With the development of information technology, back translation plagiarism, such as through the use of translation tools, becomes increasingly complex and covert, posing higher requirements for plagiarism detection methods. For this reason, a plagiarism detection method based on prompt engineering is proposed. This method guides large language model (LLM) to pay attention to potential similarities in sentence texts at the semantic level by designing prompt words, which can effectively identify highly semantically similar content. Firstly, the existing plagiarism detection technologies and the application of prompt engineering are reviewed. Based on this, a backtracking plagiarism behavior detection process based on prompt engineering is designed. Secondly, a prompt template is designed to propose a plagiarism detection index based on sentence compression ratio by merging and reducing the pairs of sentences to be detected. Finally, experiments demonstrate that the plagiarism detection method based on prompt engineering has significant advantages over traditional methods in detecting back translation plagiarism behavior.