Blockchain-oriented approach for detecting cyber-attack transactions

With the high-speed development of decentralized applications, account-based blockchain platforms have become a hotbed of various financial scams and hacks due to their anonymity and high financial value. Financial security has become a top priority with the sustainable development of blockchain-based platforms because of an increasing number of cyber attacks, which have resulted in a huge loss of crypto assets in recent years. Therefore, it is imperative to study the real-time detection of cyber attacks to facilitate effective supervision and regulation. To this end, this paper proposes the weighted and extended isolation forest algorithms and designs a novel framework for the real-time detection of cyber-attack transactions by thoroughly studying and summarizing real-world examples. Furthermore, this study develops a new detection approach for locating the compromised address of a cyber attack to resolve the data scarcity of hack addresses and reduce time consumption. Moreover, three experiments are carried out not only to apply on different types of cyber attacks but also to compare the proposed approach with the widely used existing methods. The results demonstrate the high efficiency and generality of the proposed approach. Finally, the lower time consumption and robustness of our method were validated through additional experiments. In conclusion, the proposed blockchain-oriented approach in this study can handle real-time detection of cyber attacks and has significant scope for applications.