ChatGPT-driven machine learning code generation for android malware detection

Abstract Android is a widely used operating system, primarily found on mobile phones and tablets. Applications (commonly known as “apps”) for android can be easily installed from Google Play, third-party stores, or manually using android package kit (APK) files. Due to its growing popularity, android has attracted significant attention from malicious actors deploying various forms of malware. To address this challenge, artificial intelligence-based approaches are increasingly used to protect systems from cyber-attacks. This research paper focuses on the application of ChatGPT, a powerful large language model, in cybersecurity, specifically for malware detection. It evaluates ChatGPT’s potential as an innovative tool in fighting cyber threats, exploring the process of fine-tuning ChatGPT, its performance and its limitations in malware detection tasks. The objective is to reduce the effort and time required to generate artificial intelligence-based malware detection systems, simplifying their development process. This research shows how ChatGPT can be utilized to generate code for detecting malware in structured datasets with high accuracy. The focus is not on introducing any new algorithms but on allow individuals without programming expertise to create and apply these models effectively.