Technical Program

Paper Detail

Paper IDP.3.3
Paper Title Sequence Obfuscation to Thwart Pattern Matching Attacks
Authors Bo Guan, Nazanin Takbiri, Dennis Goeckel, Amir Houmansadr, Hossein Pishro-Nik, University of Massachusetts Amherst, United States
Session P.3: Information Privacy I
Presentation Lecture
Track Cryptography, Security and Privacy
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract Suppose we are given a large number of sequences on a given alphabet, and an adversary is interested in identifying (de-anonymizing) a specific target sequence based on its patterns. Our goal is to thwart such an adversary by obfuscating the target sequences by applying artificial (but small) distortions to its values. A key point here is that we would like to make no assumptions about the statistical model of such sequences. This is in contrast to existing literature where assumptions (e.g., Markov chains) are made regarding such sequences to obtain privacy guarantees. We relate this problem to a set of combinatorial questions on sequence construction based on which we are able to obtain provable guarantees. This problem is relevant to important privacy applications: from fingerprinting webpages visited by users through anonymous communication systems to linking communicating parties on messaging applications to inferring activities of users of IoT devices.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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