execution and the comparison is made based on various security attack analyses. Based on the study and experimental results, the quantum chaos techniques used for bit plane scrambling provides better results in terms of effectiveness, efficiency, and trustworthy that can be adopted for highly secured image encryption.

Towards an optimized security approach to IoT devices with confidential healthcare data exchange

Reliable data exchange and efficient image transfer are currently significant research challenges in health care systems. To incentivize data exchange within the Internet of Things (IoT) framework, we need to ensure data sovereignty by facilitating secure data exchange between trusted parties. The security and reliability of data-sharing infrastructure require a community of trust. Therefore, this paper introduces an encryption frame based on data fragmentation. It also presents a novel, deterministic grey-scale optical encryption scheme based on fundamental mathematics. The objective is to use encryption as the underlying measure to make the data unintelligible while exploiting fragmentation to break down sensitive relationships between attributes. Thus, sensitive data distributed in separate data repositories for decryption and reconstruction using interpolation by knowing polynomial coefficients and personal values from the DBMS Database Management System. Aims also to ensure the secure acquisition of diagnostic images, micrography, and all types of medical imagery based on probabilistic approaches. Visual sharing of confidential medical imageries based on implementing a novel method, where transparencies ≤k - 1 out of n cannot reveal the original image.

Using Gene Expression Music Algorithms (GEMusicA) for the Characterization of Human Stem Cells

Gene Expression Music Algorithms (GEMusicA) use the transformation of gene expression data into melodies for the representation of sample-specific gene expression patterns. Quantitative analysis of similarities between melodies can be used for sample classification. The same algorithm can be used as simple and efficient encryption method. Here, we describe the usage of GEMusicA for the analyses of gene expression data from different stem cell types and stem cell-like tumor cells.

Data Integrity of Radiology Images Over an Insecure Network Using AES Technique

BACKGROUND

While transmitting the medical images in radiology information systems the adversary effect can break the CIA (Confidentiality, Integrity, and Availability) triads of information security. The objective of the study was to transmit the complete set of image objects in a dataset without data integrity violation.

METHODS

In this paper a hybrid cryptographic technique which combines the prime details from the patient dataset (stack of axial 2D images) and the Advanced Encryption Standard (AES) method has been proposed. The steps include a) Creating an artificial X-ray image (DRR) from the 3D volume, b) dividing the DRR image in x and y directions equally into four regions, c) applying the zig-zag pattern to each quadrant, and d) encryption of each quadrant with block cipher mode using the AES algorithm. After dataset transmission the DRR image was regenerated at the receiver and compared each of the deciphered blocks (transmitted ones) using the histogram technique.

RESULTS

The technique was tested on CT and MRI scans of sixty datasets. The image injection techniques, such as adding and deleting an image from the dataset and modifying the image pixels, were tested. The results were validated statistically using mean square error and histogram matching techniques.

CONCLUSION

The combination of the DRR and the AES technique has ensured the secured transmission of the entire dataset and not an individual image.

Strategy for optical data encryption and decryption using a D-A type stimuli-responsive AIE material

In this study, we report a new donor-acceptor (D-A) type stimuli-responsive material, (E)-4-(((9-ethyl-9H-carbazol-2-yl)methylene)amino)benzoic acid (C1), which possesses both aggregation-induced emission (AIE) and intramolecular charge transfer (ICT) natures. It glows green photoluminescence which changes into yellow color in response to mechanical stimuli, and fumigation in volatile organic compounds (VOCs) can switch the emission back to the initial state with high reversibility. In addition, the C1 film glows yellow-orange light, but turns into blue emission under continuous fumigation in ethyl acetate vapor. However the vapochromism behaves different when the C1 film is smeared: The emission of the smeared film is similar to the unsmeared but changes into cyan color after fumigation. The differences in vapochromism between smeared and unsmeared film can be easily distinguished by naked eyes. As revealed by SEM, the as-prepared film undergoes a morphology change from ill-shaped particles to microspheres in response to organic vapor, while the smeared film with scratched surface changes into dendritic patterns. According to the morphology study, the vapochromic luminescence can be ascribed to the physical adsorption of ethyl acetate vapor and the resulting change in the ICT process. In light of the unique vapochromism of C1, a new encryption-decryption technique for data recording was developed. Information can be recorded on the C1 film by mechanical writing and simultaneously concealed. It can be only accessed via fumigation in organic vapor, demonstrating a reliable steganography technology.

