Sprinkling Data :Prevent Pollution Attacks Using Entropy Variation

Abstract

The Distributed Denial-of-Service (DDoS) attacks are a critical threat to the Internet. Recently there are an increasing number of DDoS attacks against online services and Web applications. However the memoryless feature of the Internet routing mechanisms makes it extremely hard to trace back to the source of these attacks. These attacks are targeting the application level. Detecting application layer DDOS attack is not an easy task. In this paper, we propose a novel trace back method for DDoS attacks that is based on entropy variations between normal and DDoS attack traffic which is fundamentally different from commonly used packet marking techniques. The idea is to detect abrupt traffic changes across multiple network domains at the earliest time. The suspicious requests are identified based onthe variation in entropy and a rate limiter is introduced to downgrade services to malicioususers. In addition to a scheduler is include to schedule the session based on the trust score of theuser and the system workload .

Authors and Affiliations

Anil Kumar Battula, S Amarnath Babu

Keywords

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  • EP ID EP27749
  • DOI -
  • Views 263
  • Downloads 2

How To Cite

Anil Kumar Battula, S Amarnath Babu (2013). Sprinkling Data :Prevent Pollution Attacks Using Entropy Variation. International Journal of Research in Computer and Communication Technology, 2(11), -. https://europub.co.uk/articles/-A-27749