摘要：E-mail has become the main carrier of spreading malicious software and been widely used for phishing, even high-level persistent threats. The e-mail accounts with high social reputation are primary targets to be attacked and utilized by attackers, suffering a lot of probing attacks for a long time. In this paper, in order to understand the probing pattern of the e-mail account attacks, we analyse the log of email account probing captured in the campus network based on graph mining. By analysing characteristics of the dataset in different dimensions, we find a kind of e-mail account probing attack and give it a new definition. Based on the analysis results, its probing pattern is figured out. From the point of probing groups and individuals, we find definitely opposite characteristics of the attack. Owing to the probing pattern and its characteristics, attacks can escape from the detection of security devices, which has a harmful effect on e-mail users and administrators. The analysis results of this paper provide support for the detection and defence of such distributed attacks.
