VulnSense: Efficient Vulnerability Detection in Ethereum Smart Contracts by Multimodal Learning with Graph Neural Network and Language Model

The advancement of software vulnerability detection tools has accelerated in recent years, yet the prevalence and severity of vulnerabilities continue to escalate, posing significant threats to computer security and information safety. To address this, numerous detection methodologies have been proposed, with machine learning-based approaches demonstrating notable promise. In this paper,...

Detecting malware on Android remains a major challenge because malicious apps use sophisticated evasion techniques. This study presents RAX-ClaMal, a novel approach leveraging dynamic analysis of RAX (Register a Extended) register values for Android malware detection. By extracting and examining the RAX register in the data sections from Dalvik Executable...