ConnectionScore: a statistical technique to resist application-layer DDoS attacks View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-06

AUTHORS

Hakem Beitollahi, Geert Deconinck

ABSTRACT

In an application-layer distributed denial of service (DDoS) attack, zombie machines send a large number of legitimate requests to the victim server. Since these requests have legitimate formats and are sent through normal TCP connections, intrusion detection systems cannot detect them. In these attacks, an adversary does not saturate the bandwidth of the victim server through inbound traffic, but through outbound traffic. The next aim of the adversary is to consume and exhaust computational resources (e.g., CPU cycles), memory resources, TCP/IP stack, resources of input/output devices, etc. This paper proposes a novel scheme which is called ConnectionScore to resist such DDoS attacks. During the attack time, any connection is scored based on history and statistical analysis which has been done during the normal condition. The bottleneck resources are retaken from those connections which take lower scores. Our analysis shows that connections established by the adversary give low scores. In fact, the ConnectionScore technique can estimate legitimacy of connections with high probability. The rate of suspicious connections being dropped is adjusted based on the current level of overload of the server and a threshold-level of free resources. To evaluate the performance of the scheme, we perform experiments in the Emulab environment using real traceroute data of the ClarkNet WWW server (http://ita.ee.lbl.gov/html/contrib/ClarkNet-HTTP.html). More... »

PAGES

425-442

References to SciGraph publications

  • 2006. Enhanced CAPTCHAs: Using Animation to Tell Humans and Computers Apart in COMMUNICATIONS AND MULTIMEDIA SECURITY
  • 2013-04. Preserving quality of service for normal users against DDoS attacks by using Double Check Priority Queues in JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12652-013-0196-5

    DOI

    http://dx.doi.org/10.1007/s12652-013-0196-5

    DIMENSIONS

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