Intrusion Detection via Artificial Immune System: a Performance-based Approach
作者： Andrea Visconti , Nicoló Fusi , Hooman Tahayori
DOI: 10.1007/978-0-387-09655-1_12
关键词: Computer network 、 Network intrusion detection 、 Host (network) 、 Set (abstract data type) 、 Denial-of-service attack 、 Buffer overflow 、 Intrusion detection system 、 Computer science 、 State (computer science) 、 Artificial immune system
摘要: In this paper, we discuss the design and engineering of a biologically-inspired, host-based intrusion detection system to protect computer networks. To end, have implemented an Artificial Immune System (AIS) that mimics behavior biological adaptive immune system. The proposed AIS, consists number running artificial white blood cells, which search, recognize, store deny anomalous requests on individual hosts. model monitors through analysing set parameters provide general information its state — ill or not. When some are discovered values, then takes proper action. prove effectiveness suggested model, exhaustive test AIS is conducted, using server Apache, Mysql OpenSSH, results reported. Four types attacks were tested: remote buffer overflow, Distributed Denial Service (DDOS), port scanning, dictionary-attack. proved our definition self/non-self components quite effective in protecting systems.
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