collaborators

5 papers

cs.DB2026

Towards Inference-Aware Privacy Guidance for Data Preparation

Vishal Chakraborty, Felix Naumann

Data preparation often begins with sensitive data and produces a releasable artifact for analysis, sharing, or model training. Existing workflows are primarily guided by utility: a…

cs.DB2026

Don't Stir the Pot! Authorized Vector Data Retrieval via Access-Aware Indexing

Shanshan Han, Vishal Chakraborty, Sharad Mehrotra

Vector databases increasingly enforce role-based access control, where each top-k approximate nearest neighbor query must return only vectors the querying role is authorized to acc…

cs.CR2026

Post-Quantum Cryptographic Analysis of Message Transformations Across the Network Stack

Ashish Kundu, Vishal Chakraborty, Ramana Kompella

When a user sends a message over a wireless network, the message does not travel as-is. It is encrypted, authenticated, encapsulated, and transformed as it descends the protocol st…

cs.DB2026

Inference-Aware & Privacy-Preserving Deletion in Databases

Vishal Chakraborty, Youri Kaminsky, Arnav Abhijit Dhariya +3

Deletion is a fundamental database operation, yet modern systems often fail to provide the privacy guarantee that users expect from it. A deleted value may disappear from query res…

cs.DB2025

Meaningful Data Erasure in the Presence of Dependencies

Vishal Chakraborty, Youri Kaminsky, Sharad Mehrotra +5

Data regulations like GDPR require systems to support data erasure but leave the definition of "erasure" open to interpretation. This ambiguity makes compliance challenging, especi…