NDLI: Privacy Assurance in Data-Aggregation for Multiple MAX Transactions

Content Provider	IEEE Xplore Digital Library
Author	Kim Le Ramanathan, P. Saluja, K.K.
Copyright Year	2015
Description	Author affiliation: Fac. of Educ., Sci., Technol. & Math., Univ. of Canberra, Canberra, ACT, Australia (Kim Le) \|\| Dept. of Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA (Ramanathan, P.; Saluja, K.K.)
Abstract	Mobile devices are now very popular in many applications, and there is a trend to use them in statistic surveys. The main technical issue is privacy assurance. In this paper, we propose a certification-based approach for privacy assurance in multiple transactions of a survey conducted by a third-party application (TPA), which wants to find the maximal values of private data of some member groups in a social society. In our proposal, the computation burden on an involved user to verify the privacy assurance does not increase with the number of users participating in the survey. Furthermore, similar to traditional surveys, the users only need to communicate with the TPA. These features distinguish our approach from the existing research in literature for secure multi-party computation.
Starting Page	110
Ending Page	115
File Size	228366
Page Count	6
File Format	PDF
ISSN	07303157
e-ISBN	9781467365642
DOI	10.1109/COMPSAC.2015.159
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cryptography Privacy Consumer electronics Protocols Certification Computers Data privacy Differential privacy Secure multi-party computation Third-party application Cloud computing Secure Maximum computation
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Software

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