An Efficient Interaction Protocol Inference Scheme for Incompatible Updates in IoT Environments

Abstract

Incompatible updates of IoT systems and protocols give rise to interoperability problems. Even though various protocol adaptation and unknown protocol inference schemes have been proposed, they either do not work where the updated protocol specifications are not given or suffer from inefficiency issues. In this work, we present an efficient protocol inference scheme for incompatible updates in IoT environments. The scheme refines an active automata learning algorithm, L*, by incorporating a knowledge base of the legacy protocol behavior into its membership query selection procedure for updated protocol behavior inference. It also infers protocol syntax based on our previous work that computes the most probable message field updates and adapts the legacy protocol message accordingly. We evaluate the proposed scheme with two case studies with the most popular IoT protocols and prove that it infers updated protocols efficiently while improving the L* algorithm's performance for resolving the incompatibility.