SARRE: Semantics-Aware Rule Recommendation and Enforcement for Event Paths on Android

摘要: This paper presents a semantics-aware rule recommendation and enforcement (SARRE) system for taming information leakage on Android. SARRE leverages statistical analysis novel application of minimum path cover algorithm to identify event paths from dynamic runtime monitoring. Then, an online is developed automatically assign fine-grained security each path, capitalizing both known rules semantic information. The proposed prototyped Android devices evaluated using real-world malware samples popular apps Google Play spanning multiple categories. Our results show that achieves 93.8% precision 96.4% recall in identifying the paths, compared with tainting technique. Also, average difference between manual configuration less than 5%, validating effectiveness automatic recommendation. It also demonstrated by enforcing recommended through camouflage engine, can effectively prevent enable protection over private data very small performance overhead.