WebNishanth Chandran Microsoft Research India Ramachandran Ramjee Microsoft Research India Andreas Haberlen University of Pennsylvania See next page for additional authors ... Nishanth Chandran , Ramachandran Ramjee , Andreas Haeberlen. y, Harmeet Singh , Abhishek Modi , Saikrishna Badrinarayanan. 1z. y. WebNishanth Chandran (Microsoft Resea rch) Chaya Ganes h (IISc Bangalore) Vipul Goyal (Carnegie Mellon University) Shai Halevi (Algorand Foundation) David Heath (Georgia Tech) Lisa Kohl (CWI Amsterdam) Yehuda Lindell (Coinbase) Giulio Malavolta (M ax Planck Institute) Antigoni Polychroniadou (JP Morgan)
Nishanth Chandran - Sage Implementer - PlexSolution …
WebOct 30, 2024 · Assignee: Microsoft Technology Licensing, LLC Inventors: Nishanth Chandran, Divya Gupta, Sameer Wagh Filtering network traffic using protected filtering mechanisms Patent number: 10382453 Abstract: Concepts and technologies are disclosed herein for filtering network traffic using protected filtering mechanisms. WebJan 12, 2024 · Nishanth Chandran, Divya Gupta, and Akash Shah Abstract In 2 -party Circuit-based Private Set Intersection (Circuit-PSI), P 0 and P 1 hold sets S 0 and S 1 respectively … milan train station to city center
ACM India Industry Webinar with Nishanth Chandran
WebHe later spent two years as a Research Fellow at Microsoft Research Lab, India, where He worked in the cryptography group, on the EzPC (Easy Secure Multi-party Computation) project with Dr. Nishanth Chandran, Dr. Divya Gupta, Dr. … WebJun 20, 2024 · Nishanth Chandran, Microsoft Research (India) Divya Gupta, Microsoft Research (India) Abstract. Secure machine learning (ML) inference can provide meaningful privacy guarantees to both the client (holding sensitive input) and the server (holding sensitive weights of the ML model) while realizing inference-as-a-service. Although many … WebAug 18, 2024 · Deevashwer Rathee, Mayank Rathee, Nishant Kumar, Nishanth Chandran, Divya Gupta, Aseem Rastogi, and Rahul Sharma Abstract We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep Neural Networks (DNNs) using secure 2-party computation. milan trifunovic facebook