Yuanzhao Li

dblp:360/2117 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2025
0009-0001-4688-6754ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 3 since 2021
YearPublicationVenuePosition
2025 Accountable Decryption Made Formal and Practical
abstract
With the increasing scale and complexity of online activities, accountability, as an after-the-fact mechanism, has become an effective complementary approach to ensure system security. Decades of research have delved into the connotation of accountability. They fail, however, to achieve practical accountability of decryption. This paper seeks to address this gap. We consider the scenario where a client (called encryptor, her) encrypts her data and then chooses a delegate (a.k.a. decryptor, him) that stores data for her. If the decryptor initiates an illegitimate decryption on the encrypted data, there is a non-negligible probability that this behavior will be detected, thereby holding the decryptor accountable for his decryption. We make three contributions. First, we review key definitions of accountability known so far. Based on extensive investigations, we formalize new definitions of accountability specifically targeting the decryption process, denoted as accountable decryption, and discuss the (im)possibilities when capturing this concept. We also define the security goals in correspondence. Second, we present a novel Trusted Execution Environment(TEE)-assisted solution aligning with definitions. Instead of fully trusting TEE, we take a further step, making TEE work in the “trust, but verify” model where we trust TEE and use its service, but empower users (i.e., decryptors) to detect the potentially compromised state of TEEs. Third, we implement a full-fledged system and conduct a series of evaluations. The results demonstrate that our solution is efficient. Even in a scenario involving$300,000$log entries, the decryption process concludes in approximately 5.5ms, and malicious decryptors can be identified within 69ms.
Rujia Li 0001, Yuanzhao Li, Qin Wang 0008, Sisi Duan, Qi Wang 0012, Mark Ryan 0001
IEEE Trans. Inf. Forensics Secur.2
2025 Bringing Smart Contract Confidentiality via Trusted Hardware: Fact and Fiction
abstract
Trusted Execution Environment (TEE)-assisted confidential smart contracts (TCSC) have attracted extensive attention from both academia and industry. Despite an enormous number of TCSC projects, the extent of confidentiality offered by them remains being questioned: the factual and fictional aspects are not well distinguished, which limits their adoption. In this paper, we provide a formal treatment of TCSC, endowing them with an expressive syntax and security definitions. Based on these definitions, we propose a provably secure TCSC instantiation. Then, we investigate each algorithm and identify the implementation flaws that may make a TCSC system violate its security properties. Our analysis reveals the gap between theoretical security models and real-world implementations: even assuming a TCSC is provably secure by design, it may still fail in practice. We further compare our TCSC instantiation with 16 representative TCSC systems. Our results show that, surprisingly, all these surveyed projects are subject to practical attacks. Finally, we implement a TCSC prototype and conduct a comprehensive evaluation, revealing the overheads of distributed key management and the performance challenges of executing complex contracts within TEEs.
Rujia Li 0001, Qin Wang 0008, Yuanzhao Li, Sisi Duan, Qi Wang 0012, David Galindo
IEEE Trans. Inf. Forensics Secur.3
2024 Action-Driven UAV Fingerprint Verification with Perception Data
Ning Xi 0002, Ruidong Han, Yuanzhao Li, Jianfeng Ma 0001, Yulong Shen 0001
ACISP (3)4