Publications (16)
SIRNN: A Math Library for Secure RNN Inference
Deevashwer Rathee, Mayank Rathee, Rahul Kranti Kiran Goli +4
Complex machine learning (ML) inference algorithms like recurrent neural networks (RNNs) use standard functions from math libraries like exponentiation, sigmoid, tanh, and reciproc…
Privacy-Preserving Federated Learning: Integrating Zero-Knowledge Proofs in Scalable Distributed Architectures
Divya Gupta
The intersection of Artificial Intelligence (AI) and distributed systems has given rise to Federated Learning (FL), a paradigm that enables decentralized model training without com…
Efficient ML Models for Practical Secure Inference
Vinod Ganesan, Anwesh Bhattacharya, Pratyush Kumar +3
ML-as-a-service continues to grow, and so does the need for very strong privacy guarantees. Secure inference has emerged as a potential solution, wherein cryptographic primitives a…
On Constant-Round Concurrent Zero-Knowledge from a Knowledge Assumption
Divya Gupta, Amit Sahai
In this work, we consider the long-standing open question of constructing constant-round concurrent zero-knowledge protocols in the plain model. Resolving this question is known to…
Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran +6
We present CRYPTFLOW, a system that converts TensorFlow inference code into Secure Multi-party Computation (MPC) protocols at the push of a button. To do this, we build two compone…
Multi-institution encrypted medical imaging AI validation without data sharing
Arjun Soin, Pratik Bhatu, Rohit Takhar +6
Adoption of artificial intelligence medical imaging applications is often impeded by barriers between healthcare systems and algorithm developers given that access to both private…
Personalized Artificial General Intelligence (AGI) via Neuroscience-Inspired Continuous Learning Systems
Rajeev Gupta, Suhani Gupta, Ronak Parikh +3
Artificial Intelligence has made remarkable advancements in recent years, primarily driven by increasingly large deep learning models. However, achieving true Artificial General In…
Polymerized spacetime dynamics with multi-field source: unraveling the pre-inflationary Universe
Divya Gupta, Manabendra Sharma, Gustavo S. Vicente +2
We study a multi-field model in Loop Quantum Cosmology for a maximally symmetric spacetime governed by the Einstein--Hilbert action minimally coupled to scalar fields. Using a Lege…
CrypTFlow: Secure TensorFlow Inference
Nishant Kumar, Mayank Rathee, Nishanth Chandran +3
We present CrypTFlow, a first of its kind system that converts TensorFlow inference code into Secure Multi-party Computation (MPC) protocols at the push of a button. To do this, we…
EinsteinPy: A Community Python Package for General Relativity
Shreyas Bapat, Ritwik Saha, Bhavya Bhatt +46
This paper presents EinsteinPy (version 0.3), a community-developed Python package for gravitational and relativistic astrophysics. Python is a free, easy to use a high-level progr…
TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs
Tanmay Rajore, Nishanth Chandran, Sunayana Sitaram +4
Benchmarking is the de-facto standard for evaluating LLMs, due to its speed, replicability and low cost. However, recent work has pointed out that the majority of the open source b…
TrustRate: A Decentralized Platform for Hijack-Resistant Anonymous Reviews
Rohit Dwivedula, Sriram Sridhar, Sambhav Satija +4
Reviews and ratings by users form a central component in several widely used products today (e.g., product reviews, ratings of online content, etc.), but today's platforms for mana…
Privacy Preserving Multi-Agent Reinforcement Learning in Supply Chains
Ananta Mukherjee, Peeyush Kumar, Boling Yang +2
This paper addresses privacy concerns in multi-agent reinforcement learning (MARL), specifically within the context of supply chains where individual strategic data must remain con…
Blockene: A High-throughput Blockchain Over Mobile Devices
Sambhav Satija, Apurv Mehra, Sudheesh Singanamalla +5
We introduce Blockene, a blockchain that reduces resource usage at member nodes by orders of magnitude, requiring only a smartphone to participate in block validation and consensus…
CrypTFlow2: Practical 2-Party Secure Inference
Deevashwer Rathee, Mayank Rathee, Nishant Kumar +4
We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep Neural Networks (DNNs) using secure 2-party computation. CrypTFlow2 protocols are both cor…
Enterprise AI Must Enforce Participant-Aware Access Control
Shashank Shreedhar Bhatt, Tanmay Rajore, Khushboo Aggarwal +10
Large language models (LLMs) are increasingly deployed in enterprise settings where they interact with multiple users and are trained or fine-tuned on sensitive internal data. Whil…