Binary Code

Binary code analysis focuses on understanding and interpreting the machine-readable instructions of compiled programs, aiming to extract semantic meaning and facilitate tasks like reverse engineering, malware detection, and software optimization. Current research emphasizes leveraging machine learning, particularly large language models (LLMs) and graph neural networks (GNNs), to improve code understanding, often incorporating techniques like contrastive learning and hierarchical attention mechanisms to enhance representation learning and transferability across different architectures and optimization levels. These advancements are significantly impacting software security, vulnerability research, and the development of more efficient and robust software analysis tools.