Profiling cyber attackers by classification techniques; a case study on Russian hackers - Ehiorobo, Eghe (Cybersecurity in the age of smart societies, 2023)
Cyber-attacks have become increasingly common in recent years all over the world. In particular, the ongoing unfortunate events between Russia and Ukraine have been aided using technology. The Russians have used various types of attacks for various reasons, such as reconnaissance to gather information about Ukraine's critical systems. It is critical to be able to profile these types of attacks for identification and other strategies to prevent such attacks in the future. Data mining techniques can be used to profile hackers by nation states, law enforcement agencies, and organizations alike. Profiling hackers can assist in better preparing for and responding to cyber-attacks. The goal of this study is to use data mining techniques to profile Russian hackers. Another important aspect of this study is the dataset that will be used, OSINT. The open-source dataset was chosen because it is free, suitable for research, and widely available. Different classification algorithms will be used to train the proposed predictors, and the most reliable and accurate model will be chosen. This study emphasizes the importance of better understanding well known Russian hacker groups, which could lead to better preparation and handling of cyber incidents involving such threat actors. Nation-state governments, researchers, and law enforcement agencies can use the developed model in conjunction with other techniques to quickly identify attacks from Russia APT groups, recommend controls, and develop a detailed strategy for countermeasures against such attacks, which will improve data security and privacy.