Ultimate Power of Inference Attacks: Privacy Risks of High-Dimensional Models. - Sasi Kumar Murakonda; Reza Shokri; George Theodorakopoulos 001 (CoRR, 2019)

On Adversarial Bias and the Robustness of Fair Machine Learning. - Hongyan Chang; Ta Duy Nguyen; Sasi Kumar Murakonda; Ehsan Kazemi 001; Reza Shokri (CoRR, 2020)

ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning. - Sasi Kumar Murakonda; Reza Shokri (CoRR, 2020)

Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models. - Sasi Kumar Murakonda; Reza Shokri; George Theodorakopoulos 001 (AISTATS, 2021)

Enhanced Membership Inference Attacks against Machine Learning Models. - Jiayuan Ye 001; Aadyaa Maddi; Sasi Kumar Murakonda; Reza Shokri (CoRR, 2021)

Enhanced Membership Inference Attacks against Machine Learning Models. - Jiayuan Ye 001; Aadyaa Maddi; Sasi Kumar Murakonda; Vincent Bindschaedler; Reza Shokri (CCS, 2022)

Starlit: Privacy-Preserving Federated Learning to Enhance Financial Fraud Detection. - Aydin Abadi; Bradley Doyle; Francesco Gini; Kieron Guinamard; Sasi Kumar Murakonda; Jack Liddell; Paul Mellor; Steven J. Murdoch; Mohammad Naseri; Hector Page; George Theodorakopoulos 001; Suzanne Weller (IACR Cryptol. ePrint Arch., 2024)