Encryption and authentication of security patterns by ecofriendly multi-color photoluminescent inks containing oxazolidine-functionalized nanoparticles

Counterfeiting of confidential documents has been a costly challenge for banks, companies, and customers. Encryption of invisible security marks, such as barcodes, quick response codes, and logos, in national or international confidential documents by high-security anticounterfeiting inks is the most significant solution for counterfeiting problems. Ecofriendly multi-color photoluminescent anticounterfeiting inks based on highly-fluorescent polymer nanoparticles functionalized with new oxazolidine derivatives were developed for the fast and facile encryption of security labels on cellulosic documents, such as paper currency, passport, and certificate. Depending on the polarity of functionalized polymer nanoparticles, a wide range of colors and fluorescence emissions were observed as a result of polar-polar interactions between the oxazolidine molecules and surface functional groups of the nanoparticles. The fluorescent polymer nanoparticles showed spherical, vesicular, and cauliflower-like morphologies resulted from different surface functional groups. Functional polymer nanoparticles displayed high stability and printability on cellulosic substrates due to hydrogen bonding interactions. The highly-fluorescent polymer nanoparticles were also used to prepare anticounterfeiting inks with different colors and fluorescence emissions. All the ecofriendly polymeric anticounterfeiting inks were loaded to stamps with specific marks, and then applied to different confidential documents. Printed labels displayed highly intense fluorescence emission in different colors (green, orange, pink, and purple depending on the matrix polarity) under UV irradiation (365 nm). These water-based multi-color fluorescent anticounterfeiting inks with highly intense, bright, and sensitive fluorescence emission have potential applications in encryption and authentication of security patterns.

Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication

Nano-scaled structures, wireless sensing, wearable devices, and wireless communications systems are anticipated to support the development of new next-generation technologies in the near future. Exponential rise in future Radio-Frequency (RF) sensing systems have demonstrated its applications in areas such as wearable consumer electronics, remote healthcare monitoring, wireless implants, and smart buildings. In this paper, we propose a novel, non-wearable, device-free, privacy-preserving Wi-Fi imaging-based occupancy detection system for future smart buildings. The proposed system is developed using off-the-shelf non-wearable devices such as Wi-Fi router, network interface card, and an omnidirectional antenna for future body centric communication. The core idea is to detect presence of person along its activities of daily living without deploying a device on person's body. The Wi-Fi signals received using non-wearable devices are converted into time-frequency scalograms. The occupancy is detected by classifying the scalogram images using an auto-encoder neural network. In addition to occupancy detection, the deep neural network also identifies the activity performed by the occupant. Moreover, a novel encryption algorithm using Chirikov and Intertwining map-based is also proposed to encrypt the scalogram images. This feature enables secure storage of scalogram images in a database for future analysis. The classification accuracy of the proposed scheme is 91.1%.

Optical Polarization Sensitive Ultra-Fast Switching and Photo-Electrical Device

Ultra-fast electrical switches activated with an optical-polarized light trigger, also called photo-polarized activated electrical switches, are presented. A set of new transistor circuits is switched by light from above, illuminating deep V-grooves, whose angle is sensitive to the polarization of the incident. Thus, this application may serve for encryption/decryption devices since the strongest electrical responsivity is only obtained for very specific spatial polarization directions of the illumination beam. When this V-groove is sufficiently narrow, the device mainly responds to one polarization and not to the other. In such a way, electrons are generated only for one specific polarization. While the nature of the data remains electronic, the modulation control is optic, creating a photo-induced current depending on the polarization direction. This coupled device acts as a polarization modulator as well as an intensity modulator. The article focuses on the integration of several devices in different configurations of circuitry: dual, triple, and multi-element. Case studies of several adjacent devices are presented with varying critical variables, such as the V-groove aperture dimensions. Analytical models and complementary numerical analyses are presented for the future smooth integration into Complementary Metal-Oxide-Semiconductor (CMOS) technology.

