Network User Behavior Authentication Based on Hidden Markov Model

Wu, Zenan; Tian, Li; Wang, Zhigang; Wang, Yan

doi:10.1109/icicse52190.2021.9404100

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…In addition, the parameters, such as the time window in continuous trust evaluation, are set manually and lack adaptivity [2][3][4][5][6][7]. At present, research on trust evaluation models mainly can be mainly divided into two categories based on multi-attribute evaluation models [8][9][10] and machine learning models [11], both of which attach importance to the mining of multidimensional historical behavioral evidence information of network entities and the continuity and adaptiveness of the trust evaluation process. However, these methods lack the study of historical behavioral data time windows.…”

Section: Introductionmentioning

confidence: 99%

Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window

Yang

Han

Long

et al. 2023

Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023)

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At present, the time window setting of the multi-entity continuous trust evaluation model in the power mobile Internet environment lacks adaptability. The semantic retention of time series data is significant to time window setting. A trust evaluation model based on the graph model and semantic time window may provide a solution. Firstly, we analyze the entity interactions in the electric power mobile network environment and construct a global trust path diagram by combining the entropy scoring results of evidence data in this paper. Secondly, a semantic time window algorithm is proposed by combining the parameter-seeking process of the sequential data compression algorithm. Finally, update the trust value dynamically by combining the number of feature changes of entities in the global trust path graph and the semantic time window. Simulation experiments are conducted to analyze the trust value updating algorithm based on the graph model and semantic time window proposed in this paper. The experimental results show that the algorithm is feasible and accurate.

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Section: Introductionmentioning

confidence: 99%

Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window

Yang

Han

Long

et al. 2023

Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023)

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Behavioral Authentication for Security and Safety

Wang,

Zhu

2024

Universal Behavior Computing for Security and Safety

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Behavioral authentication for security and safety

Wang,

Tang,

Zhu

et al. 2024

Security and Safety

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The issues of both system security and safety can be dissected integrally from the perspective of behavioral \emph{appropriateness}. That is, a system is secure or safe can be judged by whether the behavior of certain agent(s) is \emph{appropriate} or not. Specifically, a so-called \emph{appropriate behavior} involves the right agent performing the right actions at the right time under certain conditions. Then, according to different levels of appropriateness and degrees of custodies, behavioral authentication can be graded into three levels, i.e., the authentication of behavioral \emph{Identity}, \emph{Conformity}, and \emph{Benignity}. In a broad sense, for the security and safety issue, behavioral authentication is not only an innovative and promising method due to its inherent advantages but also a critical and fundamental problem due to the ubiquity of behavior generation and the necessity of behavior regulation in any system. By this classification, this review provides a comprehensive examination of the background and preliminaries of behavioral authentication. It further summarizes existing research based on their respective focus areas and characteristics. The challenges confronted by current behavioral authentication methods are analyzed, and potential research directions are discussed to promote the diversified and integrated development of behavioral authentication.

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Network User Behavior Authentication Based on Hidden Markov Model

Cited by 4 publications

References 15 publications

Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window

Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window

Behavioral Authentication for Security and Safety

Behavioral authentication for security and safety

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