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Somesh Jha

Somesh Jha has 2 papers in our library, in 2017–2026; often with Matt Fredrikson, Mihai Christodorescu, Varun Chandrasekaran.

2 papers in our library · 2017–2026

OpenAlex · ORCID · Wikidata · h-index 71 · 355 works · 32,496 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 119 times in our library · 9 more in our library without a page yet · ⭐ Paper Stars ranking: #2411

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting (2017 · 1,036 citations)
    Models trained on sensitive records can expose facts about the people in their training sets. Before this work, the causes of that leakage were explained mostly through scattered anecdotes. Yeom, Giacomelli, Fredrikson and Jha study two black-box threats. Membership inference asks whether a given record was used for…
  2. SACTOR: LLM-Driven Correct and Idiomatic C to Rust Translation with Static Analysis and FFI-Based Verification (2026 · 1 citation)
    Moving legacy C code to Rust can remove whole classes of memory bugs. Rule-based converters such as C2Rust produce Rust that leans heavily on unsafe , and plain LLM prompting gives no assurance that the result behaves like the original. SACTOR addresses both problems. A libclang-based C Parser splits a program into…

All works

11 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Privacy Risk in Machine Learning: Analyzing the Connection to OverfittingarXiv:1709.01604Samuel Yeom, Irene Giacomelli, Matt Fredrikson, et al.2017 · 1,036 citations
  2. Towards automatic generation of vulnerability-based signatures ↗Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · no summary yetDavid Brumley et al.2006 · 297 citations
  3. Creating Vulnerability Signatures Using Weakest Preconditions ↗Proceedings - Computer Security Foundations Workshop/Proceedings · no summary yetDavid Brumley et al.2007 · 89 citations
  4. Identifying and Mitigating the Security Risks of Generative AI ↗Foundations and Trends® in Privacy and Security · no summary yetClark Barrett et al.2023 · 79 citations
  5. SoK: Watermarking for AI-Generated Content ↗Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · no summary yetXuandong Zhao et al.2025 · 33 citations
  6. Malware Detection ↗Advances in information security · no summary yetMihai Christodorescu et al.2007 · 29 citations
  7. Theory and Techniques for Automatic Generation of Vulnerability-Based Signatures ↗IEEE Transactions on Dependable and Secure Computing · no summary yetDavid Brumley et al.2008 · 28 citations
  8. Malware Detection (Advances in Information Security) ↗Springer eBooks · no summary yetMihai Christodorescu et al.2006 · 7 citations
  9. PolicyLR: A Logic Representation For Privacy Policies ↗arXiv:2408.14830 · no summary yetAshish Hooda et al.2024 · 2 citations

 Co-authors here

3 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 119 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

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