Encrypted audio dataset based on the Collatz conjecture

In information security, one way to keep a secret content is through encryption. The objective is to alter the content so that it is not intelligible, and therefore only the intended user can reveal the secret content. With the aim to provide examples of encrypted audio data, we applied a novel method of encryption based on the Collatz conjecture in five hundred speech recordings (50 speakers, 10 different messages), and then five hundred encrypted audio files were obtained. The main characteristics of our encrypted recordings are as follows: the spectrogram is quasi-uniform, histograms have a repetitive pattern, average of samples is around -0.4, standard deviation is around 0.55; Shannon entropy is around 7.5 (for 8-bits per sample). The novelty of the results consists in obtaining a completely different behavior than natural speech recordings, i.e.: spectrogram with higher energy in low frequencies, histogram with Gaussian behavior, average of samples around 0, standard deviation around 0.11, entropy around 5.5. A more comprehensive analysis of our encrypted signals may be obtained from the article "High-uncertainty audio signal encryption based on the Collatz conjecture" in the Journal of Information Security and Applications.

Medical image encryption using fractional discrete cosine transform with chaotic function

In this advanced era, where we have high-speed connectivity, it is very imperative to insulate medical data from forgery and fraud. With the regular increment in the number of internet users, it is challenging to transmit the beefy medical data. This (medical data) is always reused for different diagnosis purposes, so the information of the medical images need to be protected. This paper introduces a new scheme to ensure the safety of the medical data, which includes the use of a chaotic map on the fractional discrete cosine transform (FrDCT) coefficients of the medical data/images. The imperative FrDCT provides a high degree of freedom for the encryption of the medical images. The algorithm consists of two significant steps, i.e., application of FrDCT on an image and after that chaotic map on FrDCT coefficients. The proposed algorithm discusses the benefits of FrDCT over fractional Fourier transform (FRFT) concerning fractional order α. The key sensitivity and space of the proposed algorithm for different medical images inspire us to make a platform for other researchers to work in this area. Experiments are conducted to study different parameters and challenges. The proposed method has been compared with state-of-the-art techniques. The results suggest that our technique outperforms many other state-of-the-art techniques. Graphical Abstract Overview of the proposed algorithm.

Encrypted Oligonucleotide Arrays for Molecular Authentication

Counterfeiting is an incredibly widespread problem, with some estimates placing its economic impact above 2% of worldwide GDP. The scale of the issue suggests that current preventive measures are either technologically insufficient or too impractical and costly to be widely adopted. High-density arrays of biomolecules are explored here as security devices that can be coupled to a valuable commodity as proof of its authenticity. Light-directed DNA array fabrication technology is used to synthesize arrays that are designed to resist analysis with sequencing-by-hybridization approaches. A relatively simple sequence design strategy forces a counterfeiter to undertake a prohibitively high number of complex experiments to decipher the array sequences employed.

Data Access Control and Secured Data Sharing Approach for Health Care Data in Cloud Environment

One of the vital hitches in today's world of research is ensuring the security of the Cloud. This security can be ensured by inventing new techniques that may possibly help in safeguarding and assuring the optimal status of information in the cloud. Contents that are stored in the Cloud are majorly affected by the attempts made by illegitimate sources that are trying to access it. The security level of the contents that are stored in the cloud can be guaranteed by focusing on a task that helps in both securing and verifying the data. In order to manage the security level, (SE-KAC) which is also known as Scalable and Enhanced Key-Aggregate Cryptosystem was initiated in current research method. But this method of securing and sharing secret keys cannot be used in the stage of decryption. However this problem can be resolved in proposed method since it introduces sharing of the data securely using a method called Improved Diffie Hellman Key Exchange Algorithm (IDHKE). By introducing the Improved Diffie Hellman Key Exchange Algorithm, securely sharing the secret keys to the receivers of the data has been achieved. The secret key details can be exchanged securely using this method. By this means it makes sure its affirmations. Here the key is safely generated using one random prime number, a master secret key and parameter value. Intended for the secured and consistent access control limitation, an encryption which is attribute-based is used. The proposed method thus ensures the protected data transmission with exact and trustworthy validation.

