Towards effective and robust list-based packet filter for signature-based network intrusion detection : an engineering approach

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

2 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)204-215
Journal / PublicationHKIE Transactions Hong Kong Institution of Engineers
Volume24
Issue number4
Early online date26 Dec 2017
Publication statusPublished - 2017

Abstract

Network intrusion detection systems (NIDSs) which aim to identify various attacks, have become an essential part of current security infrastructure. In particular, signature-based NIDSs are being widely implemented in industry due to their low rate of false alarms. However, the signature matching process is a big challenge for these systems, in which the cost is at least linear to the size of an input string. As a result, overhead packets will be a major issue for practical usage, where the incoming packets exceed the maximum capability of an intrusion detection system (IDS). To mitigate this problem, packet filtration is a promising solution to reduce unwanted traffic. Motivated by this, in this work, a list-based packet filter was designed and an engineering method of combining both blacklist and whitelist techniques was introduced. To further secure such filters against IP spoofing attacks, a lightweight but efficient IP verification mechanism was developed. In the evaluation, a list-based packet filter was deployed in both simulated and real network environments under honest and dishonest scenarios. Experimental results demonstrate that the developed list-based packet filter is effective in traffic filtration as well as workload reduction, and is robust against IP spoofing attacks.

Research Area(s)

  • Intrusion detection system, IP verification, list generation, network packet filter, network security and performance

Citation Format(s)

Towards effective and robust list-based packet filter for signature-based network intrusion detection : an engineering approach. / Meng, Weizhi; Li, Wenjuan; Kwok, Lam For.

In: HKIE Transactions Hong Kong Institution of Engineers, Vol. 24, No. 4, 2017, p. 204-215.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review