赵鹏，江苏师范大学教授、副校长。主要从事可靠性统计和网络可靠性等领域的研究工作。承担多项国家级项目。担任期刊Commun. Stat.副主编（AE）、《应用概率统计》《数理统计与管理》《Journal of Reliability Science and Engineering》编委。曾获江苏省“双创人才”、江苏省数学成就奖、江苏省教学成果一等奖（第一完成人）等。担任中国数学会理事、概率统计分会常务理事等。

  报告摘要：Data breaches cause significant financial losses every year and have become a major concern for businesses. To mitigate the damage caused by a data breach, a key concept of the data breach lifecycle that involves three components, the occurrence of a breach, the time to detect the breach, and the time to report the breach, has to be well understood. In this talk, we initialize the statistical modeling of the data breach lifecycle via a self-exciting marked point process. The proposed model accommodates the heterogeneity between hacking and non-hacking events, and the dependence between two marks - the time to detect the breach and the time to report the breach - is modeled via a copula approach. The missing and censoring mechanisms are taken into account in the modeling process as well. Empirical studies show that the proposed approach has satisfactory fitting and predictive performance.