Pattern-of-Life Modeling Using Data Leakage in Smart Homes
Abstract
This work investigates data leakage in smart homes by providing a Smart Home Automation Architecture (SHAA) and a device classifier and pattern-of-life analysis tool, CITIoT (Classify, Identify, and Track Internet of things). CITIoT was able to capture traffic from SHAA and classify 17 of 18 devices, identify 95 of the events that occurred, and track when users were home or away with near 100 accuracy. Additionally, a mitigation tool, MIoTL (Mitigation of IoT Leakage) is provided to defend against smart home data leakage. With mitigation, CITIoT was unable to identify motion and camera devices and was inundated with an average of 221 false positives per day that made it ineffective at identifying real events. Also, CITIoT was only able to recognize 8 minutes of 24 hours that the user was away from the smart home. This work closes by stressing the vulnerabilities presented through the demonstration of how an adversary can use CITIoT to crack a BLE lock and gain access to the home. Lastly, security recommendations are provided to defend against vulnerabilities presented in this work and create a safer smart home environment.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 23, 2018
- Accession Number
- AD1055975
Entities
People
- Steven M Beyer
Organizations
- Air Force Institute of Technology