Are FBI's Android data-sharing apps hacker-proof?
The bureau intends to tap GMU scientists for security tests involving cloud-based computing.
The FBI plans to tap George Mason University scientists to perform tests on the law enforcement agency's Android mobile applications to see if they are hacker-proof, a notice of intent reveals.
The bureau will match funding provided by the military venture capital arm, Defense Advanced Research Projects Agency, to help tailor testing systems to the FBI's specific needs.
With DARPA money, researchers in the GMU computer science department have been working on a systematic approach to carrying out fuzzing attacks – the feeding of unexpected data into a computer program as a form of brute-force exploitation. Last year, Regina Dugan, then-director of DARPA, announced that the agency was interested in supporting offensive cyber capabilities.
Fuzz testing apps so far have lacked sophisticated or guided techniques, according to a paper outlining the DARPA-funded research. The scientists have been seeking to develop a “scalable approach for intelligent fuzz testing of Android applications” with the help of cloud computing. “The framework uses numerous heuristics and software analysis techniques to intelligently guide the generation of test cases aiming to boost the likelihood of discovering vulnerabilities,” the paper adds.
The team chose to focus on the Android operating system because it has one of the most widely used and vulnerable app markets. Also, because Android is an open-source platform, it is ideal for experimentation in the laboratory, the scientists said.
The goal is to create tools that test vulnerabilities in mobile apps such as those integrated with the Law Enforcement National Data Exchange and National Crime Information Center, both data-sharing tools that grant access to criminal justice records.
Under the terms of the prospective contract, the principal investigator, assistants, and students involved in the research have to be American citizens, the notice of intent states.
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