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StyleCloak: Anonymous Source Coding for Textual Attribute Obfuscation with Semantic Fidelity

Yin, J; Wei, Z; Masouros, C; Liu, E; Ji, W; Ji, Y; (2025) StyleCloak: Anonymous Source Coding for Textual Attribute Obfuscation with Semantic Fidelity. In: Proceedings of the IEEE/CIC International Conference on Communications in China (ICCC Workshops) 2025. (pp. pp. 1-6). IEEE: Shanghai, China. Green open access

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Abstract

With the explosion of ubiquitous user information, privacy preservation has emerged as a critical challenge in next-generation real time communications, spurring research of anonymous communications. Existing anonymity designs primarily focus on masking user attributes hidden in transmitted signals, yet user characteristics embedded in data sources can still be exploited by intelligent adversaries empowered by large language models (LLMs). In this pioneers work, we investigate anonymous source coding design, specifically for textual data sources. A novel anonymous framework, namely StyleCloak, is proposed to obfuscate user-specified attributes through minimal yet effective alterations to lexical features. By proposing a novel Pareto Beam search and iteration, StyleCloak achieves high obfuscation efficiency while well preserving semantic meaning. In addition, StyleCloak's plug-and-play architecture enables flexible adaptation to various user attribute anonymization tasks. It can be integrated as a preprocessing module for diverse downstream applications, such as real time semantic communication, without modifying existing system architectures.

Type: Proceedings paper
Title: StyleCloak: Anonymous Source Coding for Textual Attribute Obfuscation with Semantic Fidelity
Event: 2025 IEEE/CIC International Conference on Communications in China (ICCC Workshops)
Location: Shanghai, China
Dates: 10th-13th August 2025
ISBN-13: 978-1-6654-7801-4
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICCCWorkshops67136.2025.11148197
Publisher version: https://doi.org/10.1109/icccworkshops67136.2025.11...
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Pareto Beam Search and Iteration, LLM, Privacy
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10219241
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