Ajith Suresh

Orcid: 0000-0002-5164-7758

According to our database1, Ajith Suresh authored at least 31 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2025
High-Throughput Secure Multiparty Computation with an Honest Majority in Various Network Settings.
Proc. Priv. Enhancing Technol., 2025

2024
Privadome: Delivery Drones and Citizen Privacy.
Proc. Priv. Enhancing Technol., 2024

Don't Eject the Impostor: Fast Three-Party Computation With a Known Cheater.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

2023
MPClan: Protocol Suite for Privacy-Conscious Computations.
J. Cryptol., July, 2023

Comments on "Privacy-Enhanced Federated Learning Against Poisoning Adversaries".
IEEE Trans. Inf. Forensics Secur., 2023

SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning.
IACR Cryptol. ePrint Arch., 2023

PrivMail: A Privacy-Preserving Framework for Secure Emails.
IACR Cryptol. ePrint Arch., 2023

Don't Eject the Impostor: Fast Three-Party Computation With a Known Cheater (Full Version).
IACR Cryptol. ePrint Arch., 2023

FLUTE: Fast and Secure Lookup Table Evaluations (Full Version).
IACR Cryptol. ePrint Arch., 2023

ScionFL: Efficient and Robust Secure Quantized Aggregation.
IACR Cryptol. ePrint Arch., 2023

FANNG-MPC: Framework for Artificial Neural Networks and Generic MPC.
IACR Cryptol. ePrint Arch., 2023

HyFL: A Hybrid Approach For Private Federated Learning.
CoRR, 2023

FLUTE: Fast and Secure Lookup Table Evaluations.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

2022
MPClan: Protocol Suite for Privacy-Conscious Computations.
IACR Cryptol. ePrint Arch., 2022

ScionFL: Secure Quantized Aggregation for Federated Learning.
CoRR, 2022

Privacy-Preserving Epidemiological Modeling on Mobile Graphs.
CoRR, 2022

Privadome: Protecting Citizen Privacy from Delivery Drones.
CoRR, 2022

Poster MPClan: : Protocol Suite for Privacy-Conscious Computations.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Poster: Efficient Three-Party Shuffling Using Precomputation.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Poster: Privacy-Preserving Epidemiological Modeling on Mobile Graphs.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
SynCirc: Efficient Synthesis of Depth-Optimized Circuits for Secure Computation.
IACR Cryptol. ePrint Arch., 2021

Tetrad: Actively Secure 4PC for Secure Training and Inference.
IACR Cryptol. ePrint Arch., 2021

MPCLeague: Robust MPC Platform for Privacy-Preserving Machine Learning.
CoRR, 2021

2020
FLASH: Fast and Robust Framework for Privacy-preserving Machine Learning.
Proc. Priv. Enhancing Technol., 2020

ABY2.0: Improved Mixed-Protocol Secure Two-Party Computation.
IACR Cryptol. ePrint Arch., 2020

BLAZE: Blazing Fast Privacy-Preserving Machine Learning.
IACR Cryptol. ePrint Arch., 2020

SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning.
IACR Cryptol. ePrint Arch., 2020

Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning.
Proceedings of the 27th Annual Network and Distributed System Security Symposium, 2020

2019
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning.
IACR Cryptol. ePrint Arch., 2019

ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction.
IACR Cryptol. ePrint Arch., 2019

2016
Fast Actively Secure OT Extension for Short Secrets.
IACR Cryptol. ePrint Arch., 2016


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