مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

937
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

248
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

BEE ID: INTRUSION DETECTION IN AODV-BASED MANETS USING ARTIFICIAL BEE COLONY AND NEGATIVE SELECTION ALGORITHMS

Pages

  25-39

Abstract

MOBILE AD HOC NETWORKs (MANETs) are multi-hop wireless networks of mobile nodes constructed dynamically without the use of any fixed network infrastructure. Due to inherent characteristics of these networks, malicious nodes can easily disrupt the routing process. A traditional approach to detect such malicious network activities is to build a pro le of the normal network traffic, and then identify an activity as suspicious if it deviates from this profile.As the topology of a MANET constantly changes over time, the simple use of a static pro le is not efficient. In this paper, we present a dynamic hybrid approach based on the ARTIFICIAL BEE COLONY (ABC) and NEGATIVE SELECTION (NS) algorithms, called BeeID, for INTRUSION DETECTION in AODV-based MANETs.The approach consists of three phases: training, detection, and updating. In the training phase, a niching ARTIFICIAL BEE COLONY algorithm, called NicheNABC, runs a NEGATIVE SELECTION algorithm multiple times to generate a set of mature negative detectors to cover the nonself space. In the detection phase, mature negative detectors are used to discriminate between normal and malicious network activities. In the updating phase, the set of mature negative detectors is updated by one of two methods of partial updating or total updating. We use the MONTE CARLO INTEGRATION to estimate the amount of the nonself space covered by negative detectors and to determine when the total updating should be done. We demonstrate the effectiveness of BeeID for detecting several types of ROUTING ATTACKs on AODV-based MANETs simulated using the NS2 simulator. The experimental results show that BeeID can achieve a better tradeoff between detection rate and false-alarm rate as compared to other dynamic approaches previously reported in the literature.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    BARANI, FATEMEH, & ABADI, MAHDI. (2012). BEE ID: INTRUSION DETECTION IN AODV-BASED MANETS USING ARTIFICIAL BEE COLONY AND NEGATIVE SELECTION ALGORITHMS. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, 4(1), 25-39. SID. https://sid.ir/paper/241819/en

    Vancouver: Copy

    BARANI FATEMEH, ABADI MAHDI. BEE ID: INTRUSION DETECTION IN AODV-BASED MANETS USING ARTIFICIAL BEE COLONY AND NEGATIVE SELECTION ALGORITHMS. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY[Internet]. 2012;4(1):25-39. Available from: https://sid.ir/paper/241819/en

    IEEE: Copy

    FATEMEH BARANI, and MAHDI ABADI, “BEE ID: INTRUSION DETECTION IN AODV-BASED MANETS USING ARTIFICIAL BEE COLONY AND NEGATIVE SELECTION ALGORITHMS,” THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, vol. 4, no. 1, pp. 25–39, 2012, [Online]. Available: https://sid.ir/paper/241819/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button