# Database Intrusion Detection Systems (DIDs): Insider Threat Detection via Behavioural-based Anomaly Detection Systems -- A Brief Survey of Concepts and Approaches

arXiv: https://arxiv.org/abs/2011.02308 · HTML: https://mlsanity.com/paper/2011.02308/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [Leveraging large language models for SQL behavior-based database intrusion detection](https://mlsanity.com/paper/2508.05690/) (2025)

## Abstract (arXiv)

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).