MapReduce analysis for cloud-archived data
Balaji Palanisamy, Aameek Singh, et al.
CCGrid 2014
(A short version of this paper appears in IEEE INFOCOM 2009: http://www.research.ibm.com/people/i/iyengar/INFOCOM2009-kanon.pdf.) Peer-to-peer VoIP (voice over IP) networks, exemplified by Skype [5], are becoming increasingly popular due to their significant cost advantage and richer call forwarding features than traditional public switched telephone networks. One of the most important features of a VoIP network is privacy (for VoIP clients). Unfortunately, most peer-to-peer VoIP networks neither provide personalization nor guarantee a quantifiable privacy level. In this paper, we propose novel flow analysis attacks that demonstrate the vulnerabilities of peer-to-peer VoIP networks to privacy attacks. We then address two important challenges in designing privacy-aware VoIP networks: Can we provide personalized privacy guarantees for VoIP clients that allow them to select privacy requirements on a per-call basis? How to design VoIP protocols to support customizable privacy guarantee? This paper proposes practical solutions to address these challenges using a quantifiable k-anonymity metric and a privacy-aware VoIP route setup and route maintenance protocols. We present detailed experimental evaluation that demonstrates the performance and scalability of our protocol, while meeting customizable privacy guarantees. © 2011 IEEE.
Balaji Palanisamy, Aameek Singh, et al.
CCGrid 2014
Mudhakar Srivatsa, Arun Iyengar, et al.
SRDS 2006
Qi Zhang, Ling Liu, et al.
ICWS 2016
Aameek Singh, Ling Liu, et al.
International Journal of Information and Computer Security