kaihua at qin.ac
I’m a Ph.D. student at Imperial College London, where I am very fortunate to be supervised by Dr. Arthur Gervais. I also work closely with Prof. Dawn Song at UC Berkeley RDI and Liyi Zhou at Imperial College London.
My academic interests center around designing and building decentralized systems that are secure, stable, and incentive-compatible. The inherent complexity of real-world decentralized systems, with their interdependent and interacting layers, poses a fascinating challenge in achieving this objective. My primary focus is on permissionless blockchains and decentralized finance (DeFi). In my research, I aim to systematically measure and quantify various problems encountered in the rapidly evolving blockchain and DeFi ecosystems. I also strive to develop real-time offensive and defensive solutions by utilizing advanced program analysis techniques to enhance smart contract security. Furthermore, I intend to devise innovative financial primitives that minimize the systemic risks of DeFi. My research is informed by the fields of security, program analysis, measurement, and finance. I am also actively exploring the application of machine learning and game theory to my research pursuits.
|Jan 28, 2023||Our paper titled “The Blockchain Imitation Game” has been accepted at Usenix Security 2023!|
|Jan 19, 2023||Our paper on mitigating DeFi liquidations has been accepted at FC 2023!|
- The blockchain imitation gameIn 32nd USENIX Security Symposium (USENIX Security 23) 2023
- Mitigating decentralized finance liquidations with reversible call optionsIn International Conference on Financial Cryptography and Data Security 2023
- Quantifying blockchain extractable value: How dark is the forest?In 2022 IEEE Symposium on Security and Privacy (SP) 2022
- An empirical study of defi liquidations: Incentives, risks, and instabilitiesIn Proceedings of the 21st ACM Internet Measurement Conference 2021
- Attacking the defi ecosystem with flash loans for fun and profitIn International Conference on Financial Cryptography and Data Security 2021