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Evolving a Trust Model for Peer-to-Peer Networks Using Genetic Programming

  • Ugur Eray TahtaEmail author
  • Ahmet Burak Can
  • Sevil Sen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8602)

Abstract

Peer-to-peer (P2P) systems have attracted significant interest in recent years. In P2P networks, each peer act as both a server or a client. This characteristic makes peers vulnerable to a wide variety of attacks. Having robust trust management is very critical for such open environments to exclude unreliable peers from the system. This paper investigates the use of genetic programming to asses the trustworthiness of peers without a central authority. A trust management model is proposed in which each peer ranks other peers according to local trust values calculated automatically based on the past interactions and recommendations. The experimental results have shown that the model could successfully identify malicious peers without using a central authority or global trust values and, improve the system performance.

Keywords

Genetic Programming Trust Model Intrusion Detection Success Ratio Trust Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ugur Eray Tahta
    • 1
    • 2
    Email author
  • Ahmet Burak Can
    • 1
  • Sevil Sen
    • 1
  1. 1.Department of Computer EngineeringHacettepe UniversityAnkaraTurkey
  2. 2.ASELSANAnkaraTurkey

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