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Document type:
Konferenzbeitrag 
Contribution type:
Elektronisches Dokument 
Author(s):
Banescu, Sebastian and Collberg, Christian and Pretschner, Alexander 
Title:
Predicting the Resilience of Obfuscated Code Against Symbolic Execution Attacks via Machine Learning 
Abstract:
Software obfuscation transforms code such that it is more difficult to reverse engineer. However, it is known that given enough resources, an attacker will successfully reverse engineer an obfuscated program. Therefore, an open challenge for software obfuscation is estimating the time an obfuscated program is able to withstand a given reverse engineering attack. This paper proposes a general framework for choosing the most relevant software features to estimate the effort of auto...    »
 
Dewey Decimal Classification:
000 Informatik, Wissen, Systeme 
Book / Congress title:
To appear in Usenix Security, 2017 
Year:
2017 
Reviewed:
ja