1,161 research outputs found
Using HTML5 to Prevent Detection of Drive-by-Download Web Malware
The web is experiencing an explosive growth in the last years. New
technologies are introduced at a very fast-pace with the aim of narrowing the
gap between web-based applications and traditional desktop applications. The
results are web applications that look and feel almost like desktop
applications while retaining the advantages of being originated from the web.
However, these advancements come at a price. The same technologies used to
build responsive, pleasant and fully-featured web applications, can also be
used to write web malware able to escape detection systems. In this article we
present new obfuscation techniques, based on some of the features of the
upcoming HTML5 standard, which can be used to deceive malware detection
systems. The proposed techniques have been experimented on a reference set of
obfuscated malware. Our results show that the malware rewritten using our
obfuscation techniques go undetected while being analyzed by a large number of
detection systems. The same detection systems were able to correctly identify
the same malware in its original unobfuscated form. We also provide some hints
about how the existing malware detection systems can be modified in order to
cope with these new techniques.Comment: This is the pre-peer reviewed version of the article: \emph{Using
HTML5 to Prevent Detection of Drive-by-Download Web Malware}, which has been
published in final form at \url{http://dx.doi.org/10.1002/sec.1077}. This
article may be used for non-commercial purposes in accordance with Wiley
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Desktop security as a three-dimensional problem
In this paper we argue against viewing computer desktop security solely as a technical issue. Instead, we propose a perspective that combines three related dimensions: technical infrastructure, usability and user engagement. In this light, we suggest that a viable approach to desktop security should embrace these three key dimensions of the end-user context. An example desktop application is described that has been engineered to embody these dimensions in support of the desktop user
AndroShield:automated Android applications vulnerability detection, a hybrid static and dynamic analysis approach
The security of mobile applications has become a major research field which is associated with a lot of challenges. The high rate of developing mobile applications has resulted in less secure applications. This is due to what is called the “rush to release” as defined by Ponemon Institute. Security testing—which is considered one of the main phases of the development life cycle—is either not performed or given minimal time; hence, there is a need for security testing automation. One of the techniques used is Automated Vulnerability Detection. Vulnerability detection is one of the security tests that aims at pinpointing potential security leaks. Fixing those leaks results in protecting smart-phones and tablet mobile device users against attacks. This paper focuses on building a hybrid approach of static and dynamic analysis for detecting the vulnerabilities of Android applications. This approach is capsuled in a usable platform (web application) to make it easy to use for both public users and professional developers. Static analysis, on one hand, performs code analysis. It does not require running the application to detect vulnerabilities. Dynamic analysis, on the other hand, detects the vulnerabilities that are dependent on the run-time behaviour of the application and cannot be detected using static analysis. The model is evaluated against different applications with different security vulnerabilities. Compared with other detection platforms, our model detects information leaks as well as insecure network requests alongside other commonly detected flaws that harm users’ privacy. The code is available through a GitHub repository for public contribution
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