Deniable Identity-Based Matchmaking Encryption for Anonymous Messaging
Anonymous messaging system allows users to deliver messages without revealing the sending content and their identifiers, which has attracted ongoing concerns. However, to the best of our knowledge, all the existing solutions still fail to protect users’ privacy under coercion. That is, the user’s communication transcripts might be tracked and cached, and later coerced to reveal the underlying messages associated with the ciphertexts due to law enforcement reasons or for evil purposes. In addition, anonymity alone is not enough for some practical scenarios. For instance, a journalist just wants to communicate with those intended informants, and thereby gather information from anonymous but authenticated sources. In this paper, to address the above-mentioned issues, we introduce an authenticated and deniable anonymous messaging framework. Its core component is a new cryptographic primitive dubbed deniable identity-based matchmaking encryption (DIB-ME), which captures plausible deniability under coercion and mutual authentication without interactions simultaneously. We further present a concrete DIB-ME construction and prove its security in the random oracle model. The performance analysis indicates merits of the proposed DIB-ME scheme. We also implement the proposed DIB-ME construction and present extensive experiment results, as a proof of concept to demonstrate its soundness and practicability.
Authors
- Jianghong Wei (ORCID: https://orcid.org/0000-0002-0286-7973)
- Xinyi Huang (ORCID: https://orcid.org/0000-0003-0070-1707)
- Yanmei Cao (ORCID: https://orcid.org/0000-0001-7564-1767)
- Xiaofeng Chen (ORCID: https://orcid.org/0000-0001-5858-5070)
- Yang Xiang (ORCID: https://orcid.org/0000-0001-5252-0831)
Institutions
- Hong Kong University of Science and Technology (HK)
- Integrated Chinese Medicine (China) (HK)
- Swinburne University of Technology (AU)
- University of Hong Kong (HK)
Publication Details
- Journal
- IEEE Transactions on Dependable and Secure Computing
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1109/tdsc.2024.3479236
- Citations
- 5
- Primary Topic
- Internet Traffic Analysis and Secure E-voting
- Type
- article
- Field-Weighted Citation Impact
- 1.74