论文标题
数据库入侵检测系统（DIDS）：通过基于行为的异常检测系统进行内部威胁检测 - 简要调查概念和方法
Database Intrusion Detection Systems (DIDs): Insider Threat Detection via Behavioural-based Anomaly Detection Systems -- A Brief Survey of Concepts and Approaches
论文作者
论文摘要
数据安全和隐私问题之一是内部威胁，系统的合法用户滥用了其享有的访问权限。内部人士对数据安全性的威胁意味着内部人会窃取或泄漏敏感的个人信息。数据库入侵检测系统，特别是基于行为的数据库入侵检测系统，已显示在检测内部攻击方面。本文在检测内部人士威胁的背景下介绍了数据库入侵检测系统的背景概念，并研究了文献中有关内部人员对数据库管理系统（DBMS）检测恶意访问的现有方法。
One of the data security and privacy concerns is of insider threats, where legitimate users of the system abuse the access privileges they hold. The insider threat to data security means that an insider steals or leaks sensitive personal information. Database Intrusion detection systems, specifically behavioural-based database intrusion detection systems, have been shown effective in detecting insider attacks. This paper presents background concepts on database intrusion detection systems in the context of detecting insider threats and examines existing approaches in the literature on detecting malicious accesses by an insider to Database Management Systems (DBMS).
