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Conference Paper: Anonymous communication with network coding against traffic analysis attack
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TitleAnonymous communication with network coding against traffic analysis attack
 
AuthorsWang, J3 4
Wang, J3
Wu, C1
Lu, K2
Gu, N4
 
KeywordsAlgorithm complexity
Anonymous communication
Effective algorithms
Influential factors
ITS efficiencies
 
Issue Date2011
 
PublisherI E E E, Computer Society. The Journal's web site is located at http://www.ieee-infocom.org/
 
CitationThe IEEE INFOCOM 2011, Shanghai, China, 10-15 April 2011. In Conference Proceedings, 2011, p. 1008-1016 [How to Cite?]
DOI: http://dx.doi.org/10.1109/INFCOM.2011.5934873
 
AbstractFlow untraceability is one critical requirement for anonymous communication with network coding, which prevents malicious attackers with wiretapping and traffic analysis abilities from relating the senders to the receivers, using linear dependency of the received packets. There have recently been proposals advocating encryptions on the Global Encoding Vectors (GEV) of network coding to thwart such attacks [1], [2]. Nevertheless, there has been no exploration of the capability of networking coding itself, to constitute more efficient and effective algorithms which guarantee anonymity. In this paper, we design a novel, simple, and effective linear network coding mechanism (ALNCode) to achieve flow untraceability in a communication network with multiple unicast flows. With solid theoretical analysis, we first show that linear network coding (LNC) can be applied to thwart traffic analysis attacks without the need of encrypting GEVs. Our key idea is to mix multiple flows at their intersection nodes by generating downstream GEVs from the common basis of upstream GEVs belonging to multiple flows, in order to hide the correlation of upstream and downstream GEVs in each flow. We then design a deterministic LNC scheme to implement our idea, by which the downstream GEVs produced are guaranteed to obfuscate their correlation with the corresponding upstream GEVs. We also give extensive theoretical analysis on the intersection probability of GEV bases and the influential factors to the effectiveness of our scheme, as well as the algorithm complexity to support its efficiency. © 2011 IEEE.
 
ISSN0743-166X
2012 SCImago Journal Rankings: 1.703
 
DOIhttp://dx.doi.org/10.1109/INFCOM.2011.5934873
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorWang, J
 
dc.contributor.authorWang, J
 
dc.contributor.authorWu, C
 
dc.contributor.authorLu, K
 
dc.contributor.authorGu, N
 
dc.date.accessioned2011-07-27T01:46:59Z
 
dc.date.available2011-07-27T01:46:59Z
 
dc.date.issued2011
 
dc.description.abstractFlow untraceability is one critical requirement for anonymous communication with network coding, which prevents malicious attackers with wiretapping and traffic analysis abilities from relating the senders to the receivers, using linear dependency of the received packets. There have recently been proposals advocating encryptions on the Global Encoding Vectors (GEV) of network coding to thwart such attacks [1], [2]. Nevertheless, there has been no exploration of the capability of networking coding itself, to constitute more efficient and effective algorithms which guarantee anonymity. In this paper, we design a novel, simple, and effective linear network coding mechanism (ALNCode) to achieve flow untraceability in a communication network with multiple unicast flows. With solid theoretical analysis, we first show that linear network coding (LNC) can be applied to thwart traffic analysis attacks without the need of encrypting GEVs. Our key idea is to mix multiple flows at their intersection nodes by generating downstream GEVs from the common basis of upstream GEVs belonging to multiple flows, in order to hide the correlation of upstream and downstream GEVs in each flow. We then design a deterministic LNC scheme to implement our idea, by which the downstream GEVs produced are guaranteed to obfuscate their correlation with the corresponding upstream GEVs. We also give extensive theoretical analysis on the intersection probability of GEV bases and the influential factors to the effectiveness of our scheme, as well as the algorithm complexity to support its efficiency. © 2011 IEEE.
 
dc.description.naturepublished_or_final_version
 
dc.description.otherThe IEEE INFOCOM 2011, Shanghai, China, 10-15 April 2011. In Conference Proceedings, 2011, p. 1008-1016
 
dc.identifier.citationThe IEEE INFOCOM 2011, Shanghai, China, 10-15 April 2011. In Conference Proceedings, 2011, p. 1008-1016 [How to Cite?]
DOI: http://dx.doi.org/10.1109/INFCOM.2011.5934873
 
dc.identifier.doihttp://dx.doi.org/10.1109/INFCOM.2011.5934873
 
dc.identifier.epage1016
 
dc.identifier.hkuros187767
 
dc.identifier.issn0743-166X
2012 SCImago Journal Rankings: 1.703
 
dc.identifier.openurl
 
dc.identifier.scopuseid_2-s2.0-79960862937
 
dc.identifier.spage1008
 
dc.identifier.urihttp://hdl.handle.net/10722/135704
 
dc.languageeng
 
dc.publisherI E E E, Computer Society. The Journal's web site is located at http://www.ieee-infocom.org/
 
dc.publisher.placeUnited States
 
dc.relation.ispartofProceedings of the IEEE INFOCOM
 
dc.relation.referencesReferences in Scopus
 
dc.rightsIEEE Infocom Proceedings. Copyright © IEEE, Computer Society.
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
 
dc.subjectAlgorithm complexity
 
dc.subjectAnonymous communication
 
dc.subjectEffective algorithms
 
dc.subjectInfluential factors
 
dc.subjectITS efficiencies
 
dc.titleAnonymous communication with network coding against traffic analysis attack
 
dc.typeConference_Paper
 
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<subject>Algorithm complexity</subject>
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Author Affiliations
  1. The University of Hong Kong
  2. University of Puerto Rico
  3. City University of Hong Kong
  4. Hong Kong University of Science and Technology