Intellicheck – Plagiarism Detector Using HMM, BERT and Abstract Syntax Tree

Intellicheck – Plagiarism Detector Using HMM, BERT and Abstract Syntax Tree

Authors- SVS Satish, S D Anirudh, P Chandu, K Suhaas Varma, Assistant Professor P.Jyothi

Abstract-In the modern era of widespread access to information and digital resources, plagiarism detection has become increasingly essential for preserving academic integrity and protecting intellectual property. This research focuses on the design and development of a dual-functional plagiarism detection system capable of analyzing both text and source code submissions. The text-based detection module employs a Hidden Markov Model (HMM) to evaluate textual similarity and utilizes a BERT model to understand and compare the semantic meaning of the content. The source code module leverages Abstract Syntax Trees (AST) to identify structural similarities in programming code, offering precise detection of plagiarized logic and patterns. The proposed system bridges the gap between surface-level content analysis and deeper contextual and structural understanding, making it a robust and comprehensive tool for a wide array of applications. This paper also addresses implementation challenges, evaluates system performance metrics such as precision and recall, and suggests potential future enhancements, including the incorporation of multilingual support and the expansion to more programming languages. By integrating advanced technologies, this system provides a reliable solution for detecting plagiarism in academic, research, and software development environments, ensuring fairness and originality.

DOI: /10.61463/ijset.vol.13.issue2.196