NDLI: Detection on application layer DDoS using random walk model

Content Provider	IEEE Xplore Digital Library
Author	Chuan Xu Guofeng Zhao Gaogang Xie Shui Yu
Copyright Year	2014
Description	Author affiliation: Sch. of Inf. Technol., Deakin Univ., Burwood, VIC, Australia (Shui Yu) \|\| Sch. of SCIE, Chongqing Univ. of Posts & Telecommun., Chongqing, China (Chuan Xu; Guofeng Zhao) \|\| Inst. of Comput. Technol., Beijing, China (Gaogang Xie)
Abstract	Application Layer Distributed Denial of Service (ALDDoS) attacks have been increasing rapidly with the growth of Botnets and Ubiquitous computing. Differentiate to the former DDoS attacks, ALDDoS attacks cannot be efficiently detected, as attackers always adopt legitimate requests with real IP address, and the traffic has high similarity to legitimate traffic. In spite of that, we think, the attackers' browsing behavior will have great disparity from that of the legitimate users'. In this paper, we put forward a novel user behavior-based method to detect the application layer asymmetric DDoS attack. We introduce an extended random walk model to describe user browsing behavior and establish the legitimate pattern of browsing sequences. For each incoming browser, we observe his page request sequence and predict subsequent page request sequence based on random walk model. The similarity between the predicted and the observed page request sequence is used as a criterion to measure the legality of the user, and then attacker would be detected based on it. Evaluation results based on real collected data set has demonstrated that our method is very effective in detecting asymmetric ALDDoS attacks.
Starting Page	707
Ending Page	712
File Size	301850
Page Count	6
File Format	PDF
ISBN	9781479920037
DOI	10.1109/ICC.2014.6883402
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer crime Vectors Probability distribution Predictive models Educational institutions Computational modeling Information systems similarity Asymmetric application layer DDoS attack anomaly detection random walk model
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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