A Temporal Logic Based Approach to Multi-Agent Intrusion Detection and Prevention

Multi-agent architectures have been successful in attaining considerable attention among computer security researchers. This is so, because of their demonstrated capabilities such as autonomy, embedded intelligence, learning and self-growing knowledge-base, high scalability, fault tolerance, and automatic parallelism. These characteristics have made this technology a de facto standard for developing ambient security systems to meet the open and dynamic nature of today's online communities. Although multi-agent architectures are increasingly studied in the area of computer security, there is still not enough empirical evidence on their performance in intrusions and attacks detection. The aim of this paper is to report the systematic literature review conducted in the context of specific research questions, to investigate multi-agent IDS architectures to highlight the issues that affect their performance in terms of detection accuracy and response time. We used pertinent keywords and terms to search and retrieve the most recent research studies, on multi-agent IDS architectures, from the major research databases and digital libraries such as SCOPUS, Springer, and IEEE Explore. The search processes resulted in a number of studies; among them, there were journal articles, book chapters, conference papers, dissertations, and theses. The obtained studies were assessed and filtered out, and finally, there were over 71 studies chosen to answer the research questions. The results of this study have shown that multi-agent architectures include several advantages that can help in the development of ambient IDS. However, it has been found that there are several issues in the current multi-agent IDS architectures that may degrade the accuracy and response time of intrusions and attacks detection. Based on our findings, the issues of multi-agent IDS architectures include limitations in the techniques, mechanisms, and schemes used for multi-agent IDS adaptation and learning, load balancing, scalability, fault-tolerance, and high communication overhead. It has also been found that new measurement metrics are required for evaluating multi-agent IDS architectures.

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A Survey on Malware and Malware Detection Systems

Saeed¹,

Selamat²,

Abuagoub³

2013

IJCA

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Over the last decades, there were lots of studies made on malware and their countermeasures. The most recent reports emphasize that the invention of malicious software is rapidly increasing. Moreover, the intensive use of networks and Internet increases the ability of the spreading and the effectiveness of this kind of software. On the other hand, researchers and manufacturers making great efforts to produce anti-malware systems with effective detection methods for better protection on computers. In this paper, a detailed review has been conducted on the current situation of malware infection and the work done to improve anti-malware or malware detection systems. Thus, it provides an up-to-date comparative reference for developers of malware detection systems.

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A Temporal Logic Based Approach to Multi-Agent Intrusion Detection and Prevention

Cited by 3 publications

References 17 publications

Logical Inference Framework for Security Management in Geographical Information Systems

Logical Inference Framework for Security Management in Geographical Information Systems

A Systematic State-of-the-Art Analysis of Multi-Agent Intrusion Detection

A Survey on Malware and Malware Detection Systems

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