# A Modular IoT Hardware Platform for Distributed and Secured Extreme Edge Computing
## 1 Introduction  
The Internet of Things paradigm has achieved an enormous integration level inside the technology distributed all around the world. It covers from consumer electronics, such as Wi-Fi controlled thermostats, to industrial or professional applications, such as a Wireless Sensor Network (WSN) registering data all along a whole forest. The future of communication protocols could also lead to bigger growths on new IoT system implementations, e.g., real-time systems collecting data from dozens of sensors around a fabric to optimize manufacturing operations dynamically. Therefore, the development of this kind of platforms looks promising. The traditional hardware solutions that were used in Wireless Sensor Networks mostly relied on de-facto standard sensor motes, such as Micas and TelosB [1], or similar approaches where 8-bit or 16-bit-based microcontrollers were integrated as the core of the wireless devices, to perform simple yet energy-efficient tasks for the target application. During the last decade tens of hardware platforms for the Extreme Edge [2] of the IoT have appeared with different elements and focusingon aspects such as low power consumption, high processing capabilities or open HW philosophy, among others [3]. Although these hardware platforms have been valid for many WSN application contexts, the ongoing revolution of IoT is pushing the hardware implementation towards the integration of more complex capabilities that allow tackling the challenges of smart and highly dynamic scenarios [4], particularly concerning the arising end-to-end IoT security issues with such an amount of expected Edge devices in place. In this sense, the traditional behavior of a WSN, in which the devices remained in sleep modes for a very long period of time (thus the main consumption components to be considered were the deep power modes) and then wake up to transmit a sensing measurement to a root device, is changing to more active collaborations among participant sensors, in which the type of features they provide to the local or overall IoT Edge deployment becomes a key performance element of the system. In such scenarios, protecting the relationships among the nodes is crucial to assure data integrity and security on the Edge. Nonetheless, it seems that practical implementation problems of IoT networks are always related to security and reliability issues. One of the many reasons is that those networks are usually built up from many nodes that have some restrictions on energy consumption and processing capabilities. Thus, they are often designed as tiny embedded systems with low-cost processors that do not have the enough computational power to implement security systems. However, if the problems associated with a lack of security capabilities are ignored, several disasters on the network and on the products related to it can indeed appeared. A common mistake on simple IoT products deployment is to think that data exchanged by the nodes on the Edge is not critical, as it does not contain private data about users, e.g., humidity sensors sensing moisture measurements to the central node that controls the overall climate of one house. However, since the security process is too simple or may not even exist on these nodes, an attacker could take control of one node and then scale privileges through upper layers of the network, reaching cloud server and the data located there. The problem resides not only in the ability of the attacker to scale privileges in the network. Actions taken inside the nodes on the Edge might be also harmful for the system and for the users. Although many people might think that an attacker stealing data related to the temperature of their rooms is not a real threat, other systems may suffer from this uncontrolled access to the Edge. A good example of that is the research made by the authors in [5], where they analyzed the security problems within the Philips Hue lamps.