基于自注意引导的多表示融合的功能级代码混淆检测

IF 0.6 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zhenzhou Tian, Ruikang He, Hongliang Zhao, Lingwei Chen
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Function-Level Code Obfuscation Detection Through Self-Attention Guided Multi-Representation Fusion
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来源期刊
CiteScore
1.90
自引率
11.10%
发文量
71
审稿时长
16 months
期刊介绍: The International Journal of Software Engineering and Knowledge Engineering is intended to serve as a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of software engineering and knowledge engineering. Three types of papers will be published: Research papers reporting original research results Technology trend surveys reviewing an area of research in software engineering and knowledge engineering Survey articles surveying a broad area in software engineering and knowledge engineering In addition, tool reviews (no more than three manuscript pages) and book reviews (no more than two manuscript pages) are also welcome. A central theme of this journal is the interplay between software engineering and knowledge engineering: how knowledge engineering methods can be applied to software engineering, and vice versa. The journal publishes papers in the areas of software engineering methods and practices, object-oriented systems, rapid prototyping, software reuse, cleanroom software engineering, stepwise refinement/enhancement, formal methods of specification, ambiguity in software development, impact of CASE on software development life cycle, knowledge engineering methods and practices, logic programming, expert systems, knowledge-based systems, distributed knowledge-based systems, deductive database systems, knowledge representations, knowledge-based systems in language translation & processing, software and knowledge-ware maintenance, reverse engineering in software design, and applications in various domains of interest.
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