Abstract

Source code transformation is a way in which source code of a program is transformed by observing any operation for generating another or nearly the same program. This is mostly performed in situations of piracy where the pirates want the ownership of the software program. Various approaches are being practiced for source code transformation and code obfuscation. Researchers tried to overcome the issue of modifying the source code and prevent it from the people who want to change the source code. Among the existing approaches, software birthmark was one of the approaches developed with the aim to detect software piracy that exists in the software. Various features are extracted from software which are collectively termed as “software birthmark.” Based on these extracted features, the piracy that exists in the software can be detected. Birthmarks are considered to insist on the source code and executable of certain programming languages. The usability of software birthmark can protect software by any modification or changes and ultimately preserve the ownership of software. The proposed study has used machine learning algorithms for classification of the usability of existing software birthmarks in terms of source code transformation. The K-nearest neighbors (K-NN) algorithm was used for classification of the software birthmarks. For cross-validation, the algorithms of decision rules, decomposition tree, and LTF-C were used. The experimental results show the effectiveness of the proposed research.

Highlights

  • Source code transformation is performed in a manner in which the source code of a program is transmuted by spotting any operation for creating an alternative or nearly same program. is is mostly performed in situation of piracy where the pirates want the ownership of the software program

  • E K-nearest neighbors algorithm was used for classification of the software birthmarks

  • The researchers have devised different solutions. e proposed study has used machine learning algorithms for classification of the software birthmarks usability in terms of source code transformation. e K-nearest neighbors algorithm was used for classification of the software birthmarks

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Summary

Introduction

Source code transformation is performed in a manner in which the source code of a program is transmuted by spotting any operation for creating an alternative or nearly same program. is is mostly performed in situation of piracy where the pirates want the ownership of the software program. E similar concerns are existing in the software fingerprints To overawe these limitations, the idea of birthmark was presented and is broadly acknowledged and known approach for preventing source code transformation and piracy of software. More features of a software birthmark can eventually present the robustness and effectiveness which will further show the precise detection of transformations or theft made in the software or program. Ese approaches talk about various applications of software birthmark including source code transformation, code obfuscations, software theft, piracy, and many others. E proposed study endeavored to use machine learning algorithms for classification of the usability of existing software birthmarks in terms of source code transformation.

Related Work
Research Methodology
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Conclusion

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