Abstract
As social science researchers increasingly use online mechanisms to recruit participants and collect data, they must also defend against the growing threat of fraudulent submissions from autonomous bots and bad-faith human respondents. This paper describes such threats and outlines conditions that make some studies particularly vulnerable. It also provides explicit guidance for researchers by introducing a typology of 30 protective countermeasures designed to deter, prevent, track, and detect fraudulent responses.