Abstract
The escalation of code plagiarism in computer science education has necessitated the development of more sophisticated detection methods, particularly for binary files which pose a unique challenge. This study introduces a novel approach to plagiarism detection through binary decomposition, which decompiles binary files back into high-level code to reveal similarities that may be hidden at the binary level. The methodology is crucial for scenarios where students submit compiled programs, enabling the application of traditional code similarity analysis methods to detect instances of plagiarism. Statistical data on code similarity among student submissions in a C programming course are presented, highlighting the urgent need for robust detection strategies. This paper explores the ethical implications of plagiarism, the technical challenges of binary file analysis, and the potential for applying this technique across various programming languages and educational contexts.