NDLI: Static Analysis of Malicious Java Applets

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Content Provider	ACM Digital Library
Author	Di Troia, Fabio Stamp, Mark Austin, Thomas H. Ganesh, Nikitha Corrado, Visaggio Aaron
Abstract	In this research we consider the problem of detecting malicious Java applets, based on static analysis. Dynamic analysis can be more informative, since it is immune to many common obfuscation techniques, while static analysis is often more efficient, since it does not require code execution or emulation. Consequently, static analysis is generally preferred, provided the results are comparable to those obtained using dynamic analysis. We conduct experiments using three techniques that have been employed in previous studies of metamorphic malware. We show that our static approach can detect malicious Java applets with greater accuracy than previously published research that relied on dynamic analysis.
Starting Page	58
Ending Page	63
Page Count	6
File Format	PDF
ISBN	9781450340779
DOI	10.1145/2875475.2875477
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-03-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Java Hidden markov models Applets Malware Profile hidden markov models
Content Type	Text
Resource Type	Article

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Static Analysis of Malicious Java Applets