Formal analysis of intrusion detection systems for high speed networks

  • Authors:
  • Mohsen Rouached;Hassen Sallay;Ouissem Ben Fredj;Adel Ammar;Khaled Al-Shalfan;Majdi Ben

  • Affiliations:
  • Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamad Ibn Saud University, Saudi Arabia;Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamad Ibn Saud University, Saudi Arabia;Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamad Ibn Saud University, Saudi Arabia;Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamad Ibn Saud University, Saudi Arabia;Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamad Ibn Saud University, Saudi Arabia;Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamad Ibn Saud University, Saudi Arabia

  • Venue:
  • ISPACT'10 Proceedings of the 9th WSEAS international conference on Advances in e-activities, information security and privacy
  • Year:
  • 2010

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Abstract

Network Intrusion Detection System (NIDS) is an important and practical tool for network security. To guarantee a precise detection, the NIDS must detect packets at a wire speed. However, with the recent trend of high-speed networks, the capability of a single NIDS cannot meet the speed's demand, resulting in rising of false negatives. To address this problem, Specification-based techniques have been proposed as a promising alternative that combine the strengths of misuse and anomaly detection. In this paper, we present an event calculus (EC) based framework towards the formal analysis of NIDS. This framework checks that security requirements and assumptions are preserved at run-time by monitoring the satisfaction of EC formulas that formalize them using the detection rules. This can be done by observing the network at run-time and checking observations against specified network behavior trying to detect deviations from what is specified.