Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5022
Title: False alarm minimization techniques in signature-based intrusion detection systems: A survey
Authors: Hubballi, Neminath
Keywords: Alarm systems;Computer crime;Correlation methods;Intrusion detection;False alarms;Intrusion Detection Systems;Minimization techniques;Network based intrusion detection systems;Security information and event management (SIEM);Security violations;Signature-based network intrusion detection systems;System administrators;Errors
Issue Date: 2014
Publisher: Elsevier
Citation: Hubballi, N., & Suryanarayanan, V. (2014). False alarm minimization techniques in signature-based intrusion detection systems: A survey. Computer Communications, 49, 1-17. doi:10.1016/j.comcom.2014.04.012
Abstract: A network based Intrusion Detection System (IDS) gathers and analyzes network packets and report possible low level security violations to a system administrator. In a large network setup, these low level and partial reports become unmanageable to the administrator resulting in some unattended events. Further it is known that state of the art IDS generate many false alarms. There are techniques proposed in IDS literature to minimize false alarms, many of which are widely used in practice in commercial Security Information and Event Management (SIEM) tools. In this paper, we review existing false alarm minimization techniques in signature-based Network Intrusion Detection System (NIDS). We give a taxonomy of false alarm minimization techniques in signature-based IDS and present the pros and cons of each class. We also study few of the prominent commercial SIEM tools which have implemented these techniques along with their performance. Finally, we conclude with some directions to the future research. © 2014 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.comcom.2014.04.012
https://dspace.iiti.ac.in/handle/123456789/5022
ISSN: 0140-3664
Type of Material: Review
Appears in Collections:Department of Computer Science and Engineering

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