arXiv subjects

Miti Mazmudar

Publications and source records attributed to Miti Mazmudar.

2 recordsLinked to original sources

arXiv2024

Peer2PIR: Private Queries for IPFS

The InterPlanetary File System (IPFS) is a peer-to-peer network for storing data in a distributed file system, hosting over 190,000 peers spanning 152 countries. Despite its prominence, the privacy properties that IPFS offers to peers are severely limited. Any query within the network leaks the queried content to other peers. We address IPFS' privacy leakage across three functionalities (peer routing, provider advertisements, and content retrieval), ultimately empowering peers to privately navigate and retrieve content in the network. Our work highlights and addresses novel challenges inherent to integrating PIR into distributed systems. We present our new, private protocols and demonstrate that they incur reasonably low communication and computation overheads. We also provide a systematic comparison of state-of-art PIR protocols in the context of distributed systems.

cs.CR↗

arXiv2022

Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration

Differential privacy (DP) allows data analysts to query databases that contain users' sensitive information while providing a quantifiable privacy guarantee to users. Recent interactive DP systems such as APEx provide accuracy guarantees over the query responses, but fail to support a large number of queries with a limited total privacy budget, as they process incoming queries independently from past queries. We present an interactive, accuracy-aware DP query engine, CacheDP, which utilizes a differentially private cache of past responses, to answer the current workload at a lower privacy budget, while meeting strict accuracy guarantees. We integrate complex DP mechanisms with our structured cache, through novel cache-aware DP cost optimization. Our thorough evaluation illustrates that CacheDP can accurately answer various workload sequences, while lowering the privacy loss as compared to related work.

cs.CR↗