Graduation Year


Document Type




Degree Name

MS in Computer Science (M.S.C.S.)

Degree Granting Department

Computer Science and Engineering

Major Professor

Yao Liu, Ph.D.

Committee Member

Jay Ligatti, Ph.D.

Committee Member

Yicheng Tu, Ph.D.


Sensors, Accelerometer, Smart Phones, FFT, Coherence


With the advancements in technology and computing environment capabilities, the number of devices that people carry has increased exponentially. This increase initially occurred as a result of necessity to monitor the human body condition due to chronic diseases, heart problems etc. Later, individuals’ interest was drawn towards self-monitoring their physiology and health care. This is achieved by implanting various sensors that can proactively monitor the human body based on medical necessity and the health condition of the user. Sensors connected on a human body perceive phenomena such as locomotion or heartbeat, and act accordingly to form a Body Area Network. The primary concern of these sensors is to ensure a secure way of communication and coordination among the devices to form a flawless system. A secondary concern is wireless sensor authentication, which ensures trustworthiness and reliable gathering of a user’s data. To address this concern, we designed a secure approach using low cost accelerometers to authenticate sensors in Body Area Networks.

To ensure authentication in on-body sensor networks, we need a mechanism which intuitively proves all the communicating nodes are trusted ones. In order to achieve sensor authentication, we used accelerometer data gathered from sensors to distinguish whether or not the devices are carried on waist of same individual’s body. Our approach is focused at analyzing walking patterns recorded from smartphone accelerometers placed in the same location of the user’s body, and we present results showing these sensors record similar pattern.