Biblio

This paper proposes a new strategy, named resident strategy, for defending IoT networks from repeated infection of malicious botnets in the Botnet Defense System (BDS). The resident strategy aims to make a small-scale white-hat botnet resident in the network respond immediately to invading malicious botnets. The BDS controls the resident white-hat botnet with two parameters: upper and lower number of its bots. The lower limit prevents the white-hat botnet from disappearing, while the upper limit prevents it from filling up the network. The BDS with the strategy was modeled with agent-oriented Petri nets and was evaluated through the simulation. The result showed that the proposed strategy was able to deal with repeatedly invading malicious botnets with about half the scale of the conventional white-hat botnet.

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.

Password-based authentication is the most common authentication method for either online or offline system. Password composition policies become too burdensome and put the user in a state of struggle to remember their password. Thus, most of the user save their password on the browser or even list it down in their personal gadgets. Therefore, a multi agent-based password management application have been developed to helps user in keeping their password safely. However, multi-agent system facing security issues such as man in the middle attack, data modification and eavesdropping. This paper proposed a security protocol for multi agent-based architecture in order to reduce potential threats. The security protocol focuess on the authentication of mobile agents, data transmission and the data local protection. The communication channels are secured using cryptography techniques.

It is important to provide strong security for IoT devices with limited security related resources. We introduce a new dynamic security agent management framework, which dynamically chooses the best security agent to support security functions depending on the applications' security requirements of IoT devices in the system. This framework is designed to overcome the challenges including high computation costs, multiple security protocol compatibility, and efficient energy management in IoT system.