Visible to the public A Botnet Detection Approach Based on the Clonal Selection Algorithm

TitleA Botnet Detection Approach Based on the Clonal Selection Algorithm
Publication TypeConference Paper
Year of Publication2018
AuthorsLysenko, S., Bobrovnikova, K., Savenko, O.
Conference Name2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT)
ISBN Number978-1-5386-5903-8
Keywordsartificial immune system, artificial immune systems, benign network traffic, BotGRABBER system, Botnet, Botnet detection, botnets, Classification algorithms, clonal selection algorithm, compositionality, Computer crime, computer network security, computer systems, corporate area networks, DNS botnet detection, HTTP botnet detection, hypermedia, Immune system, invasive software, IP networks, IRC botnet detection, Malware, Metrics, P2P botnet detection, Peer-to-peer computing, pubcrawl, resilience, Resiliency, telecommunication traffic, Training, transport protocols

The paper presents a new technique for the botnets' detection in the corporate area networks. It is based on the usage of the algorithms of the artificial immune systems. Proposed approach is able to distinguish benign network traffic from malicious one using the clonal selection algorithm taking into account the features of the botnet's presence in the network. An approach present the main improvements of the BotGRABBER system. It is able to detect the IRC, HTTP, DNS and P2P botnets.

Citation Keylysenko_botnet_2018