Securing Internet of Things (IoT) through an Adaptive Framework

The research on Internet of Things (IoT) has made tremendous progress in the last few years. IoT is being regarded as the next big thing that is going to change human perception about daily life. Smart devices of heterogeneous nature make an essential part of modern day IoT-based system. Because of the amount and type of data handled by these devices, they are an attractive target for malicious attackers. To secure the IoT devices of heterogeneous nature, we formulated a weighted optimization problem. The objective of this problem is to secure the IoT devices while finding the best trade-off between their resource usage and throughput. For this purpose, we consider five different implementations of AES cryptographic scheme that offer varied resources and throughput. These implementation schemes are mapped to IoT devices through a novel adaptive framework. This framework considers the resource and throughput requirements of different IoT devices and uses Hungarian algorithm to map different AES implementations on them. The comparison of proposed framework with random and greedy approaches shows that the proposed framework adaptively secures the IoT-based system while providing higher average throughput and requiring fewer resources.