Machine learning (ML) is increasingly being adopted in a wide variety of application
domains. Usually, a well-performing ML model relies on a large volume of training data and …

Searchable Symmetric Encryption (SSE) when deployed in the cloud allows one to query
encrypted data without the risk of data leakage. Despite the widespread interest, existing …

Indistinguishability obfuscation, introduced by [Barak et. al. Crypto 2001], aims to compile
programs into unintelligible ones while preserving functionality. It is a fascinating and …

Federated learning has emerged as a promising approach for collaborative and privacy-
preserving learning. Participants in a federated learning process cooperatively train a model …

Depth estimation and scene parsing are two particularly important tasks in visual scene
understanding. In this paper we tackle the problem of simultaneous depth estimation and …

As 5G and mobile computing are growing rapidly, deep learning services in the Social
Computing and Social Internet of Things (IoT) have enriched our lives over the past few …

Cryptography is an indispensable tool used to protect information in computing systems. It is
used everywhere and by billions of people worldwide on a daily basis. It is used to protect …

Secure aggregation consists of computing the sum of data collected from multiple sources
without disclosing these individual inputs. Secure aggregation has been found useful for …

In the last few years, there has been significant interest in developing methods to search
over encrypted data. In the case of range queries, a simple solution is to encrypt the contents …

Deciding “greater-than” relations among data items just given their encryptions is at the
heart of search algorithms on encrypted data, most notably, non-interactive binary search on …