Yan Huang
Computer Science · Indiana University
Publications
34
Citations
2,437
Est. group size
—
Recurring co-author estimate
Active years
15
Publishing since 2011
Yan Huang works in computer security and cryptography, with a focus on secure multi-party computation—methods that let multiple parties jointly compute results while keeping their individual data private. Related work includes privacy-preserving data inspection, secure computation of tasks like edit distance, and analyzing information flow in software programs. The research blends cryptographic protocol design with practical efficiency improvements.
Publication activity has slowed over the last decade, from about three papers per year in 2017 to under one per year on average recently.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Towards Efficient Privacy-Preserving Deep Packet Inspection
Lecture notes in computer science · 2024
- A Loopless Distributed Algorithm for Personalized Bilevel Optimization
2023
- Hash-Enabled Garbling and the Insecurity of Free-Hashing Garbled Circuits
2021
- Secure multi-party computation
Elsevier eBooks · 2020
- Efficient and Precise Secure Generalized Edit Distance and Beyond
IEEE Transactions on Dependable and Secure Computing · 2020
- Uncovering Information Flow Policy Violations in C Programs (Extended Abstract)
Lecture notes in computer science · 2019
- FlowNotation
2018
- JIMU: Faster LEGO-Based Secure Computation Using Additive Homomorphic Hashes
Lecture notes in computer science · 2017
- Pool
2017
- Faster LEGO-based Secure Computation without Homomorphic Commitments.
IACR Cryptology ePrint Archive · 2017
- The Cut-and-Choose Game and Its Application to Cryptographic Protocols
USENIX Security Symposium · 2016
- Lecture notes in computer science×3
- Elsevier eBooks×1
- IEEE Transactions on Dependable and Secure Computing×1
- USENIX Security Symposium×1
- IACR Cryptology ePrint Archive×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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