Dynamically Real-time Anomaly Detection Algorithm with Immune Negative Selection

Peng, Lingxi; Chen, Wenbin; Xie, Dongqing; Gao, Ying; Liang, Chunlin

doi:10.12785/amis/070338

Cited by 4 publications

(1 citation statement)

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“…Their experimental results show that it has the features of real-time processing and self-adapting. Peng et al proposed a Dynamic Anomaly Detection Algorithm with Immune NS (DADAI) [ 22 ], combining the antibody's clone theory and vaccination. It established dynamic evolvement formulations of detection profiles which can dynamically synchronize detection profiles with the real network environment.…”

Section: Evolution Modementioning

confidence: 99%

A Survey of Artificial Immune System Based Intrusion Detection

Yang

Wang

et al. 2014

The Scientific World Journal

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In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

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Section: Evolution Modementioning

confidence: 99%