Today’s smartphone operating systems frequently fail to provide users with visibility into how third-party applications collect and share their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid enables realtime analysis by leveraging Android’s virtualized execution environment. TaintDroid incurs only 32p performance overhead on a CPU-bound microbenchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, in our 2010 study we found 20 applications potentially misused users’ private information; so did a similar fraction of the tested applications in our 2012 study. Monitoring the flow of privacy-sensitive data with TaintDroid provides valuable input for smartphone users and security service firms seeking to identify misbehaving applications.

/pdf/taintdroid-an-information-flow-tracking-system-for-realtime-5d8smsr0iy.pdf

TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

Today's smartphone operating systems frequently fail to provide users with adequate control over and visibility into how third-party applications use their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid provides realtime analysis by leveraging Android's virtualized execution environment. TaintDroid incurs only 14% performance overhead on a CPU-bound micro-benchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, we found 68 instances of potential misuse of users' private information across 20 applications. Monitoring sensitive data with TaintDroid provides informed use of third-party applications for phone users and valuable input for smartphone security service firms seeking to identify misbehaving applications.

/pdf/taintdroid-an-information-flow-tracking-system-for-realtime-3fnz9lwdso.pdf

TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

Today's smartphones are a ubiquitous source of private and confidential data. At the same time, smartphone users are plagued by carelessly programmed apps that leak important data by accident, and by malicious apps that exploit their given privileges to copy such data intentionally. While existing static taint-analysis approaches have the potential of detecting such data leaks ahead of time, all approaches for Android use a number of coarse-grain approximations that can yield high numbers of missed leaks and false alarms. In this work we thus present FlowDroid, a novel and highly precise static taint analysis for Android applications. A precise model of Android's lifecycle allows the analysis to properly handle callbacks invoked by the Android framework, while context, flow, field and object-sensitivity allows the analysis to reduce the number of false alarms. Novel on-demand algorithms help FlowDroid maintain high efficiency and precision at the same time. We also propose DroidBench, an open test suite for evaluating the effectiveness and accuracy of taint-analysis tools specifically for Android apps. As we show through a set of experiments using SecuriBench Micro, DroidBench, and a set of well-known Android test applications, FlowDroid finds a very high fraction of data leaks while keeping the rate of false positives low. On DroidBench, FlowDroid achieves 93% recall and 86% precision, greatly outperforming the commercial tools IBM AppScan Source and Fortify SCA. FlowDroid successfully finds leaks in a subset of 500 apps from Google Play and about 1,000 malware apps from the VirusShare project.

/pdf/flowdroid-precise-context-flow-field-object-sensitive-and-303w6s31hk.pdf

FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps

An important open problem in the area of Traitor Tracing is designing a scheme with constant expansion of the size of keys (users' keys and the encryption key) and of the size of ciphertexts with respect to the size of the plaintext. This problem is known from the introduction of Traitor Tracing by Chor, Fiat and Naor. We refer to such schemes as traitor tracing with constant transmission rate. Here we present a general methodology and two protocol constructions that result in the first two public-key traitor tracing schemes with constant transmission rate in settings where plaintexts can be calibrated to be sufficiently large. Our starting point is the notion of copyrighted function which was presented by Naccache, Shamir and Stern. We first solve the open problem of discrete-log-based and public-key-based copyrighted function. Then, we observe the simple yet crucial relation between (public-key) copyrighted encryption and (public-key) traitor tracing, which we exploit by introducing a generic design paradigm for designing constant transmission rate traitor tracing schemes based on copyrighted encryption functions. Our first scheme achieves the same expansion efficiency as regular ElGamal encryption. The second scheme introduces only a slightly larger (constant) overhead, however, it additionally achieves efficient black-box traitor tracing (against any pirate construction).

