Abstract: Cheating damages the integrity of a testing program and can cause testing organizations significant losses. Security breaches can arise from individuals memorizing and sharing items, the concerted efforts of a test preparation company to harvest items and teach them to their customers, and answer copying or collusion among examinees during a testing event. Without proper detection, these types of cheating could remain undetected until their presence becomes significant enough to threaten test-score validity. Therefore, effectively identifying cheaters is a popular topic in the measurement field. Many detection techniques have been developed to flag aberrant testing behaviors. Some of them are specifically designed for the paper-and-pencil test and may not be feasible for poolbased computer-administered tests. Some of them are based on complicated mathematical models and extensive ad-hoc data analyses and thus cannot be practically fitted into many testing programs’ operational schedules. This session covers several methods that could help detect aberrant testing behavior in the operational setting. Findings in this session may provide more insights into data forensics research. They may also inspire practitioners to use more practical, less time-consumingly computed statistics in their operational work to improve test security.