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Jyothi KK, Borra SR, Srilakshmi K, Balachandran PK, Reddy GP, Colak I, Dhanamjayulu C, Chinthaginjala R, Khan B. A novel optimized neural network model for cyber attack detection using enhanced whale optimization algorithm. Sci Rep 2024; 14:5590. [PMID: 38453945 DOI: 10.1038/s41598-024-55098-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 02/20/2024] [Indexed: 03/09/2024] Open
Abstract
Cybersecurity is critical in today's digitally linked and networked society. There is no way to overestimate the importance of cyber security as technology develops and becomes more pervasive in our daily lives. Cybersecurity is essential to people's protection. One type of cyberattack known as "credential stuffing" involves using previously acquired usernames and passwords by attackers to access user accounts on several websites without authorization. This is feasible as a lot of people use the same passwords and usernames on several different websites. Maintaining the security of online accounts requires defence against credential-stuffing attacks. The problems of credential stuffing attacks, failure detection, and prediction can be handled by the suggested EWOA-ANN model. Here, a novel optimization approach known as Enhanced Whale Optimization Algorithm (EWOA) is put on to train the neural network. The effectiveness of the suggested attack identification model has been demonstrated, and an empirical comparison will be carried out with respect to specific security analysis.
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Affiliation(s)
- Koganti Krishna Jyothi
- Department of Computer Science and Engineering, Geethanjali College of Engineering and Technology, Hyderabad, TS, 501301, India
| | - Subba Reddy Borra
- Department of Information Technology, Malla Reddy Engineering College for Women, Hyderabad, TS, India
| | - Koganti Srilakshmi
- Department of Electrical and Electronics Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, TS, 501301, India
| | - Praveen Kumar Balachandran
- Department of Electrical and Electronics Engineering, Vardhaman College of Engineering, Hyderabad, TS, 501218, India
| | - Ganesh Prasad Reddy
- Department of Electrical and Electronics Engineering, AM Reddy Memeorial College of Engineering, Guntur, AP, India
| | - Ilhami Colak
- Department of Electrical and Electronics Engineering, Faculty of Engineering and Architectures, Nisantasi University, 34398, Istanbul, Turkey
| | - C Dhanamjayulu
- School of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
| | | | - Baseem Khan
- Department of Electrical and Computer Engineering, Hawassa University, Hawassa 05, Ethiopia.
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Srilakshmi K, Santosh DT, Ramadevi A, Balachandran PK, Reddy GP, Palanivelu A, Colak I, Dhanamjayulu C, Chinthaginjala RK, Khan B. Development of renewable energy fed three-level hybrid active filter for EV charging station load using Jaya grey wolf optimization. Sci Rep 2024; 14:4429. [PMID: 38396163 DOI: 10.1038/s41598-024-54550-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
This work develops a hybrid active power filter (HAPF) in this article to operate in conjunction with the energy storage system (ESS), wind power generation system (WPGS), and solar energy system (SES). It employs three level shunt voltage source converters (VSC) connected to the DC-bus. Optimization of the gain values of the fractional-order proportional integral derivative controller (FOPIDC) and parameter values of the HAPF is achieved using the Jaya grey wolf hybrid algorithm (GWJA). The primary objectives of this study, aimed at enhancing power quality (PQ), include: (1) ensuring swift stabilization of DC link capacitor voltage (DCLCV); (2) reducing harmonics and improving power factor (PF); (3) maintaining satisfactory performance under different combinations of loads like EV charging load, non linear load and solar irradiation conditions. The proposed controller's performance is evaluated through three test scenarios featuring different load configurations and irradiation levels. Additionally, the HAPF is subjected to design using other optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) to assess their respective contributions to PQ improvement.
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Affiliation(s)
- Koganti Srilakshmi
- Department of Electrical and Electronics Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, TS, 501301, India
| | - D Teja Santosh
- CVR College of Engineering/Computer Science and Engineering, Hyderabad, India
| | - Alapati Ramadevi
- Department of Electrical and Electronic Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Kanuru, Vijayawada, Andhra Pradesh, India
| | - Praveen Kumar Balachandran
- Department of Electrical and Electronics Engineering, Vardhaman College of Engineering, Hyderabad, TS, 501218, India
| | - Ganesh Prasad Reddy
- Department of Electrical and Electronics Engineering, AM Reddy Memeorial College of Engineering, Guntur, AP, India
| | | | - Ilhami Colak
- Department of Electrical and Electronics Engineering, Faculty of Engineering and Architectures, Nisantasi University, 34398, Istanbul, Turkey
| | - C Dhanamjayulu
- School of Electrical Engineering, Vellore Institute of Technology, Vellore, India.
| | | | - Baseem Khan
- Department of Electrical and Computer Engineering, Hawassa University, P.O. Box 05, Hawassa, Ethiopia.
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Venkatesan Y, Srilakshmi K, Palanivelu A. Modified soccer game optimization and its application on power flow and distribution generation placement problems of distribution systems. Evol Intel 2021. [DOI: 10.1007/s12065-021-00677-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Mohandass J, Ravichandran S, Srilakshmi K, Rajadurai CP, Sanmugasamy S, Kumar GR. BCDB - A database for breast cancer research and information. Bioinformation 2010; 5:1-3. [PMID: 21346869 PMCID: PMC3039995 DOI: 10.6026/97320630005001] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2010] [Accepted: 03/02/2010] [Indexed: 11/25/2022] Open
Abstract
In pursuit of a better updated source including ‘omics’ information for breast cancer, Breast Cancer Database (BCDB) has been developed to provide the researcher with the quick overview of the Breast cancer disease and other relevant information. This database comprises of myriad of information about genes involved in breast cancer, its functions and drug molecules which are currently being used in the treatment of breast cancer. The data available in BCDB is
retrieved from the biomedical research literature. It facilitates the user to search information on gene, its location in chromosome, functions and its importance
in cancer diseases. Broadly, this can be queried by giving gene name, protein name and drug name. This database is platform independent, user friendly and
freely accessible through internet. The data present in BCDB is directly linked to other on-line resources such as NCBI, PDB and PubMed. Hence, it can act as
a complete web resource comprising gene sequences, drug structures and literature information related to breast cancer, which is not available in any other
breast cancer database.
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Affiliation(s)
| | | | | | | | - Sangeetha Sanmugasamy
- Bioinformatics Lab, AU-KBC Research Centre, M.I.T Campus of Anna University, Chennai 600044, India
| | - Gopal Ramesh Kumar
- Bioinformatics Lab, AU-KBC Research Centre, M.I.T Campus of Anna University, Chennai 600044, India
- Gopal Ramesh Kumar: Phone: +91-44-2223 2711; Fax: +91-44-2223 1034/7073
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