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Intrusion Detection in Mobile Adhoc Networks

Kumar, Kavitha

Abstract Details

2009, Master of Science in Engineering, University of Toledo, Electrical Engineering.

Mobile ad hoc networks (MANETs) are autonomous, infrastructure-less networks in which mobile nodes organize themselves in a network without the help of any predefined infrastructure. Securing MANETs is an important part of deploying and utilizing them, since they are often used in critical applications where data and communications integrity in important. Existing solutions for wireless networks can be used to obtain a certain level of such security. However, these solutions may not always be sufficient for MANETs, since their characteristics create vulnerabilities that cannot be addressed by these solutions. To obtain an acceptable level of security in such a context, traditional security solutions should be coupled with an intrusion detection mechanism.

We propose using a quantitative method to detect intrusion in MANETS with mobile nodes. Our method is a behavioral anomaly based system, which makes it dynamic, scalable, configurable and robust. We verify our method using simulations where mobile nodes follow linear movement patterns. The simulations are run with mobile nodes and employing Ad-hoc on-demand Distance Vector (AODV) routing. It is observed that the malicious node detection rate is very good, and the false positive detection rate is low.

Mansoor Alam, Dr (Committee Chair)
Daniel Solarek (Committee Member)
Henry Ledgard, Dr (Committee Member)
96 p.

Recommended Citations

Citations

  • Kumar, K. (2009). Intrusion Detection in Mobile Adhoc Networks [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1260232844

    APA Style (7th edition)

  • Kumar, Kavitha. Intrusion Detection in Mobile Adhoc Networks. 2009. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1260232844.

    MLA Style (8th edition)

  • Kumar, Kavitha. "Intrusion Detection in Mobile Adhoc Networks." Master's thesis, University of Toledo, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1260232844

    Chicago Manual of Style (17th edition)