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Private Variable-Length Coding with Zero Leakage
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0001-9296-4939
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-0036-9049
Imperial College London, Dept. of Electrical and Electronic Engineering, Imperial College London, Dept. of Electrical and Electronic Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-7926-5081
2023 (English)In: WIFS 2023 - IEEE Workshop on Information Forensics and Security, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

A private compression design problem is studied, where an encoder observes useful data Y, wishes to compress it using variable length code and communicates it through an unsecured channel. Since Y is correlated with private attribute X, the encoder uses a private compression mechanism to design encoded message C and sends it over the channel. An adversary is assumed to have access to the output of the encoder, i.e., C, and tries to estimate X. Furthermore, it is assumed that both encoder and decoder have access to a shared secret key W. The design goal is to encode message C with minimum possible average length that satisfies a perfect privacy constraint. To do so we first consider two different privacy mechanism design problems and find upper bounds on the entropy of the optimizers by solving a linear program. We use the obtained optimizers to design C. In two cases we strengthen the existing bounds: 1. |X| |Y| 2. The realization of (X,Y) follows a specific joint distribution. In particular, considering the second case we use two-part construction coding to achieve the upper bounds. Furthermore, in a numerical example we study the obtained bounds and show that they can improve the existing results.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023.
National Category
Communication Systems Computer Sciences Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-343176DOI: 10.1109/WIFS58808.2023.10374696ISI: 001156967300009Scopus ID: 2-s2.0-85183466137OAI: oai:DiVA.org:kth-343176DiVA, id: diva2:1836078
Conference
2023 IEEE International Workshop on Information Forensics and Security, WIFS 2023, Nurnberg, Germany, Dec 4 2023 - Dec 7 2023
Note

Part of proceedings ISBN 9798350324914

QC 20240212

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-03-12Bibliographically approved

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Zamani, AmirrezaOechtering, Tobias J.Skoglund, Mikael

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