Boneh, Dan

Ensemble Adversarial Training: Attacks and Defenses

Tramèr, F., Kurakin, A., Papernot, N., Goodfellow, I., Boneh, D., & McDaniel, P. (2017) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 2,176

Bulletproofs: Short Proofs for Confidential Transactions and More

Bunz, B., Bootle, J., Boneh, D., Poelstra, A., Wuille, P., & Maxwell, G. (2018) · 2018 IEEE Symposium on Security and Privacy (SP)

Cryptography and Data SecurityBlockchain Technology Applications and Security

Cited by 1,154

Do Users Write More Insecure Code with AI Assistants?

Perry, N., Srivastava, M., Kumar, D., & Boneh, D. (2023) · Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

Software Engineering ResearchWeb Application Security Vulnerabilities

Cited by 259

Quantum Cryptanalysis of Hidden Linear Functions

Boneh, D., & Lipton, R. J. (1995) · Lecture Notes in Computer Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 161

Adversarial training and robustness for multiple perturbations

Tramèr, F., & Boneh, D. (2019) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 145

Deriving genomic diagnoses without revealing patient genomes

Jagadeesh, K. A., Wu, D. J., Birgmeier, J. A., Boneh, D., & Bejerano, G. (2017) · Science

Cryptography and Data SecurityPrivacy-Preserving Technologies in Data

Cited by 134

FairProof : Confidential and Certifiable Fairness for Neural Networks

Yadav, C., Chowdhury, A. R., Boneh, D., & Chaudhuri, K. (2024) · arXiv

Cryptography and Data SecurityEthics and Social Impacts of AI

Cited by 2