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Mayank Rathee
Mayank Rathee
Verified email at berkeley.edu - Homepage
Title
Cited by
Cited by
Year
Cryptflow: Secure tensorflow inference
N Kumar, M Rathee, N Chandran, D Gupta, A Rastogi, R Sharma
2020 IEEE Symposium on Security and Privacy (SP), 336-353, 2020
1462020
CrypTFlow2: Practical 2-party secure inference
D Rathee, M Rathee, N Kumar, N Chandran, D Gupta, A Rastogi, ...
Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications …, 2020
1032020
Function secret sharing for mixed-mode and fixed-point secure computation
E Boyle, N Chandran, N Gilboa, D Gupta, Y Ishai, N Kumar, M Rathee
Advances in Cryptology–EUROCRYPT 2021: 40th Annual International Conference …, 2021
342021
Sirnn: A math library for secure rnn inference
D Rathee, M Rathee, RKK Goli, D Gupta, R Sharma, N Chandran, ...
2021 IEEE Symposium on Security and Privacy (SP), 1003-1020, 2021
222021
Waldo: A private time-series database from function secret sharing
E Dauterman, M Rathee, RA Popa, I Stoica
2022 IEEE Symposium on Security and Privacy (SP), 2450-2468, 2022
142022
Checking laws of the blockchain with property-based testing
A Chepurnoy, M Rathee
2018 International Workshop on Blockchain Oriented Software Engineering …, 2018
92018
Efficient Protocols for Private Database Queries
TK Saha, Mayank, T Koshiba
DBSec 2017 10359 (LNCS), 337-348, 2017
92017
Efficient private database queries using ring-LWE somewhat homomorphic encryption
TK Saha, M Rathee, T Koshiba
Journal of Information Security and Applications 49, 102406, 2019
82019
Secure medical image analysis with cryptflow
J Alvarez-Valle, P Bhatu, N Chandran, D Gupta, A Nori, A Rastogi, ...
arXiv preprint arXiv:2012.05064, 2020
72020
SIRNN: A math library for secure inference of RNNs
D Rathee, M Rathee, RKK Goli, D Gupta, R Sharma, N Chandran, ...
IEEE S&P, 2021
62021
Private Comparison Protocol and Its Application to Range Queries
TK Saha, Mayank, Deevashwer, T Koshiba
International Conference on Internet and Distributed Computing System 10, 2017
12017
ELSA: Secure Aggregation for Federated Learning with Malicious Actors
M Rathee, C Shen, S Wagh, RA Popa
Cryptology ePrint Archive, 2022
2022
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