産総研：川本裕輔

Profile

I am the leader of Continuum Computing Trustworthiness Research Group at AIST (National Institute of Advanced Industrial Science and Technology).

Research

My research topic is the foundation of information security and software science, especially the modeling and verification of probabilistic programs, protocols, and systems by using the following approaches and their integration:

symbolic approach (e.g., formal methods, programming languages, and mathematical logic);
probabilistic approach (e.g., information theory, inferential statistics, and machine learning).

Examples of my recent research interests:

Formal methods for probabilistic systems and quantitative properties
- Statistical approach to program analysis [FAOC19] [ATVA17] [FM16] [ESORICS14] [CAV13]
- Foundation of quantitative information flow (QIF) [LMCS17] [QAPL15] [CSF13]
Formal specification and quality management of machine learning and artificial intelligence

Logic for statistics and machine learning [CAV25] [JELIA23] [AI23] [KR21] [SoSyM20]
Taxonomy for machine learning security [preprint23a]
Quality management guidelines for machine learning systems [AIQM Guidelines]

Foundation of privacy protection mechanisms
- Game theory for information leakage (QIF/DP) [ACM TOPS22] [Entropy18]
- Extension of differential privacy (DP) [ESORICS21] [Allerton19] [ESORICS19] [USENIX Sec19]

Details

Here is a publication list.
More details can be found in researchmap [Japanese | English]

Previously

Formal methods for cryptographic protocols and their computational soundness [CompSoft16] [AMH13] [ISPEC12]
Attacks on RSA PKCS#1 v1.5 on cryptographic device [CRYPTO12]
Attacks on the privacy of deep transfer learning [IJCNN21]

Yusuke Kawamoto