TY - GEN
T1 - EARS
T2 - 2020 IEEE Conference on Communications and Network Security, CNS 2020
AU - Kilari, Vishnu Teja
AU - Yu, Ruozhou
AU - Misra, Satyajayant
AU - Xue, Guoliang
N1 - Funding Information:
Kilari and Xue ({vkilari, xue}@asu.edu) are with Arizona State University, Tempe, AZ 85287. Yu (ryu5@ncsu.edu) is with North Carolina State University, Raleigh, NC 27606. Misra (misra@cs.nmsu.edu) is with New Mexico State University, Las Cruces, NM 88003. This research was supported in part by NSF grants 1704092, 1717197, 1719342, 1345232, 1914635, and EPSCoR Cooperative Agreement OIA-1757207 and DOE SETO award ED-EE0008774. The information reported here does not reflect the position or the policy of the funding agencies.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Reputation systems, designed to remedy the lack of information quality and assess credibility of information sources, have become an indispensable component of many online systems. A typical reputation system works by tracking all information originating from a source, and the feedback to the information with its attribution to the source. The tracking of information and the feedback, though essential, could violate the privacy of users who provide the information and/or the feedback, which could both cause harm to the users' online well-being, and discourage them from participation. Anonymous reputation systems have been designed to protect user privacy by ensuring anonymity of the users. Yet, current anonymous reputation systems suffer from several limitations, including but not limited to a)lack of support for core functionalities such as feedback update, b) lack of protocol efficiency for practical deployment, and c) reliance on a fully trusted authority. This paper proposes EARS, an anonymous reputation system that ensures user anonymity while supporting all core functionalities (including feedback update) of a reputation system both efficiently and practically, and without the need of a fully trusted central authority. We present security analysis of EARS against multiple types of attacks that could potentially violate user anonymity, such as feedback duplication, bad mouthing, and ballot stuffing. We also present evaluation of the efficiency and scalability of our system based on implementations.
AB - Reputation systems, designed to remedy the lack of information quality and assess credibility of information sources, have become an indispensable component of many online systems. A typical reputation system works by tracking all information originating from a source, and the feedback to the information with its attribution to the source. The tracking of information and the feedback, though essential, could violate the privacy of users who provide the information and/or the feedback, which could both cause harm to the users' online well-being, and discourage them from participation. Anonymous reputation systems have been designed to protect user privacy by ensuring anonymity of the users. Yet, current anonymous reputation systems suffer from several limitations, including but not limited to a)lack of support for core functionalities such as feedback update, b) lack of protocol efficiency for practical deployment, and c) reliance on a fully trusted authority. This paper proposes EARS, an anonymous reputation system that ensures user anonymity while supporting all core functionalities (including feedback update) of a reputation system both efficiently and practically, and without the need of a fully trusted central authority. We present security analysis of EARS against multiple types of attacks that could potentially violate user anonymity, such as feedback duplication, bad mouthing, and ballot stuffing. We also present evaluation of the efficiency and scalability of our system based on implementations.
KW - Reputation system
KW - anonymity
KW - privacy
UR - http://www.scopus.com/inward/record.url?scp=85090118468&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090118468&partnerID=8YFLogxK
U2 - 10.1109/CNS48642.2020.9162328
DO - 10.1109/CNS48642.2020.9162328
M3 - Conference contribution
AN - SCOPUS:85090118468
T3 - 2020 IEEE Conference on Communications and Network Security, CNS 2020
BT - 2020 IEEE Conference on Communications and Network Security, CNS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 June 2020 through 1 July 2020
ER -