Abnormal User Detection Based on the Correlation Probabilistic Model
Joint Authors
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-13
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
As an important part of the new generation of information technology, the Internet of Things (IoT), which is developing rapidly, requires high user security.
However, malicious nodes located in an IoT network can influence user security.
Abnormal user detection and correlation probability analysis are fundamental and challenging problems.
In this paper, the probabilistic model of the correlation between abnormal users (PMCAU) is proposed.
First, the concept of user behavior correlation degree is proposed, which is defined as two parts: user attribute similarity degree and behavior interaction degree; the attribute similarity measurement algorithm and behavior correlation measurement algorithm are constructed, respectively, and the spontaneous and interactive behaviors of users were analyzed to determine the abnormal correlated users.
Second, first-order logic grammar is used to express the before and after connection of user behavior and to deduce the probabilistic of occurrence of the correlation of behavior and determine the abnormal user groups.
Experimental results show that, compared with the traditional anomaly detection algorithm and Markov logic network, this model can identify the users correlated with anomalies, make probabilistic inferences on the possible associations, and identify the potential abnormal user groups, thus achieving higher accuracy and predictability in the IoT.
American Psychological Association (APA)
Yang, Xiaohui& Sun, Ying. 2020. Abnormal User Detection Based on the Correlation Probabilistic Model. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1208560
Modern Language Association (MLA)
Yang, Xiaohui& Sun, Ying. Abnormal User Detection Based on the Correlation Probabilistic Model. Security and Communication Networks No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1208560
American Medical Association (AMA)
Yang, Xiaohui& Sun, Ying. Abnormal User Detection Based on the Correlation Probabilistic Model. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1208560
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208560