Crypto-jacking Threat Detection Based on Blockchain Framework and Deception Techniques

Speaker: Haissam Badih

Recent advancements in malware necessitate a robust security solution, as traditional and hybrid malware detection approaches fall short of modern cyber-attack strategies. This paper introduces a novel method to detect malware targeting webcam protocols and addresses crypto-jacking threats within blockchain technology. Our approach enhances blockchain security by injecting a specialized application into each node, enabling the identification and protection of miners and nodes against crypto-jacking. The application monitors CPU usage to detect abnormal processes, utilizing a cuckoo process for further analysis without alerting the attacker, thereby preventing compromised miners from conducting transactions. This innovative method not only secures nodes but also contributes to creating a denylist of infected internet protocols and blockchain addresses, enhancing overall network safety. Tested against threat actors and regular users, our approach is an effective defense mechanism against malware, particularly crypto-jacking.