51 research outputs found
Ghera: A Repository of Android App Vulnerability Benchmarks
Security of mobile apps affects the security of their users. This has fueled
the development of techniques to automatically detect vulnerabilities in mobile
apps and help developers secure their apps; specifically, in the context of
Android platform due to openness and ubiquitousness of the platform. Despite a
slew of research efforts in this space, there is no comprehensive repository of
up-to-date and lean benchmarks that contain most of the known Android app
vulnerabilities and, consequently, can be used to rigorously evaluate both
existing and new vulnerability detection techniques and help developers learn
about Android app vulnerabilities. In this paper, we describe Ghera, an open
source repository of benchmarks that capture 25 known vulnerabilities in
Android apps (as pairs of exploited/benign and exploiting/malicious apps). We
also present desirable characteristics of vulnerability benchmarks and
repositories that we uncovered while creating Ghera.Comment: 10 pages. Accepted at PROMISE'1
Gluon transverse momentum dependent correlators in polarized high energy processes
We investigate the gluon transverse momentum dependent correlators as Fourier transform of matrix elements of nonlocal operator combinations. At the operator level these correlators include both field strength operators and gauge links bridging the nonlocality. In contrast to the collinear PDFs, the gauge links are no longer unique for transverse momentum dependent PDFs (TMDs) and also Wilson loops lead to nontrivial effects. We look at gluon TMDs for unpolarized, vector and tensor polarized targets. In particular a single Wilson loop operators become important when one considers the small-x limit of gluon TMDs
PPAndroid-Benchmarker: Benchmarking Privacy Protection Systems on Android Devices
Mobile devices are ubiquitous in today's digital world. While people enjoy the convenience brought by mobile devices, it has been proven that many mobile apps leak personal information without user consent or even awareness. That can occur due to many reasons, such as careless programming errors, intention of developers to collect private information, infection of innocent apps by malware, etc. Thus, the research community has proposed many methods and systems to detect privacy leakage and prevent such detected leakage on mobile devices. This is a to do note at margin While it is obviously essential to evaluate the accuracy and effectiveness of privacy protection systems, we are not aware of any automated system that can benchmark performance of privacy protection systems on Android devices. In this paper, we report PPAndroid-Benchmarker, the first system of this kind, which can fairly benchmark any privacy protection systems dynamically (i.e., in run time) or statically. PPAndroid-Benchmarker has been released as an open-source tool and we believe that it will help the research community, developers and even end users to analyze, improve, and choose privacy protection systems on Android devices. We applied PPAndroid-Benchmarker in dynamic mode to 165 Android apps with some privacy protection features, selected from variant app markets and the research community, and showed effectiveness of the tool. We also illustrate two components of PPAndroid-Benchmarker on the design level, which are Automatic Test Apps Generator for benchmarking static analysis based tools and Reconfigurability Engine that allows any instance of PPAndroid-Benchmarker to be reconfigured including but not limited to adding and removing information sources and sinks. Furthermore, we give some insights about current status of mobile privacy protection and prevention in app markets based upon our analysis
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