The study presents multivariate sequential monitoring procedures for examining test-taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test-taking behavior. The study in particular proposes three schemes to track different indicators of a test-taking mode--the observable manifest variables, latent trait variables, and measurement likelihood. For each procedure, sequential sampling strategies are presented to implement online monitoring. Numerical experimentation based on simulated data suggests that the proposed procedures demonstrate adequate performance. The procedures identified examinees with aberrant behaviors with high detection power and timeliness, while maintaining error rates reasonably small. Experimental application to real data also suggested that the procedures have practical relevance to real assessments. Based on the observations from the experiential analysis, the study discusses implications and guidelines for practical use.