User profiling in intrusion detection: A review. (September 2016)

• Record Type: Journal Article
• Authors: Peng, Jian; Choo, Kim-Kwang Raymond; Ashman, Helen
• Is Part Of: Journal of network and computer applications. Volume 72(2016)
• Page Start: 14
• Page End: 27
• Publication Date: 2016-09
• Subjects: Behavioural biometrics -- Intrusion detection and prevention systems -- Psychometrics -- User behaviour -- User profiling; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2016.06.012
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Intrusion detection systems are important for detecting and reacting to the presence of unauthorised users of a network or system. They observe the actions of the system and its users and make decisions about the legitimacy of the activity and users. Much work on intrusion detection has focused on analysing the actions triggered by users, determining that atypical or disallowed actions may represent unauthorised use. It is also feasible to observe the users' own behaviour to see if they are acting in their'usual' way, reporting on any sufficiently-aberrant behaviour. Doing this requires a user profile, a feature found more often in marketing and education, but increasingly in security contexts. In this paper, we survey literature on intrusion detection and prevention systems from the viewpoint of exploiting the behaviour of the user in the context of their user profile to confirm or deny the legitimacy of their presence on the system (i.e. review of intrusion detection and prevention systems aimed at user profiling). User behaviour can be measured with both behavioural biometrics, such as keystroke speeds or mouse use, but also psychometrics which measure higher-order cognitive functions such as language and preferences. Graphical abstract: Highlights: User profiling in intrusion detection. Robustness of behavioural characteristics. How to keep user profile secret. Falsify input data to fool the intrusion detection system. Behavioural profiling in intrusion detection.