Fuzzy-Based Intrusion Detection Systems

Abstract

Intrusion detection is a field of computer security that deals with detecting unauthorized network activities. An intrusion detection system is needed to identify all forms of malicious network traffic and computer activity that a traditional firewall cannot detect. Artificial Intelligence is an area of computing that explores how to create knowledge-based software that can successfully do tasks that humans can now do better. Expert systems, fuzzy logic, and neural networks are among the most recent developments in the field of artificial intelligence. Network Intrusion Detection Systems have been created and extensively researched in order to relieve the problem and detect malicious activity as early as possible. The fact that there are often no clear borders between normal and abnormal network traffic, that there is noisy or contains incorrect data, and that the analyzed traffic might represent both attack and normal communication, is a typical problem in this area. When compared with other techniques, fuzzy logic-based solutions may be beneficial because of their capacity to establish precise membership levels in multiple classes and perform various operations with outcomes that ensure reduced false positive and false negative categorization.