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Researchers Have Found a Way To Root Out Identity Thieves By Analyzing Their Mouse Movements With AI (qz.com)
An anonymous reader shares an article: In the study, published recently in PLoS One, the researchers quizzed 40 respondents about their personal details. Half of the respondents were asked to answer the questions truthfully, but the other half were given details about fake identities they had to memorize and use in the quiz.
The computer quiz kept track of the movement of each respondent's mouse as they answered the questions, and noted how the fakes differed from the truth-tellers when they moved the cursor from the bottom of the screen to the answers at the top. The quiz consisted of 12 questions like, "Do you live in Padua?" and "Are you Italian?" That covered details an identity thief could easily remember and answer, but then the quiz threw them a curve ball. "What is your zodiac sign," it asked in the second series of 12 questions, which were designed to be easy for the genuine respondents, but more difficult for the fakers to work out. After the researchers took the mouse-movement data collected from the quizzes and trained a machine-learning algorithm to analyze it, they found that was indeed the case. It was able to discern the fake responses from the real ones 95% of the time.
By itself, this study just shows that a machine learning algorithm can compute a statistical average (regarding mouse movements) that classifies a specific set of 40 people into two groups.
If the same statistical average also classifies other groups of people accurately, then you can make real claims about separating truth-tellers and liars.
See this good explanation of pattern classification and its uses and misuses.
Actually, that is close to how a lot of drug research is done. 1) Create new drug, 2) throw at a lot of cultures to see what effect it has on any of them, 3) follow up where an effect is observed, 4) market. For example, Rogaine was originally developed to treat ulcers and hypertension, and Viagra to treat hypertension and mild heart problems, and look where they went.