Securing Databases from Probabilistic Inference

2017/06/08 by Guarnieri, Marco, Marinovic, Srdjan, Basin, David
#Cryptography and Security (cs.CR) #Databases (cs.DB) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.1706.02473

Abstract

Databases can leak confidential information when users combine query results with probabilistic data dependencies and prior knowledge. Current research offers mechanisms that either handle a limited class of dependencies or lack tractable enforcement algorithms. We propose a foundation for Database Inference Control based on ProbLog, a probabilistic logic programming language. We leverage this foundation to develop Angerona, a provably secure enforcement mechanism that prevents information leakage in the presence of probabilistic dependencies. We then provide a tractable inference algorithm for a practically relevant fragment of ProbLog. We empirically evaluate Angerona's performance showing that it scales to relevant security-critical problems.

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