Shamik Sural

This paper investigates the vulnerability of Graph Neural Networks (GNNs) protected by Local Differential Privacy (LDP) to adversarial attacks, analyzing the interplay between privacy guarantees and adversarial robustness.

The paper introduces APLiance, a novel ABAC framework that models privacy policies as access requests and checks their compliance against legal requirements by mapping law sections to ABAC rules.

The paper introduces MuSimA, a web-based tool that addresses the lack of large-scale synthetic dataset generation for Attribute-based Access Control (ABAC) systems.

This paper introduces EXTree, a novel structure for Attribute-based Access Control (ABAC) policies that optimizes for both fast evaluation and human-understandable explanations when access is denied.