An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment

Most current anti-worm systems and intrusion-detection systems use signature-based technology instead of anomaly-based technology. Signature-based technology can only detect known attacks with identified signatures. Existing anti-worm systems cannot detect unknown Internet scanning worms automatical...

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Bibliographic Details
Main Author: Rasheed, Mohammad M.
Format: Thesis
Language:English
English
Published: 2012
Subjects:
Online Access:https://etd.uum.edu.my/3353/1/MOHAMMAD_M._RASHEED.pdf
https://etd.uum.edu.my/3353/3/MOHAMMAD_M._RASHEED.pdf
https://etd.uum.edu.my/3353/
http://sierra.uum.edu.my/record=b1242446~S1
Abstract Abstract here
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author Rasheed, Mohammad M.
author_facet Rasheed, Mohammad M.
author_sort Rasheed, Mohammad M.
description Most current anti-worm systems and intrusion-detection systems use signature-based technology instead of anomaly-based technology. Signature-based technology can only detect known attacks with identified signatures. Existing anti-worm systems cannot detect unknown Internet scanning worms automatically because these systems do not depend upon worm behaviour but upon the worm’s signature. Most detection algorithms used in current detection systems target only monomorphic worm payloads and offer no defence against polymorphic worms, which changes the payload dynamically. Anomaly detection systems can detect unknown worms but usually suffer from a high false alarm rate. Detecting unknown worms is challenging, and the worm defence must be automated because worms spread quickly and can flood the Internet in a short time. This research proposes an accurate, robust and fast technique to detect and contain Internet worms (monomorphic and polymorphic). The detection technique uses specific failure connection statuses on specific protocols such as UDP, TCP, ICMP, TCP slow scanning and stealth scanning as characteristics of the worms. Whereas the containment utilizes flags and labels of the segment header and the source and destination ports to generate the traffic signature of the worms. Experiments using eight different worms (monomorphic and polymorphic) in a testbed environment were conducted to verify the performance of the proposed technique. The experiment results showed that the proposed technique could detect stealth scanning up to 30 times faster than the technique proposed by another researcher and had no false-positive alarms for all scanning detection cases. The experiments showed the proposed technique was capable of containing the worm because of the traffic signature’s uniqueness.
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spelling oai:etd.uum.edu.my:33532025-06-03T03:27:12Z https://etd.uum.edu.my/3353/ An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment Rasheed, Mohammad M. QA76 Computer software Most current anti-worm systems and intrusion-detection systems use signature-based technology instead of anomaly-based technology. Signature-based technology can only detect known attacks with identified signatures. Existing anti-worm systems cannot detect unknown Internet scanning worms automatically because these systems do not depend upon worm behaviour but upon the worm’s signature. Most detection algorithms used in current detection systems target only monomorphic worm payloads and offer no defence against polymorphic worms, which changes the payload dynamically. Anomaly detection systems can detect unknown worms but usually suffer from a high false alarm rate. Detecting unknown worms is challenging, and the worm defence must be automated because worms spread quickly and can flood the Internet in a short time. This research proposes an accurate, robust and fast technique to detect and contain Internet worms (monomorphic and polymorphic). The detection technique uses specific failure connection statuses on specific protocols such as UDP, TCP, ICMP, TCP slow scanning and stealth scanning as characteristics of the worms. Whereas the containment utilizes flags and labels of the segment header and the source and destination ports to generate the traffic signature of the worms. Experiments using eight different worms (monomorphic and polymorphic) in a testbed environment were conducted to verify the performance of the proposed technique. The experiment results showed that the proposed technique could detect stealth scanning up to 30 times faster than the technique proposed by another researcher and had no false-positive alarms for all scanning detection cases. The experiments showed the proposed technique was capable of containing the worm because of the traffic signature’s uniqueness. 2012 Thesis NonPeerReviewed text en https://etd.uum.edu.my/3353/1/MOHAMMAD_M._RASHEED.pdf text en https://etd.uum.edu.my/3353/3/MOHAMMAD_M._RASHEED.pdf Rasheed, Mohammad M. (2012) An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment. Doctoral thesis, Universiti Utara Malaysia. http://sierra.uum.edu.my/record=b1242446~S1
spellingShingle QA76 Computer software
Rasheed, Mohammad M.
An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
thesis_level PhD
title An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
title_full An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
title_fullStr An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
title_full_unstemmed An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
title_short An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
title_sort innovative signature detection system for polymorphic and monomorphic internet worms detection and containment
topic QA76 Computer software
url https://etd.uum.edu.my/3353/1/MOHAMMAD_M._RASHEED.pdf
https://etd.uum.edu.my/3353/3/MOHAMMAD_M._RASHEED.pdf
https://etd.uum.edu.my/3353/
http://sierra.uum.edu.my/record=b1242446~S1
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