Measurement-device-independent quantum communication without encryption

Security in communication is vital in modern life. At present, security is realized by an encryption process in cryptography. It is unbelievable if a secure communication is achievable without encryption. In quantum cryptography, there is a unique form of quantum communication, quantum secure direct communication, where secret information is transmitted directly over a quantum channel. Quantum secure direct communication is drastically distinct from our conventional concept of secure communication, because it does not require key distribution, key storage and ciphertext transmission, and eliminates the encryption procedure completely. Hence it avoids in principle all the security loopholes associated with key and ciphertext in traditional secure communications. For practical implementation, defects always exist in real devices and it may downgrade the security. Among the various device imperfections, those with the measurement devices are the most prominent and serious ones. Here we report a measurement-device-independent quantum secure direct communication protocol using Einstein-Podolsky-Rosen pairs. This protocol eradicates the security vulnerabilities associated with the measurement device, and greatly enhances the practical security of quantum secure direct communication. In addition to the security advantage, this protocol has an extended communication distance, and a high communication capacity.

Multiuser communication scheme based on binary phase-shift keying and chaos for telemedicine

BACKGROUND AND OBJECTIVES

Currently, telemedicine is levered upon the improvement in communication network technology such as Body Area Sensor Networks (BASN) to provided biomedicine solutions. Nevertheless, information security is an important issue since biomedical data is exchanged through insecure channels, which exposes private information that can be intercepted by malicious intruder. Therefore, secure communication protocols for multiuser networks in telemedicine applications are a big challenge. Recent chaos-based encryption works have been conducted in the area of medical secure communications with high security capabilities. However, none of them has considered multiuser network, which is used in several e-health applications. Up to our knowledge, the proposed protocol is the first attempt to consider this service in secure telemedicine. In this paper, we propose a novel scheme based on binary phase-shift key (BPSK) and chaos to provide information security at biosignals in a multiuser network system transmitting data over single channel.

METHODS

The proposed scheme uses the two-dimensional Hénon map with enhance pseudorandom sequences and CDMA technique to achieve multiuser encryption process and transmit data over a single channel. We use biosignals such as electrocardiograms (ECG) and blood pressure (PB) signals from PhisioBank ATM data base for simulation results at MatLab software. We evaluate the security and performance by determining the secret key space, secret key sensitivity, resistance against noise attack with quality analysis by using BER, MSE, and PSNR, encryption-decryption time, and throughput.

RESULTS

In simulations tests, biosignals of ECG and BP in a BANS network are encrypted and transmitted over shared wireless channels and just authorized medical personal can retrieve such information with corresponding secret key from the cryptogram, that appears as noise to any intruder. The proposed multiuser scheme support high noise and interference attacks efficiently in contrast with classic chaos-based encryption works for telemedicine, where some scenarios are simulated with very low BER, very low MSE, and high PSNR between plain biosignals and recovered biosignals when high AWGN noise is added to encrypted-transmitted signal. In addition, the encryption process presents enough key space and high sensitivity at secret key. A comparative analysis of proposed method and recent existing works was also presented.

CONCLUSIONS

Patients can be monitored and diagnosed opportunely remotely and all their medical information is transmitted securely to the correct specialist. Also, it is possible to transmit several electrophysiological signals in a single channel in a secure multiuser network at low cost optimizing the use of available bandwidth for telemedicine applications.

