2,008 research outputs found
Evolution and Detection of Polymorphic and Metamorphic Malwares: A Survey
Malwares are big threat to digital world and evolving with high complexity.
It can penetrate networks, steal confidential information from computers, bring
down servers and can cripple infrastructures etc. To combat the threat/attacks
from the malwares, anti- malwares have been developed. The existing
anti-malwares are mostly based on the assumption that the malware structure
does not changes appreciably. But the recent advancement in second generation
malwares can create variants and hence posed a challenge to anti-malwares
developers. To combat the threat/attacks from the second generation malwares
with low false alarm we present our survey on malwares and its detection
techniques.Comment: 5 Page
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
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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