Checking More Alerting Less PRESENTED BY: AMIN ROIS SINUNG NUGROHO

Authors.

Pronounced as Apple.

Improvements of AAPL over previous works

Purifying Peer Apps  Noisy Apps: Most popular apps, frequently installed along. Filter with same category policy.  Accessories Apps: Compare similarity in apps description (English only) using natural language processing technique called semantic similarity.  Polluting Apps: Apps from the same developer with similar functionality. Filter by developer account.

Uncovering Privacy Disclosures  Conditional Flow Identification (sensitivities can’t be surely determined) a. Opportunistic Constant Evaluation (dependent on parameter value), e.g., uri=content://contacts//…” will be considered as sensitive data source. b. Object Origin Interface (dependent on object type), infer derived type of interested object, e.g., HttpsURLConnection.getOutputStream(), will be considered as sensitive sink.  Joint Flow Tracking joint flow tracking records all potential sources/sinks even they point to non-sensitive resources/channels, and finds all sub-flows containing potential sources or potential sinks by conservatively matching all potential sinks with all potential sources.

CHEX

IBM Wala

AAPL Usage Cases  Market Providers (e.g. Google Play) An efficient detection and screening system to detect apps with potential privacy leakages.  Users Identify apps with suspicious privacy disclosures. (should be developed further to recommend alternative apps with less or none privacy disclosures)  Developers Check whether their apps have suspicious privacy disclosures. If caused by third party library, choose an alternative library.

Already cited by 3 papers in less than a year.

Weaknesses  Peer apps selection has not been bound formally by an algorithm. Such algorithm will make it more scalable.  The authors skipped non English description from the peer apps filtering. It should not be hard to use digital translator such as Google translate to provide better peer apps filtering.  Peer voting mechanism will not work if majority of peer apps show similar behavior. Suspicious primary apps will be detected as legitimate in this scenario.  Because of Android fragmentation, this method might not work well in all Android version (software) or devices (hardware).

Further Improvement  Recommend an alternative apps from peer apps in a situation where the primary apps display suspicious privacy disclosures.

Thank you.