Abstract:
Edge computing is a distributed architecture, that features decentralized processing of data near the source, where data is being generated, or by the device that is generating the said data. These devices are known as Internet of Things (IoT) devices or edge devices. The data generated by the IoT devices has increased significantly over the passage of time, it has become infeasible to transfer all the data over to the cloud for processing. This gave rise to the edge computing paradigm. In edge computing data is processed by these devices and only the required data is sent to cloud to increase robustness and decrease overall network overhead. IoT edge devices are inherently suffering from various security risks and attacks causing a lack of trust between devices. To reduce this malicious behavior, a lightweight trust management system is required that maintains the trust of a device and manages the service level trust along with the quality of service (QoS). This allows the communication of trusted devices and their data can also be considered as legitimate as the devices are trusted. Since this is an emerging paradigm, a limited amount of research is carried out to address the trust issues. Therefore, the focus of this research is to develop a lightweight trust management model which calculates the overall trust of the devices by using QoS parameters to evaluate the trust of devices through assigned weight. Trust management models using QoS parameters show improved results that can be helpful in identifying malicious edge nodes in edge computing networks and can be used for industrial purposes.