Synergistic Information Processing Encrypts Strategic Reasoning in Poker

There is a tendency in decision-making research to treat uncertainty only as a problem to be overcome. But it is also a feature that can be leveraged, particularly in social interaction. Comparing the behavior of profitable and unprofitable poker players, we reveal a strategic use of information processing that keeps decision makers unpredictable. To win at poker, a player must exploit public signals from others. But using public inputs makes it easier for an observer to reconstruct that player's strategy and predict his or her behavior. How should players trade off between exploiting profitable opportunities and remaining unexploitable themselves? Using a recent multivariate approach to information theoretic data analysis and 1.75 million hands of online two-player No-Limit Texas Hold'em, we find that the important difference between winning and losing players is not in the amount of information they process, but how they process it. In particular, winning players are better at integrative information processing-creating new information from the interaction between their cards and their opponents' signals. We argue that integrative information processing does not just produce better decisions, it makes decision-making harder for others to reverse engineer, as an expert poker player's cards act like the private key in public-key cryptography. Poker players encrypt their reasoning with the way they process information. The encryption function of integrative information processing makes it possible for players to exploit others while remaining unexploitable. By recognizing the act of information processing as a strategic behavior in its own right, we offer a detailed account of how experts use endemic uncertainty to conceal their intentions in high-stakes competitive environments, and we highlight new opportunities between cognitive science, information theory, and game theory.

MEAS: memory encryption and authentication secure against side-channel attacks

Memory encryption is used in many devices to protect memory content from attackers with physical access to a device. However, many current memory encryption schemes can be broken using differential power analysis (DPA). In this work, we present Meas-the first Memory Encryption and Authentication Scheme providing security against DPA attacks. The scheme combines ideas from fresh re-keying and authentication trees by storing encryption keys in a tree structure to thwart first-order DPA without the need for DPA-protected cryptographic primitives. Therefore, the design strictly limits the use of every key to encrypt at most two different plaintext values. Meas prevents higher-order DPA without changes to the cipher implementation by using masking of the plaintext values. Meas is applicable to all kinds of memory, e.g., NVM and RAM. For RAM, we give two concrete Meas instances based on the lightweight primitives Ascon, PRINCE, and QARMA. We implement and evaluate both instances on a Zynq XC7Z020 FPGA showing that Meas has memory and performance overhead comparable to existing memory authentication techniques without DPA protection.

Are privacy-enhancing technologies for genomic data ready for the clinic? A survey of medical experts of the Swiss HIV Cohort Study

PURPOSE

Protecting patient privacy is a major obstacle for the implementation of genomic-based medicine. Emerging privacy-enhancing technologies can become key enablers for managing sensitive genetic data. We studied physicians' attitude toward this kind of technology in order to derive insights that might foster their future adoption for clinical care.

METHODS

We conducted a questionnaire-based survey among 55 physicians of the Swiss HIV Cohort Study who tested the first implementation of a privacy-preserving model for delivering genomic test results. We evaluated their feedback on three different aspects of our model: clinical utility, ability to address privacy concerns and system usability.

RESULTS

38/55 (69%) physicians participated in the study. Two thirds of them acknowledged genetic privacy as a key aspect that needs to be protected to help building patient trust and deploy new-generation medical information systems. All of them successfully used the tool for evaluating their patients' pharmacogenomics risk and 90% were happy with the user experience and the efficiency of the tool. Only 8% of physicians were unsatisfied with the level of information and wanted to have access to the patient's actual DNA sequence.

CONCLUSION

This survey, although limited in size, represents the first evaluation of privacy-preserving models for genomic-based medicine. It has allowed us to derive unique insights that will improve the design of these new systems in the future. In particular, we have observed that a clinical information system that uses homomorphic encryption to provide clinicians with risk information based on sensitive genetic test results can offer information that clinicians feel sufficient for their needs and appropriately respectful of patients' privacy. The ability of this kind of systems to ensure strong security and privacy guarantees and to provide some analytics on encrypted data has been assessed as a key enabler for the management of sensitive medical information in the near future. Providing clinically relevant information to physicians while protecting patients' privacy in order to comply with regulations is crucial for the widespread use of these new technologies.

