Owner-Centric Protection of Unstructured Data on Smartphones

Modern smartphone apps tend to contain and use vast amounts of data that can be broadly classified as

structured

and

unstructured

. Structured data, such as an user’s geolocation, has predefined semantics that can be retrieved by well-defined platform APIs. Unstructured data, on the other hand, relies on the context of the apps to reflect its meaning and value, and is typically provided by the user directly into an app’s interface. Recent research has shown that third-party apps are leaking highly-sensitive unstructured data, including user’s banking credentials. Unfortunately, none of the current solutions focus on the protection of unstructured data.

In this paper, we propose an owner-centric solution to protect unstructured data on smartphones. Our approach allows the data owners to specify security policies when providing their

untrusted

data to third-party apps. It tracks the flow of information to enforce the owner’s policies at strategic exit points. Based on this approach, we design and implement a system, called

DataChest

. We develop several mechanisms to reduce user burden and keep interruption to the minimum, while at the same time preventing the malicious apps from tricking the user. We evaluate our system against a set of real-world malicious apps and a series of synthetic attacks to show that it can successfully prevent the leakage of unstructured data while incurring reasonable performance overhead.