A Security Situation Awareness Approach for IoT Software Chain Based on Markov Game Model

Author
Keywords
Abstract
Since Internet of Things (IoT) has been widely used in our daily life nowadays, it is regarded as a promising and popular application of the Internet, and has attracted more and more attention. However, IoT is also suffered by some security problems which seriously affect the implementation of IoT system. Similar to traditional software, IoT software is always threated by many vulnerabilities, thus how to evaluate the security situation of IoT software chain becomes a basic requirement. In this paper, A framework of security situation awareness for IoT software chain is proposed, which mainly includes two processes: IoT security situation classification based on support vector machine and security situation awareness based on Markov game model. The proposed method firstly constructs a classification model using support vector machine (IoT) to automatically evaluates the security situation of IoT software chain. Based on the situation classification, we further proposed to adopt Markov model to simulate and predict the next behaviors of participants that involved in IoT system. Additionally, we have designed and developed a security situation awareness system for IoT software chain, the developed system supports the detection of typical IoT vulnerabilities and inherits more than 20 vulnerability detection methods, which shows great potential in IoT system protection.
Year of Publication
2022
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
7
Issue
Special Issue on Multimedia Streaming and Processing in Internet of Things with Edge Intelligence
Number
5
Number of Pages
59-65
Date Published
09/2022
ISSN Number
1989-1660
URL
https://www.ijimai.org/journal/sites/default/files/2022-08/ijimai_7_5_7.pdf
DOI
10.9781/ijimai.2022.08.002
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