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Titlebook: Software Similarity and Classification; Silvio Cesare,Yang Xiang Book 2012 The Author(s) 2012 Code Clone Detection.Malware Classification.

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发表于 2025-3-21 19:06:56 | 显示全部楼层 |阅读模式
书目名称Software Similarity and Classification
编辑Silvio Cesare,Yang Xiang
视频video
概述The first book to construct a theory to describe the problems in software similarity and classification.Includes supplementary material:
丛书名称SpringerBriefs in Computer Science
图书封面Titlebook: Software Similarity and Classification;  Silvio Cesare,Yang Xiang Book 2012 The Author(s) 2012 Code Clone Detection.Malware Classification.
描述Software similarity and classification is an emerging topic with wide applications. It is applicable to the areas of malware detection, software theft detection, plagiarism detection, and software clone detection. Extracting program features, processing those features into suitable representations, and constructing distance metrics to define similarity and dissimilarity are the key methods to identify software variants, clones, derivatives, and classes of software. Software Similarity and Classification reviews the literature of those core concepts, in addition to relevant literature in each application and demonstrates that considering these applied problems as a similarity and classification problem enables techniques to be shared between areas. Additionally, the authors present in-depth case studies using the software similarity and classification techniques developed throughout the book.
出版日期Book 2012
关键词Code Clone Detection; Malware Classification; Plagiarism Detection; Software Classification; Software Si
版次1
doihttps://doi.org/10.1007/978-1-4471-2909-7
isbn_softcover978-1-4471-2908-0
isbn_ebook978-1-4471-2909-7Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s) 2012
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发表于 2025-3-21 20:40:25 | 显示全部楼层
Introduction,tware theft detection, plagiarism detection and code clone detection. The motivations for these applications are examined and an underlying theory is formalized. This theory is based on extracting signatures from programs, known as birthmarks, that are amenable to approximate matching that tells us
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Dynamic Analysis,d in this chapter. It is an alternative approach to static analysis that can be used for birthmark construction. Dynamic analysis concerns itself with analysing a running program. The program being run is typically isolated in an environment which allows its behaviour to be inspected. Typical behavi
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Feature Extraction,tations and birthmarks to be useful. Furthermore, mathematical representations may be embedded in other mathematical types to make birthmarks more amenable to similarity comparisons and for use in classification algorithms. Another approach is to represent features using kernels. This allows for the
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Software Similarity Searching and Classification,r class. This chapter examines how we transform the pair-wise similarity problem into a similarity search problem over a database. Moreover, we examine statistical classification of birthmarks to identify the class of software it belongs to.
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