Xuan Nam Nguyen and Dai Tho Nguyen and Hai Long Vu (2016) POCAD: a Novel Payload-based One-Class Classifier for Anomaly Detection. In: 2016 3rd National Foundation for Science and Technology Development (NAFOSTED) Conference on Information and Computer Science (NICS), September 14-16, 2016, Danang City, Vietnam.
- Published Version
Official URL: http://www.nafosted-nics.org
In this paper, we propose a novel Payload-based One-class Classifier for Anomaly Detection called POCAD, which combines a generalized 2v-gram feature extractor and a one-class SVM classifier to effectively detect network intrusion attacks. We extensively evaluate POCAD with real-world datasets of HTTP-based attacks. Our experiment results show that POCAD can quickly detect malicious payload and achieves a high detection rate as well as a low false positive rate. The experiment results also show that POCAD outperforms state of the art payload-based detection schemes such as McPAD  and PAYL .
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Information Technology (IT)|
|Divisions:||Faculty of Information Technology (FIT)|
|Deposited By:||Dr. Dai Tho Nguyen|
|Deposited On:||29 Dec 2016 08:24|
|Last Modified:||12 Jan 2017 16:15|
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