HackerPapers

arXiv:1203.2668cs.CR

Octopus: A Secure and Anonymous DHT Lookup

Qiyan Wang, Nikita Borisov

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Distributed Hash Table (DHT) lookup is a core technique in structured peer-to-peer (P2P) networks. Its decentralized nature introduces security and privacy vulnerabilities for applications built on top of them; we thus set out to design a lookup mechanism achieving both security and anonymity, heretofore an open problem. We present Octopus, a novel DHT lookup which provides strong guarantees for both security and anonymity. Octopus uses attacker identification mechanisms to discover and remove malicious nodes, severely limiting an adversary's ability to carry out active attacks, and splits lookup queries over separate anonymous paths and introduces dummy queries to achieve high levels of anonymity. We analyze the security of Octopus by developing an event-based simulator to show that the attacker discovery mechanisms can rapidly identify malicious nodes with low error rate. We calculate the anonymity of Octopus using probabilistic modeling and show that Octopus can achieve near-optimal anonymity. We evaluate Octopus's efficiency on Planetlab with 207 nodes and show that Octopus has reasonable lookup latency and manageable communication overhead.

arXiv comments
Journal reference
DOI
Subjects
cs.CRCryptography and Security

On Hacker News

Linked by 1 identifiable commenter in 1 comment across 1 thread, from Jul 2013 to Jul 2013.

Comments linking this paper, per year.

Discussed in comments1 thread

    • Two e-mail replacements that aspire toward secure communication with little actionable metadata are Bitmessage and I2pbote (runs over i2p net). Both are very much alpha, and Bitmessage has some significant work to do on how to scale up. But both are also p2p, and both…

      jnbicheView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.