2,058 research outputs found
Optimizing Abstract Abstract Machines
The technique of abstracting abstract machines (AAM) provides a systematic
approach for deriving computable approximations of evaluators that are easily
proved sound. This article contributes a complementary step-by-step process for
subsequently going from a naive analyzer derived under the AAM approach, to an
efficient and correct implementation. The end result of the process is a two to
three order-of-magnitude improvement over the systematically derived analyzer,
making it competitive with hand-optimized implementations that compute
fundamentally less precise results.Comment: Proceedings of the International Conference on Functional Programming
2013 (ICFP 2013). Boston, Massachusetts. September, 201
Secure multi-party computation for analytics deployed as a lightweight web application
We describe the definition, design, implementation, and deployment of a secure multi-party computation protocol and web application. The protocol and application allow groups of cooperating parties with minimal expertise and no specialized resources to compute basic statistical analytics on their collective data sets without revealing the contributions of individual participants. The application was developed specifically to support a Boston Women’s Workforce Council (BWWC) study of wage disparities within employer organizations in the Greater Boston Area. The application has been deployed successfully to support two data collection sessions (in 2015 and in 2016) to obtain data pertaining to compensation levels across genders and demographics. Our experience provides insights into the particular security and usability requirements (and tradeoffs) a successful “MPC-as-a-service” platform design and implementation must negotiate.We would like to acknowledge all the members of the Boston Women’s Workforce Council, and to thank in particular MaryRose Mazzola, Christina M. Knowles, and Katie A. Johnston, who led the efforts to organize participants and deploy the protocol as part of the 100% Talent: The Boston Women’s Compact [31], [32] data collections. We also thank the Boston University Initiative on Cities (IOC), and in particular Executive Director Katherine Lusk, who brought this potential application of secure multi-party computation to our attention. The BWWC, the IOC, and several sponsors contributed funding to complete this work. Support was also provided in part by Smart-city Cloud-based Open Platform and Ecosystem (SCOPE), an NSF Division of Industrial Innovation and Partnerships PFI:BIC project under award #1430145, and by Modular Approach to Cloud Security (MACS), an NSF CISE CNS SaTC Frontier project under award #1414119
Do Android Taint Analysis Tools Keep Their Promises?
In recent years, researchers have developed a number of tools to conduct
taint analysis of Android applications. While all the respective papers aim at
providing a thorough empirical evaluation, comparability is hindered by varying
or unclear evaluation targets. Sometimes, the apps used for evaluation are not
precisely described. In other cases, authors use an established benchmark but
cover it only partially. In yet other cases, the evaluations differ in terms of
the data leaks searched for, or lack a ground truth to compare against. All
those limitations make it impossible to truly compare the tools based on those
published evaluations.
We thus present ReproDroid, a framework allowing the accurate comparison of
Android taint analysis tools. ReproDroid supports researchers in inferring the
ground truth for data leaks in apps, in automatically applying tools to
benchmarks, and in evaluating the obtained results. We use ReproDroid to
comparatively evaluate on equal grounds the six prominent taint analysis tools
Amandroid, DIALDroid, DidFail, DroidSafe, FlowDroid and IccTA. The results are
largely positive although four tools violate some promises concerning features
and accuracy. Finally, we contribute to the area of unbiased benchmarking with
a new and improved version of the open test suite DroidBench
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