Misbehavior detection in Mobile ad hoc Networks using Artificial Immune System approach

Ansari, Shamsher Alam; Inamullah, Muhammad

doi:10.1109/ants.2011.6163683

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Ansari and Inamullah (2011) proposed an enhancement for the anomaly detection based on AIS and showed how their model improves AIS performance in applications such as anomaly detection, ensuring security, detecting errors and performing data mining in mobile ad hoc networks [61]. Fang et al (2012) proposed an AIS for phishing detection through memory and mature detectors.…”

Section: Zhang Et Al (2011) Proposed Sgdids -A New Hierarchical Distmentioning

confidence: 99%

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

Dilek¹,

Çakır²,

Aydin³

2015

IJAIA

128

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With the advances in information technology (IT) criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not sufficient for monitoring and protection of these infrastructures; hence, there is a need for more sophisticated cyber defense systems that need to be flexible, adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions. Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention. The purpose of this study is to present advances made so far in the field of applying AI techniques for combating cyber crimes, to demonstrate how these techniques can be an effective tool for detection and prevention of cyber attacks, as well as to give the scope for future work.

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Section: Zhang Et Al (2011) Proposed Sgdids -A New Hierarchical Distmentioning

confidence: 99%

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

Dilek¹,

Çakır²,

Aydin³

2015

IJAIA

128

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“…Ansari et al in [66] use the concepts of clonal selection and danger signal for misbehavior detection using DSR. The protocol events of a node are mapped to HIS elements.…”

Section: ) Recovery Processmentioning

confidence: 99%

A Review of Artificial Immune System Based Security Frameworks for MANET

Jim¹,

Gregory²

2016

IJCNS

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Mobile ad hoc networks (MANETs) are collections of wireless mobile devices that form a communication network with restricted broadcast range, limited resources and without fixed infrastructure. Routing is a critical function in multi-hop MANETs. At the same time, security in MANETsespecially routing security-presents a number of new and interesting challenges. Communication is achieved by relaying data along routes that are dynamically discovered and maintained through collaboration between the nodes. Advances in the field of artificial immune systems provide an opportunity to improve MANET security and performance. Artificial immune systems mimic the functionality of the human immune system wherein there is clear distinction between self and non self and this delineation is important in a MANET where there is no centralized management. The high level of protection provided to the human body by an evolved immune system can be applied as a security feature in MANET. The current security techniques proposed for MANET have varying degrees of success due to the dynamic nature of a MANET. This paper will review different strategies for the application of artificial immune systems to MANETs.

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