Medical Images are Safe - an Enhanced Chaotic Scrambling Approach

The patient data confidentiality is one of the vital security aspects in e-Health and m-Health services. In particular, providing confidentiality to the patient's medical image is essential and the protection approaches have to be explored in-depth due to the rapid progress in the technologies of teleradiology and PACS. In this study, the pseudo random number generators (PRNGs), namely, the linear congruential generator (LCG) and XOR shift generator (XSG) are improved and combined with improved logistic 2D coupled chaotic map to provide enhanced chaos based encryption. The proposed scheme encrypts the Digital Imaging and Communication in Medicine (DICOM) images to protect the patient confidentiality during the storage and transfer in radiological information system (RIS). The cipher image was measured with various security analyses and tested with different test suites to prove its randomness.

Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm

Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and availability), the confidentiality is the most essential feature for exchanging medical images among physicians. The Goldreich Goldwasser Halevi (GGH) algorithm can be a good choice for encrypting medical images as both the algorithm and sensitive data are represented by numeric matrices. Additionally, the GGH algorithm does not increase the size of the image and hence, its complexity will remain as simple as O(n²). However, one of the disadvantages of using the GGH algorithm is the Chosen Cipher Text attack. In our strategy, this shortcoming of GGH algorithm has been taken in to consideration and has been improved by applying the padding (i.e., snail tour XORing), before the GGH encryption process. For evaluating their performances, three measurement criteria are considered including (i) Number of Pixels Change Rate (NPCR), (ii) Unified Average Changing Intensity (UACI), and (iii) Avalanche effect. The results on three different sizes of images showed that padding GGH approach has improved UACI, NPCR, and Avalanche by almost 100%, 35%, and 45%, respectively, in comparison to the standard GGH algorithm. Also, the outcomes will make the padding GGH resist against the cipher text, the chosen cipher text, and the statistical attacks. Furthermore, increasing the avalanche effect of more than 50% is a promising achievement in comparison to the increased complexities of the proposed method in terms of encryption and decryption processes.

Secured Medical Images - a Chaotic Pixel Scrambling Approach

In this paper, a cryptosystem is proposed to encrypt 16-bit monochrome DICOM image using enhanced chaotic economic map. A new enhanced chaotic economic map (ECEM) is designed from the chaotic economic map which has better bifurcation nature and positive Lyapunov exponent values. In order to improve the sternness of the encryption algorithm, the enhanced chaotic map is employed to generate the pixel permutation, masking, and swapping sequences. The substitution operation is introduced in-between the standard permutation and diffusion operations. The robustness of the proposed image encryption algorithm is measured by various analyses such as histogram, key sensitivity, key space, number of pixel change rate (NPCR), unified average change intensity (UACI), information entropy and correlation coefficient. The results of the security analyses are compared with existing algorithms to validate that the proposed algorithm is better in terms of larger key space to resist brute force attacks and other common attacks on encryption.

A secure and efficiently searchable health information architecture

Patient-centric repositories of health records are an important component of health information infrastructure. However, patient information in a single repository is potentially vulnerable to loss of the entire dataset from a single unauthorized intrusion. A new health record storage architecture, the personal grid, eliminates this risk by separately storing and encrypting each person's record. The tradeoff for this improved security is that a personal grid repository must be sequentially searched since each record must be individually accessed and decrypted. To allow reasonable search times for large numbers of records, parallel processing with hundreds (or even thousands) of on-demand virtual servers (now available in cloud computing environments) is used. Estimated search times for a 10 million record personal grid using 500 servers vary from 7 to 33min depending on the complexity of the query. Since extremely rapid searching is not a critical requirement of health information infrastructure, the personal grid may provide a practical and useful alternative architecture that eliminates the large-scale security vulnerabilities of traditional databases by sacrificing unnecessary searching speed.

