With increased inter-connectivity among disparate devices, such as Internet-of-Things (IoT) devices, including those deployed in a nation’s critical infrastructure, there is a need to ensure that any failure in the deployed devices can be detected. The capability to automatically detect device failures is particularly crucial in a large-scale, complex IoT system, since it can be very time-consuming and challenging to investigate a large number of geographically-dispersed devices that are also of different makes and types. In this paper, we present a faulty-device identification technique that is designed to achieve lightweight processor-level architectural support. Specifically, a hardware-based monitoring agent is incorporated within a processor and connected to a separate monitoring program when an examination is required. By analyzing information collected by the agent, the monitoring program determines whether the device being monitored is functioning. Findings from our detailed evaluation demonstrate that the proposed approach can detect around 90 percent of the failures with minimal hardware overhead of approximately 5k gates. This area overhead is reasonable and amounts to 7.69 percent of the ARM Cortex-M4 – a lightweight IoT-class processor – that has a total area (excluding optional caches and scratch-pad memory) of 65k gates.

Internet-of-Things (IoT) is increasingly becoming the norm in both civilian and military settings. In this paper, we present a comprehensive security abstraction layer for IoT systems based on blockchain, which provides us a logical view of a system that comprises trusted devices. The goal of the proposed layer is to detect and isolate untrusted devices. The proposed abstraction layer provides three services, namely: authorization, authentication, and auditing by using blockchain and smart contract-based approaches. We adopt a hardware based approach, where dedicated hardware modules are used to monitor the behavior of the firmware without incurring excessive performance overhead.