Estimating Software Obfuscation Potency with Artificial Neural Networks

被引：7

作者：

Canavese, Daniele ^{[1
]}

Regano, Leonardo ^{[1
]}

Basile, Cataldo ^{[1
]}

Viticchie, Alessio ^{[1
]}

机构：

[1] Politecn Torino, Turin, Italy

来源：

SECURITY AND TRUST MANAGEMENT (STM 2017) | 2017年 / 10547卷

关键词：

Software protection; Code obfuscation; Potency; Neural networks; SOURCE CODE OBFUSCATION;

D O I：

10.1007/978-3-319-68063-7_13

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents an approach to estimate the potency of obfuscation techniques. Our approach uses neural networks to accurately predict the value of complexity metrics - which are used to compute the potency - after an obfuscation transformation is applied to a code region. This work is the first step towards a decision support to optimally protect software applications.

引用

页码：193 / 202

页数：10

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