DocCompare: An Approach to Prevent the Problem of Character Injection in Document Similarity Algorithm

Anupama Namburu, Akhil Surendran, S Vijay Balaji, Senthilkumar Mohan () and Celestine Iwendi
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Anupama Namburu: School of Computer Science and Engineering, VIT-AP University, Andhra Pradesh 522237, India
Akhil Surendran: School of Computer Science and Engineering, VIT-AP University, Andhra Pradesh 522237, India
S Vijay Balaji: School of Computer Science and Engineering, VIT-AP University, Andhra Pradesh 522237, India
Senthilkumar Mohan: School of Information Technology and Engineering, Vellore Institute of Technology, Vellore 632014, India
Celestine Iwendi: School of Creative Technologies, University of Bolton, A676 Deane Rd., Bolton BL3 5AB, UK

Mathematics, 2022, vol. 10, issue 22, 1-16

Abstract: There is a constant rise in the amount of data being copied or plagiarized because of the abundance of content and information freely available across the internet. Even though the systems try to check documents for the plagiarism, there have been trials to overcome these system checks. In this paper, the concept of character injection is used to trick plagiarism checker is presented. It is also showcased that how does the similarity check algorithms based on k-grams fail to detect the character injection. In order to eradicate the problem or error in similarity rates caused due to the problem of character injection, image processing based approach of multiple histogram projections are used. An application is developed to detect the character injection in the document and produce the accurate similarity rate. The results are shown with some test documents and the proposed method eliminates any kind of character injected in the document that tricks plagiarism. The proposed method has addressed the problem of character injection with image processing based changes in the existing methods of document-similarity check algorithms using k-grams. The proposed method can detect 100% injected character be it any alphabet of any language, The processing time for conversion, histogram projections and applying winnowing algorithm takes 1.2 sec per page on average when experimented on multiple types of document varying in size from 2 KB to 10 MB.

Keywords: plagiarism detection; character injection; image segmentation; word segmentation; histogram projection; document analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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