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CS298 Proposal

Authentication by Mouse Movements

Shivani Hashia (

Advisor: Dr. Chris Pollett(

Committee Members: Dr.Mark Stamp( Dr.Robert Chun (


Security systems help to protect machines or sensitive data from unauthorized users. The need for better and cheap security systems is growing with the growth in Internet. There are various techniques that can authenticate a user. One of these techniques is biometrics. In the project, we plan to use mouse movements as the biometric for user authentication. The mouse is used for verifying the authenticity of the user by validating the mouse movements of that person. There will be two modes of identification. First will be initial login where the user will be given a set of points on which he has to move the mouse. Based on the pattern of mouse movements on the screen for those random points, he will be authenticated and allowed to login. After the initial login, his movements will be continuously monitored to check if he is the specified user. Three parameters will be used for the identification: speed of the mouse, deviation from a straight line and the angle of the devia tion. There will be two stages of the software model. In the first stage, various mouse movement patterns are recorded for each user till we find the threshold within which the user's mouse movement properties fall and a template file is made. In the second stage, actual verification will be done based on the template file created in the first stage. The software will compare the real time statistics with the template file and decide the authenticity of the user. If none of the three parameters match the user's template file data, he will be forced to logout.

CS297 Results

  • Recorded mouse coordinates for a user by making him move the mouse on some specified points on the screen. Plotted graph between speed and time, deviation and time and angle and time.
  • Tracked the mouse movements in background and plotted the graph of mouse coordinates and time by installing mouse hooks.
  • Isolated the regions on the screen where the mouse hovered the most. Used gift-wrapping algorithm to draw convex hulls around the dense regions.

Proposed Schedule

Week 1-3: Aug 30-Sep 20Study mathematical models and implement them to find threshhold of the parameters
Week 4: Sep 13-20Read up on Bezeir curves
Week 5-7: Sep 20-Oct 4Prepare a working model
Week 8-9: Oct 4-18Do experiments to check how well the model works
Week 10-12: Oct 18-Nov 8Start writing the report
Week 13: Nov 8-15Submit the draft to committee
Week 14-15: Nov 15-29Prepare presentation
Week 16: Dec 1-8Oral defense

Key Deliverables:

  • Software
    • Record the parameters (speed, deviation and angle) during initial login (as described in the abstract) by making the user move the mouse on fixed points on the screen and check with the already recorded parameters from previous graphs of these parameters that they match i.e., they fall within a certain threshold as calculated for that person in the first stage (described in the abstract) using statistical algorithms.
    • For continuous monitoring of the mouse, consider the convex hulls (as described in CS297 Deliverable 3) as the start and end points depending on the mouse movement at that time. Calculate the parameters (speed, deviation and angle) between these two points and compare them with already recorded parameters for the two points for that user.
    • Do experiments to see how well the software works by gathering the data from various users many times and then finding the false acceptance rate and true rejection rate of the software.
  • Report
    • Description of the mouse authentication model and experimental results.

Innovations and Challenges

  • Designing a user authentication technique with mouse movement has never been used before.
  • Implementing various mathematical models for finding the threshhold of the parameters.
  • Finding the false acceptance and true rejection rates.


[CE93] Statistical Language Learning. Eugene Charniak. MIT. 1993.

[PI02] Circuit complexity and Neural Networks. Ian Parberry. MIT 1994

[RP03] Java-Based Internet Biometric Authentication System. Ross A.J and Peter W. McOwan. IEEE Transactions on Pattern and Machine Intelligence. Vol 25(9).Page 1166-1172. 2003.

[HR02] Movement Awareness for Ubiquitous Game Control. Robert Headon & Rupert Curwen. Personal and Ubiquitious Computing. Springer-Verlag. Vol 6. Page 407-415. 2002.

[RS02] Artificial Intelligence.Stuart J.Russell , Peter Norvig. Prentice Hall. 2002