Networking and Communication Engineering

M. Manikandaprabu ¹, R. Gnanakumaran ¹, R. Gopinath ¹

Affiliations
1 Department of Computer Science, IN

Abstract

Peer-To-Peer (P2P) network users expect to be able to search objects by semantic attributes based on their preferences for multimedia content. Partial match search has become an essential service in P2P systems. To realize an interest-based small-world CommunityNet, we also investigate the following practical design issues: 1) similarity estimation: we define a quantifiable similarity measure that enables clustering of similar peers in CommunityNet; 2)
distributed small-world overlay adaptation: peers maintain a smallworld overlay under network dynamics; and 3) query strategy under the small-world overlay: we analyze appropriate settings for the Time-to-Live (TTL) value, for TTL-limited flooding, that provides a satisfactory success ratio and avoids redundant message overhead. We use simulations and a real database called AudioScrobbler [1], which tracks users’ listening habits, to evaluate the performance of
CommunityNet. The results show that CommunityNet assists peers in locating content at peers with similar interests through short path lengths, and hence, achieves a higher success ratio (than nonsmallworld interest-based overlays and noninterest-based small-world overlays) while reducing message overhead significantly.

Keywords

Unstructured Peer-to-Peer Networks, Content Search and Retrieval, Overlay Construction, Small-World Theory.

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R. Gopinath ¹, J. Balakumar ¹, R. Gnanakumaran ², M. Manikandaprabu ³

Affiliations
1 Department of Computer Science, A.R.J College of Engineering & Technology, IN
2 Department of PG Computer Science, P.R. Engineering College, IN
3 Department of Computer Science, Prist University, IN

Abstract

Mixes have been used in many anonymous communication systems and are supposed to provide countermeasures to defeat traffic analysis attacks. In this project, we focus on a particular class of traffic analysis attacks, flow correlation attacks, by which an adversary attempts to analyze the network traffic and correlate the traffic of a flow over an input link with that over an output link. Two classes of correlation methods are considered, namely time-domain methods and frequency-domain methods. Based on our threat model and known strategies in existing mix networks, we perform extensive experiments to analyze the performance of mixes. We find that all but a few batching strategies fail against flow-correlation attacks, allowing the adversary to either identify ingress or egress points of a flow or to reconstruct the path used by the flow. Counter intuitively, some batching strategies are actually detrimental against attacks. The empirical results provided in this project give an indication to designers of Mix networks about appropriate configurations and mechanisms to be used to counter flow-correlation attacks.

Keywords

Privacy, Mixes, Anonymity, Anonymous Communication, Flow-Correlation Attack.

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