65 citations · 207 across the 20 of their papers we have counts for
9 papers · 1 filter
Multimodal Privacy-Preserving Entity Resolution with Fully Homomorphic Encryption
Susim Roy, Nalini Ratha
The canonical challenge of entity resolution within high-compliance sectors, where secure identity reconciliation is frequently confounded by significant data heterogeneity, includ…
Shielding Latent Face Representations From Privacy Attacks
Arjun Ramesh Kaushik, Bharat Chandra Yalavarthi, Arun Ross +2
In today's data-driven analytics landscape, deep learning has become a powerful tool, with latent representations, known as embeddings, playing a central role in several applicatio…
Towards Building Secure UAV Navigation with FHE-aware Knowledge Distillation
Arjun Ramesh Kaushik, Charanjit Jutla, Nalini Ratha
In safeguarding mission-critical systems, such as Unmanned Aerial Vehicles (UAVs), preserving the privacy of path trajectories during navigation is paramount. While the combination…
Confidential and Protected Disease Classifier using Fully Homomorphic Encryption
Aditya Malik, Nalini Ratha, Bharat Yalavarthi +3
With the rapid surge in the prevalence of Large Language Models (LLMs), individuals are increasingly turning to conversational AI for initial insights across various domains, inclu…
Enhancing Privacy and Security of Autonomous UAV Navigation
Vatsal Aggarwal, Arjun Ramesh Kaushik, Charanjit Jutla +1
Autonomous Unmanned Aerial Vehicles (UAVs) have become essential tools in defense, law enforcement, disaster response, and product delivery. These autonomous navigation systems req…
Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption
Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross +2
Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templ…
Efficient Encrypted Inference on Ensembles of Decision Trees
Kanthi Sarpatwar, Karthik Nandakumar, Nalini Ratha +4
Data privacy concerns often prevent the use of cloud-based machine learning services for sensitive personal data. While homomorphic encryption (HE) offers a potential solution by e…
Efficient CNN Building Blocks for Encrypted Data
Nayna Jain, Karthik Nandakumar, Nalini Ratha +2
Machine learning on encrypted data can address the concerns related to privacy and legality of sharing sensitive data with untrustworthy service providers. Fully Homomorphic Encryp…
Securing CNN Model and Biometric Template using Blockchain
Akhil Goel, Akshay Agarwal, Mayank Vatsa +2
Blockchain has emerged as a leading technology that ensures security in a distributed framework. Recently, it has been shown that blockchain can be used to convert traditional bloc…