Enhancing Code Obfuscation Techniques: Exploring the Impact of Artificial Intelligence on Malware Detection

被引:0
|
作者
Catalano, Christian [1 ]
Specchia, Giorgia [2 ]
Totaro, Nicol O. G. [2 ]
机构
[1] Univ Salento, Dept Innovat Engn, Lecce, Italy
[2] Univ Salento, Ctr Appl Math & Phys Ind CAMPI, Lecce, Italy
关键词
Metamorphic Generator; Malware Obfuscation; Malware Detection; Artificial Intelligence; Cybersecurity;
D O I
10.1007/978-3-031-49269-3_8
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Code obfuscation techniques serve to obscure proprietary code, and there are several types. Various tools, such as reverse engineering, are used to reconstruct obfuscated code. To make the analysis and decoding of obfuscated code more difficult, obfuscation techniques can be combined in cascades. Artificial Intelligence (AI) can be used to recombine old codes with each other and make it more difficult to decrypt them. In this paper, the focus is precisely on the increased complexity of the process of reconstructing proprietary code if it is generated with the aid of AI, and consequently on the increasing difficulty for antiviruses in detecting this new type of malware.
引用
收藏
页码:80 / 88
页数:9
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