No abstract

No abstract

Secure multilinear maps (mmaps) have been shown to have remarkable applications in cryptography, such as multi-input functional encryption (MIFE) and program obfuscation. To date, there has been little evaluation of the performance of these applications. In this paper we initiate a systematic study of mmap-based constructions. We build a general framework, called 5Gen, to experiment with these applications. At the top layer we develop a compiler that takes in a high-level program and produces an optimized matrix branching program needed for the applications we consider. Next, we optimize and experiment with several MIFE and obfuscation constructions and evaluate their performance. The 5Gen framework is modular and can easily accommodate new mmap constructions as well as new MIFE and obfuscation constructions, as well as being an open-source tool that can be used by other research groups to experiment with a variety of mmap-based constructions.1 The name 5Gen comes from the fact that multilinear maps can be considered the "fifth generation" of cryptography, where the prior four are: symmetric key, public key, bilinear maps, and fully homomorphic encryption.

Android's popularity has given rise to myriad application analysis techniques to improve the security and robustness of mobile applications, motivated by the evolving adversarial landscape. These techniques have focused on identifying undesirable behaviors in individual applications, either due to malicious intent or programmer error. We present a collection of tools that provide a static information flow analysis across a set of applications, showing a holistic view of all the applications destined for a particular device. The techniques we present include a static binary single-app analysis, a security lint tool to mitigate the limits of static binary analysis, a multi-app information flow analysis, and an evaluation engine to detect information flows that violate specified security policies.We show that our single-app analysis is comparable with the leading approaches on the DroidBench benchmark suite; we present a brief listing of lint-like heuristics used to show the limits of the single-app analysis in the context of an application; we present a multi-app analysis, and demonstrate information flows that cannot be detected by single-app analyses; and we present a policy evaluation engine to automatically detect violations in collections of Android apps. General TermsSecurity