Anonymous systems lie at the intersection of theoretical cryptography and practical privacy-preserving technologies. Attribution can make anonymous systems more practical by adding accountability, revocation, or reputation functionality. Incorporating attribution into such systems is challenging because their core purpose is to preserve anonymity and prevent identification. This dissertation addresses the issue of attribution in two types of anonymous systems: anonymous authentication systems and anonymous reputation systems.Anonymous authentication systems enable a user to prove possession of valid credentials without revealing their identity, while revocation mechanisms ensure that misbehaving or no longer authorized users can be excluded from future access. These two goals are often in tension: strong anonymity can make revocation difficult, while efficient revocation mechanisms can introduce linkability or tracing features that weaken privacy. This dissertation studies the design, analysis, and implementation of revocable anonymous authentication systems in both pre-quantum and post-quantum settings, with a focus on practical constructions that preserve privacy under realistic trust and threat models.
These techniques are further extended to anonymous reputation systems, where users can accumulate and present trust signals anonymously without exposing their long-term identities or enabling unintended cross-session tracking. This dissertation develops separate frameworks for revocable anonymous authentication, anonymous reputation systems, and post-quantum revocable anonymous authenticated key exchange. The frameworks are analyzed extensively for their security and privacy properties, and detailed evaluations demonstrate the feasibility of these frameworks.
Details
- Kilari, Vishnu Teja (Author)
- Xue, Guoliang (Thesis advisor)
- Sen, Arunabha (Committee member)
- Zhang, Yanchao (Committee member)
- Misra, Satyajayant (Committee member)
- Arizona State University (Publisher)
- en
- Partial requirement for: Ph.D., Arizona State University, 2026
- Field of study: Computer Science