Traitor Tracing with constant transmission rate

We present DroidSafe, a static information flow analysis tool that reports potential leaks of sensitive information in Android applications. DroidSafe combines a comprehensive, accurate, and precise model of the Android runtime with static analysis design decisions that enable the DroidSafe analyses to scale to analyze this model. This combination is enabled by accurate analysis stubs, a technique that enables the effective analysis of code whose complete semantics lies outside the scope of Java, and by a combination of analyses that together can statically resolve communication targets identified by dynamically constructed values such as strings and class designators. Our experimental results demonstrate that 1) DroidSafe achieves unprecedented precision and accuracy for Android information flow analysis (as measured on a standard previously published set of benchmark applications) and 2) DroidSafe detects all malicious information flow leaks inserted into 24 real-world Android applications by three independent, hostile Red-Team organizations. The previous state-of-the art analysis, in contrast, detects less than 10% of these malicious flows.

/pdf/information-flow-analysis-of-android-applications-in-4a62sj2ni8.pdf

Information-Flow Analysis of Android Applications in DroidSafe

Verifying that programs trusted to enforce security actually do so is a practical concern for programmers and administrators. However, there is a disconnect between the kinds of tools that have been successfully applied to real software systems (such as taint mode in Perl and Ruby), and information-flow compilers that enforce a variant of the stronger security property of noninterference. Tools that have been successfully used to find security violations have focused on explicit flows of information, where high-security information is directly leaked to output. Analysis tools that enforce noninterference also prevent implicit flows of information, where high-security information can be inferred from a program's flow of control. However, these tools have seen little use in practice, despite the stronger guarantees that they provide.

To better understand why, this paper experimentally investigates the explicit and implicit flows identified by the standard algorithm for establishing noninterference. When applied to implementations of authentication and cryptographic functions, the standard algorithm discovers many real implicit flows of information, but also reports an extremely high number of false alarms, most of which are due to conservative handling of unchecked exceptions (e.g., null pointer exceptions). After a careful analysis of all sources of true and false alarms, due to both implicit and explicit flows, the paper concludes with some ideas to improve the false alarm rate, toward making stronger security analysis more practical.

/pdf/implicit-flows-can-t-live-with-em-can-t-live-without-em-1jctsstgs2.pdf

Implicit Flows: Can't Live with `Em, Can't Live without `Em

The web is now being used as a general platform for hosting distributed applications like wikis, bulletin board messaging systems and collaborative editing environments. Data from multiple applications originating at multiple sources all intermix in a single web browser, making sensitive data stored in the browser subject to a broad milieu of attacks (cross-site scripting, cross-site request forgery and others). The fundamental problem is that existing web infrastructure provides no means for enforcing end-to-end security on data. To solve this we design an architecture using mandatory access control (MAC) enforcement. We overcome the limitations of traditional MAC systems, implemented solely at the operating system layer, by unifying MAC enforcement across virtual machine, operating system, networking and application layers. We implement our architecture using Xen virtual machine management, SELinux at the operating system layer, labeled IPsec for networking and our own label-enforcing web browser, called FlowwolF. We tested our implementation and find that it performs well, supporting data intermixing while still providing end-to-end security guarantees.

http://www.cse.psu.edu/~trj1/papers/sacmat10-hicks.pdf

An architecture for enforcing end-to-end access control over web applications

Security-typed languages (STLs) are powerful tools for provably implementing policy in applications. The programmer maps policy onto programs by annotating types with information flow labels, and the STL compiler guarantees that data always obeys its label as it flows within an application. As data flows into or out of an application, however, a runtime system is needed to mediate between the information flow world within the application and the non-information flow world of the operating system. In the few existing STL applications, this problem has been handled in ad hoc ways that hindered software engineering and security analysis. In this paper, we present a principled approach to STL runtime system development along with policy infrastructure and class abstractions for the STL, Jif that implement these principles. We demonstrate the effectiveness of our approach by using our infrastructure to develop a firewall application, Flow Wall, that provably enforces its policy.

/pdf/channels-runtime-system-infrastructure-for-security-typed-4al1g0hbqc.pdf

Boniface Hicks

Papers

Implicit Flows: Can't Live with `Em, Can't Live without `Em

An architecture for enforcing end-to-end access control over web applications

Channels: Runtime System Infrastructure for Security-Typed Languages