Research on Privacy Security Risk Assessment Method of Mobile Commerce Based on Information Entropy and Markov

Zhang, Tao; Zhao, Kun; Yang, Ming; Gao, Tilei; Xie, Wanyu

doi:10.1155/2020/8888296

Cited by 9 publications

(8 citation statements)

References 26 publications

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“…In addition, using this method requires the establishment of a special trust chain, and the cost of assessment is high. erefore, as a risk assessment method, in order to illustrate the characteristics of the method proposed in this paper, it should be compared with other common risk assessment methods, such as risk assessment method based on AHP [45][46][47], risk assessment method based on risk matrix [48,49], and risk assessment method based on information entropy [26,[49][50][51][52]. ey are all mature risk assessment methods, which have been widely used and can provide users with effective risk assessment results.…”

Section: Methods Comparisonmentioning

confidence: 99%

“…Xiang [24] built a risk index system of personal privacy information disclosure of mobile commerce consumers and evaluated the risk of consumer privacy disclosure through the fuzzy comprehensive assessment method. Shi et al [25], Zhang [26], and Yang [27] used the information entropy method to measure and assess the privacy risk according to the uncertainty of information. Ali-Eldin et al [28] proposed a privacy risk assessment model, which can provide effective privacy risk avoidance and mitigation measures for open data.…”

Section: Related Researchmentioning

confidence: 99%

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Comprehensive Assessment of Mobile Service Privacy Security Based on FAHP and D–S Theory

Yang

Gao

Jiang

et al. 2022

Wireless Communications and Mobile Computing

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As an indispensable medium for people’s daily life and communication, mobile applications provide users with a variety of services. In order to enjoy these services, users inevitably need to provide personal privacy information or authorization to application providers in the process of use. In the case of insufficient privacy security evaluation, even if users use the applications verified by the application market, their privacy security will be threatened because of their weak awareness of privacy protection. Therefore, in order to ensure the privacy security of users, this paper establishes a mobile service assessment attribute model including 3 risk categories and 11 risk indicators. Based on this model, this paper proposes a service risk weight assessment method based on FAHP (fuzzy analytical hierarchy process), defines the risk level and its trust degree from two aspects of risk frequency and risk loss, and puts forward a reasonable fusion method for different assessment results of risk level based on D–S (Dempster–Shafer) theory, so as to realize the multidimensional and multilayer assessment of mobile service risk. Finally, the case analysis shows that the method proposed in this paper is reasonable and feasible and has important value for improving the security of mobile services and managing users’ privacy information.

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Section: Methods Comparisonmentioning

confidence: 99%

Section: Related Researchmentioning

confidence: 99%

Comprehensive Assessment of Mobile Service Privacy Security Based on FAHP and D–S Theory

Yang

Gao

Jiang

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

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“…Markov chain [54] is a process with discrete set and random state space. It is suitable for analyzing things with random process.…”

Section: Assessment Of Cloud Service Trustworthiness State Based On M...mentioning

confidence: 99%

The Assessment of Cloud Service Trustworthiness State Based on D-S Theory and Markov Chain

et al. 2022

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The massive cloud service market is full of various services with uneven quality. Even the services that have passed the platform detection will have unknown trustworthiness problems in the actual use process. The risk environment of the cloud service determines that its trustworthiness is random. The static trustworthiness assessment results can only reflect the cloud service trustworthiness at a certain time, not enough to reflect the real trustworthiness of the cloud service. To objectively reflect the trustworthiness of the cloud service, it is necessary to further assess the cloud service trustworthiness state and its changes on the basis of trustworthiness level measurement. To solve this problem, this paper combs the trustworthiness indicators of the cloud service, puts forward an effective assessment method of cloud service trustworthiness level based on D-S theory, and puts forward the representation method of cloud service trustworthiness state and its transition state combined with Markov chain, so as to realize the effective assess of cloud service trustworthiness state and its changes. Finally, through case analysis, it shows that the method proposed in this paper is feasible, can effectively assess the cloud service trustworthiness state and its changes, and provide users with detailed assessment results, so as to help users make reasonable service selection and trustworthiness management. This research has important research significance for ensuring the trustworthiness of the cloud service and improving the security of cloud service market.

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“…With the continuous development and progress of Internet technology, information security and privacy protection have attracted more and more attention [1][2][3][4][5][6][7]. e development of scienti c and technological revolution has promoted the advent of the Internet era, and computer intelligent image recognition technology is becoming more and more mature [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Image Recognition and Encryption Algorithm Based on Artificial Neural Network and Multidimensional Chaotic Sequence

Feng

Chen

2022

Computational Intelligence and Neuroscience

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With the continuous development of Internet technology and technological innovation, image recognition technologies such as face unlocking and face brushing payment have gradually entered daily life. However, it can not be ignored that these technologies not only bring us great convenience but also face great risks. The biological characteristics of a face image are unique, and it will be difficult to modify once it is leaked. If the image information stored in the cloud is leaked because it cannot be properly kept, users have no privacy. The encryption and recognition of face image can effectively solve this problem. Aiming at this, high-dimensional chaos Henon Map and one-dimensional chaos Logistic Map are used to generate a key to complete the encryption of the image in the transformation domain, and the capacity and complexity of the key are further enhanced. Then, combined with BP neural network to achieve face image recognition. Finally, the robustness of the proposed algorithm is verified and analyzed by conventional attacks, geometric attacks, and occlusion attacks.

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Research on Privacy Security Risk Assessment Method of Mobile Commerce Based on Information Entropy and Markov

Cited by 9 publications

References 26 publications

Comprehensive Assessment of Mobile Service Privacy Security Based on FAHP and D–S Theory

Comprehensive Assessment of Mobile Service Privacy Security Based on FAHP and D–S Theory

The Assessment of Cloud Service Trustworthiness State Based on D-S Theory and Markov Chain

Image Recognition and Encryption Algorithm Based on Artificial Neural Network and Multidimensional Chaotic Sequence

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