Degree Type


Date of Award


Degree Name

Master of Science


Electrical and Computer Engineering


Computer Engineering

First Advisor

Yong Guan


Security problems have been discussed for a long time in the past recent decades in many fields such as communication, networking and user authentication. Security and authentication methods have also been explored for a long time by many researchers, and many ecient ways have been developed and used in modern society. Password and fingerprint based user authentication methods are most common user authentication methods being used in our daily lives. With computers and smart phones population growing vastly, we need to put more attention on the security methods. However, those traditional authentication methods are not safe and ecient enough. Passwords are stolen and revealed to hackers, while fingerprint can be easily got from an authenticated person. We moved our eyes on another way of security and authentication- biometric kinesiology. The muscle in our body can remember the movement if we practiced an action a lot, and that memory is built in the body, not in our brain memory, which means that we cannot forget a practiced action in the way we forget a password. We proposed to use the action with mouse from an authenticated user as the password of a system, in which only the user perform right action can be regarded as an authenticated user. Otherwise the system will reject the user. This movement is hard to mimic unless the hacker do a lot of practice of that certain movement and do exactly the same as an authenticated user. This is very difficult because we modified the normal mouse and the mouse will not move as the hacker expect. What’s more, only the authenticated user knows how was the mouse be modified and how to act to adjust to that modification. In this way our proposed approach is much safer than the above traditional security and authentication methods. However, this is a feasibility study and more experiment will be done to prove our proposal and we will discuss it in the future work chapter.


Copyright Owner

Xuantong Zhang



File Format


File Size

48 pages