A Botnet Detection Approach Based on the Clonal Selection Algorithm

Title	A Botnet Detection Approach Based on the Clonal Selection Algorithm
Publication Type	Conference Paper
Year of Publication	2018
Authors	Lysenko, S., Bobrovnikova, K., Savenko, O.
Conference Name	2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT)
ISBN Number	978-1-5386-5903-8
Keywords	artificial 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
Abstract	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.
URL	https://ieeexplore.ieee.org/document/8409171
DOI	10.1109/DESSERT.2018.8409171
Citation Key	lysenko_botnet_2018