Summary of From Clicks to Security: Investigating Continuous Authentication Via Mouse Dynamics, by Rushit Dave et al.
From Clicks to Security: Investigating Continuous Authentication via Mouse Dynamics
by Rushit Dave, Marcho Handoko, Ali Rashid, Cole Schoenbauer
First submitted to arxiv on: 6 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper explores the use of mouse movement dynamics as a continuous authentication method in computer security. The authors analyze user mouse movements in two gaming scenarios, “Team Fortress” and Poly Bridge, to identify behavioral patterns. They employ various machine learning models to assess their effectiveness in capturing these patterns. The study reveals that mouse movement dynamics can be a reliable indicator for user authentication. The results show that the diverse machine learning models perform well in user verification, outperforming previous methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how people use their mice while playing different games. They want to know if this behavior can help keep computers safe from bad guys. To do this, they looked at two types of games and saw what the players did with their mice. Then, they used special computer programs called machine learning models to see if these programs could tell who was playing based on how they moved their mice. It turns out that the way people move their mice can be a good way to figure out who’s using the computer. |
Keywords
» Artificial intelligence » Machine learning