Diagonal queue medical image steganography with Rabin cryptosystem

The main purpose of this work is to provide a novel and efficient method to the image steganography area of research in the field of biomedical, so that the security can be given to the very precious and confidential sensitive data of the patient and at the same time with the implication of the highly reliable algorithms will explode the high security to the precious brain information from the intruders. The patient information such as patient medical records with personal identification information of patients can be stored in both storage and transmission. This paper describes a novel methodology for hiding medical records like HIV reports, baby girl fetus, and patient’s identity information inside their Brain disease medical image files viz. scan image or MRI image using the notion of obscurity with respect to a diagonal queue least significant bit substitution. Data structure queue plays a dynamic role in resource sharing between multiple communication parties and when secret medical data are transferred asynchronously (secret medical data not necessarily received at the same rate they were sent). Rabin cryptosystem is used for secret medical data writing, since it is computationally secure against a chosen-plaintext attack and shows the difficulty of integer factoring. The outcome of the cryptosystem is organized in various blocks and equally distributed sub-blocks. In steganography process, various Brain disease cover images are organized into various blocks of diagonal queues. The secret cipher blocks and sub-blocks are assigned dynamically to selected diagonal queues for embedding. The receiver gets four values of medical data plaintext corresponding to one ciphertext, so only authorized receiver can identify the correct medical data. Performance analysis was conducted using MSE, PSNR, maximum embedding capacity as well as by histogram analysis between various Brain disease stego and cover images.

Distributed clinical data sharing via dynamic access-control policy transformation

BACKGROUND

Data sharing in electronic health record (EHR) systems is important for improving the quality of healthcare delivery. Data sharing, however, has raised some security and privacy concerns because healthcare data could be potentially accessible by a variety of users, which could lead to privacy exposure of patients. Without addressing this issue, large-scale adoption and sharing of EHR data are impractical. The traditional solution to the problem is via encryption. Although encryption can be applied to access control, it is not applicable for complex EHR systems that require multiple domains (e.g. public and private clouds) with various access requirements.

OBJECTIVES

This study was carried out to address the security and privacy issues of EHR data sharing with our novel access-control mechanism, which captures the scenario of the hybrid clouds and need of access-control policy transformation, to provide secure and privacy-preserving data sharing among different healthcare enterprises.

METHODS

We introduce an access-control mechanism with some cryptographic building blocks and present a novel approach for secure EHR data sharing and access-control policy transformation in EHR systems for hybrid clouds.

RESULTS

We propose a useful data sharing system for healthcare providers to handle various EHR users who have various access privileges in different cloud environments. A systematic study has been conducted on data sharing in EHR systems to provide a solution to the security and privacy issues.

CONCLUSIONS

In conclusion, we introduce an access-control method for privacy protection of EHRs and EHR policy transformation that allows an EHR access-control policy to be transformed from a private cloud to a public cloud. This method has never been studied previously in the literature. Furthermore, we provide a protocol to demonstrate policy transformation as an application scenario.

Medical data sheet in safe havens - A tri-layer cryptic solution

Secured sharing of the diagnostic reports and scan images of patients among doctors with complementary expertise for collaborative treatment will help to provide maximum care through faster and decisive decisions. In this context, a tri-layer cryptic solution has been proposed and implemented on Digital Imaging and Communications in Medicine (DICOM) images to establish a secured communication for effective referrals among peers without compromising the privacy of patients. In this approach, a blend of three cryptic schemes, namely Latin square image cipher (LSIC), discrete Gould transform (DGT) and Rubik׳s encryption, has been adopted. Among them, LSIC provides better substitution, confusion and shuffling of the image blocks; DGT incorporates tamper proofing with authentication; and Rubik renders a permutation of DICOM image pixels. The developed algorithm has been successfully implemented and tested in both the software (MATLAB 7) and hardware Universal Software Radio Peripheral (USRP) environments. Specifically, the encrypted data were tested by transmitting them through an additive white Gaussian noise (AWGN) channel model. Furthermore, the sternness of the implemented algorithm was validated by employing standard metrics such as the unified average changing intensity (UACI), number of pixels change rate (NPCR), correlation values and histograms. The estimated metrics have also been compared with the existing methods and dominate in terms of large key space to defy brute force attack, cropping attack, strong key sensitivity and uniform pixel value distribution on encryption.