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Malware Detection and Prevention System Based on Multi-Stage Rules

Author

Listed:
  • Ammar Alazab

    (School of Information Technology, Deakin University, Burwood, VIC, Australia)

  • Michael Hobbs

    (School of Information Technology, Deakin University, Burwood, VIC, Australia)

  • Jemal Abawajy

    (School of Information Technology, Deakin University, Burwood, VIC, Australia)

  • Ansam Khraisat

    (Ballarat University, Mt Helen, VIC, Australia)

Abstract

The continuously rising Internet attacks pose severe challenges to develop an effective Intrusion Detection System (IDS) to detect known and unknown malicious attack. In order to address the problem of detecting known, unknown attacks and identify an attack grouped, the authors provide a new multi stage rules for detecting anomalies in multi-stage rules. The authors used the RIPPER for rule generation, which is capable to create rule sets more quickly and can determine the attack types with smaller numbers of rules. These rules would be efficient to apply for Signature Intrusion Detection System (SIDS) and Anomaly Intrusion Detection System (AIDS).

Suggested Citation

  • Ammar Alazab & Michael Hobbs & Jemal Abawajy & Ansam Khraisat, 2013. "Malware Detection and Prevention System Based on Multi-Stage Rules," International Journal of Information Security and Privacy (IJISP), IGI Global, vol. 7(2), pages 29-43, April.
    • Handle: RePEc:igg:jisp00:v:7:y:2013:i:2:p:29-43
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