Shmatikov, Vitaly

Membership Inference Attacks Against Machine Learning Models

Shokri, R., Stronati, M., Song, C., & Shmatikov, V. (2017) · 2017 IEEE Symposium on Security and Privacy (SP)

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 4,754

Robust De-anonymization of Large Sparse Datasets

Narayanan, A., & Shmatikov, V. (2008) · 2008 IEEE Symposium on Security and Privacy (sp 2008)

Privacy-Preserving Technologies in DataInternet Traffic Analysis and Secure E-voting

Cited by 2,372

Privacy-preserving deep learning

Shokri, R., & Shmatikov, V. (2015) · Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 2,356

Exploiting Unintended Feature Leakage in Collaborative Learning

Melis, L., Song, C., De Cristofaro, E., & Shmatikov, V. (2019) · 2019 IEEE Symposium on Security and Privacy (SP)

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 1,734

How to backdoor federated learning

Bagdasaryan, E., Veit, A., Hua, Y., Estrin, D., & Shmatikov, V. (2018) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 1,495

Machine Learning Models that Remember Too Much

Song, C., Ristenpart, T., & Shmatikov, V. (2017) · Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 526

Myths and fallacies of personally identifiable information

Narayanan, A., & Shmatikov, V. (2010) · Communications of the ACM

Privacy, Security, and Data ProtectionPrivacy-Preserving Technologies in Data

Cited by 346

"You Might Also Like:" Privacy Risks of Collaborative Filtering

Calandrino, J. A., Kilzer, A., Narayanan, A., Felten, E. W., & Shmatikov, V. (2011) · 2011 IEEE Symposium on Security and Privacy

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 311

Privacy-preserving deep learning

Shokri, R., & Shmatikov, V. (2015) · 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 223

Differential Privacy Has Disparate Impact on Model Accuracy

Bagdasaryan, E., & Shmatikov, V. (2019) · arXiv

Privacy-Preserving Technologies in DataEthics and Social Impacts of AI

Cited by 219

Using Frankencerts for Automated Adversarial Testing of Certificate Validation in SSL/TLS Implementations

Brubaker, C., Jana, S., Ray, B., Khurshid, S., & Shmatikov, V. (2014) · 2014 IEEE Symposium on Security and Privacy

Web Application Security VulnerabilitiesSoftware Testing and Debugging Techniques

Cited by 218

Auditing Data Provenance in Text-Generation Models

Song, C., & Shmatikov, V. (2018) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 199

The tao of inference in privacy-protected databases

Bindschaedler, V., Grubbs, P., Cash, D., Ristenpart, T., & Shmatikov, V. (2018) · Proceedings of the VLDB Endowment

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 75

Multi-Agent Systems Execute Arbitrary Malicious Code

Triedman, H., Jha, R., & Shmatikov, V. (2025) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 52

How to Steal Reasoning Without Reasoning Traces

Zhang, T., Morris, J. X., & Shmatikov, V. (2026) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 0