3,954 research outputs found
A Dual-Engine for Early Analysis of Critical Systems
This paper presents a framework for modeling, simulating, and checking
properties of critical systems based on the Alloy language -- a declarative,
first-order, relational logic with a built-in transitive closure operator. The
paper introduces a new dual-analysis engine that is capable of providing both
counterexamples and proofs. Counterexamples are found fully automatically using
an SMT solver, which provides a better support for numerical expressions than
the existing Alloy Analyzer. Proofs, however, cannot always be found
automatically since the Alloy language is undecidable. Our engine offers an
economical approach by first trying to prove properties using a
fully-automatic, SMT-based analysis, and switches to an interactive theorem
prover only if the first attempt fails. This paper also reports on applying our
framework to Microsoft's COM standard and the mark-and-sweep garbage collection
algorithm.Comment: Workshop on Dependable Software for Critical Infrastructures (DSCI),
Berlin 201
KeyForge: Mitigating Email Breaches with Forward-Forgeable Signatures
Email breaches are commonplace, and they expose a wealth of personal,
business, and political data that may have devastating consequences. The
current email system allows any attacker who gains access to your email to
prove the authenticity of the stolen messages to third parties -- a property
arising from a necessary anti-spam / anti-spoofing protocol called DKIM. This
exacerbates the problem of email breaches by greatly increasing the potential
for attackers to damage the users' reputation, blackmail them, or sell the
stolen information to third parties.
In this paper, we introduce "non-attributable email", which guarantees that a
wide class of adversaries are unable to convince any third party of the
authenticity of stolen emails. We formally define non-attributability, and
present two practical system proposals -- KeyForge and TimeForge -- that
provably achieve non-attributability while maintaining the important protection
against spam and spoofing that is currently provided by DKIM. Moreover, we
implement KeyForge and demonstrate that that scheme is practical, achieving
competitive verification and signing speed while also requiring 42% less
bandwidth per email than RSA2048
Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild
In this paper, we seek to better understand Android obfuscation and depict a
holistic view of the usage of obfuscation through a large-scale investigation
in the wild. In particular, we focus on four popular obfuscation approaches:
identifier renaming, string encryption, Java reflection, and packing. To obtain
the meaningful statistical results, we designed efficient and lightweight
detection models for each obfuscation technique and applied them to our massive
APK datasets (collected from Google Play, multiple third-party markets, and
malware databases). We have learned several interesting facts from the result.
For example, malware authors use string encryption more frequently, and more
apps on third-party markets than Google Play are packed. We are also interested
in the explanation of each finding. Therefore we carry out in-depth code
analysis on some Android apps after sampling. We believe our study will help
developers select the most suitable obfuscation approach, and in the meantime
help researchers improve code analysis systems in the right direction
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
Android Malware Characterization using Metadata and Machine Learning Techniques
Android Malware has emerged as a consequence of the increasing popularity of
smartphones and tablets. While most previous work focuses on inherent
characteristics of Android apps to detect malware, this study analyses indirect
features and meta-data to identify patterns in malware applications. Our
experiments show that: (1) the permissions used by an application offer only
moderate performance results; (2) other features publicly available at Android
Markets are more relevant in detecting malware, such as the application
developer and certificate issuer, and (3) compact and efficient classifiers can
be constructed for the early detection of malware applications prior to code
inspection or sandboxing.Comment: 4 figures, 2 tables and 8 page
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