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Private Variable-Length Coding with Non-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
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 data 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. In this work, we generalize the perfect privacy (secrecy) assumption and consider a non-zero leakage between the private data X and encoded message C. The design goal is to encode message C with minimum possible average length that satisfies non-perfect privacy constraints. We find upper and lower bounds on the average length of the encoded message using different privacy metrics and study them in special cases. For the achievability we use two-part construction coding and extended versions of Functional Representation Lemma. Lastly, in an example we show that the bounds can be asymptotically tight.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023.
National Category
Communication Systems Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-343179DOI: 10.1109/WIFS58808.2023.10374604ISI: 001156967300005Scopus ID: 2-s2.0-85183470148OAI: oai:DiVA.org:kth-343179DiVA, id: diva2:1836081
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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