Data Provenance for IoT using Wireless Channel Characteristics and Physically Unclonable Functions
Muhammad Naveed Aman, Mohammed Haroon Basheer, Biplab Sikdar · 2019
IoT can provide many new exciting services in energy management, home and commercial automation, environmental monitoring etc. Data provenance establishes the trust in the origin and location of data. This paper takes an information theoretic approach to solve the problem of data provenance in IoT systems. The proposed protocol uses Physically Unclonable Functions to prove the origin of data and wireless fingerprints derived from the received signal strength indicator (RSSI) measurements to verify the location of the IoT device producing the data. The security analysis of the proposed protocol shows that it is robust against different types of attacks. Experimental results show that the proposed technique can improve the accuracy of detecting attacks by 100% as compared to existing techniques.