A two‐stage privacy protection mechanism based on blockchain in mobile crowdsourcing

Differential privacy protection algorithm for network sensitive information based on singular value decomposition

In order to reduce the risk of data privacy disclosure and improve the effect of information privacy protection, a differential privacy protection algorithm for network sensitive information based on singular value decomposition is proposed. TF-IDF method is used to extract network sensitive information text. By comparing the word frequency of network sensitive information, high word frequency word elements in network information content are collected to obtain the mining results of network sensitive information text. According to the decision tree theory, the equal difference privacy budget allocation mechanism is improved to achieve equal difference privacy budget allocation. By discarding some small singular values and corresponding spectral vectors, the data can be disturbed, and the availability of the original data can be retained, so that it can truly represent the original data set structure. According to the results of equal difference privacy budget allocation and singular value decomposition disturbance, the data of high-dimensional network graph is reduced by random projection, singular value decomposition is performed on the reduced data, and Gaussian noise is added to the singular value. Finally, the matrix to be published is generated through the inverse operation of singular value decomposition to achieve differential privacy protection of network sensitive information. The experimental results show that the privacy protection quality of this algorithm is high and the data availability is effectively improved.

Multi-Dimensional Sport Physique Evaluation and Ranking for Healthcare Based on TOPSIS

Typically, through monitoring, collecting, integrating and analyzing the sport scores of individuals, we can know about the sport physique of the individuals in a real-time manner, so as to further guarantee a high-quality health level of people. However, in the abovementioned sport scores-based sport physique monitoring scenario, two major challenges are raised. First, the collected sport scores for sport physique monitoring are often multi-dimensional, which make it hard to evaluate the sport physique of individuals fairly and reasonably. Moreover, the multiple dimensions of sport scores are often of different weights or significances, which raise a challenging task to objectively evaluate the sport physique of an individual. Considering these challenges, a novel multi-dimensional sport physique evaluation and ranking method, named MSPER, is proposed in this research work for better healthcare for individuals, which is based on the TOPSIS theory. At last, a case study is presented to show the concrete procedure of MSPER method.