Comparing Signature Detection of Convolutional Neural Network in Low-Level and Large Language Model in High-Level Programming Language

Can GPT models, specifically those designed for natural language processing, outperform convolutional neural networks (CNN) when it comes to signature detection? Signature detection is one of the most important tasks involved in deep learning. It is used to identify objects and patterns in data. On the other hand, the extremely rapid development of chat bots like chat GPT creates the potential for their use in malware detection with preprocessed code. In this study, the authors compare the performance of signature detection using low-level on the ResNet50 network and high-level programming languages on the GPT 2 model. The results show that signature detection in high-level languages perform better than ResNet50 in low-level languages. This suggests that GPT 2 and general chat bot related models are more suited for signature detection tasks.