A novel trust management model for edge computing

Abstract

Edge computing is a distributed architecture that features decentralized processing of data near the source/devices, where data are being generated. These devices are known as Internet of Things (IoT) devices or edge devices. As we continue to rely on IoT devices, the amount of data generated by the IoT devices have increased significantly due to which it has become infeasible to transfer all the data over to the Cloud for processing. Since these devices contain insufficient storage and processing power, it gives rise to the edge computing paradigm. In edge computing data are processed by edge devices and only the required data are sent to the 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 model is proposed that maintains the trust of a device and manages the service level trust along with quality of service (QoS). The model calculates the overall trust of the devices by using QoS parameters to evaluate the trust of devices through assigned weights. 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.

Towards a Reputation-based Trustworthy Edge-Cloud Continuum

“…Numerous recent studies have put forth solutions to tackle distributed reputation management in the edgecloud continuum. Examples of such works encompass the research conducted by Yuan et al [5], DREAMS [6], Liang et al [7], COMITMENT [8], Latif et al [9], Liu et al [10], Feng et al [11], and Kang et al [3].…”

“…The final reputation score is determined by a weighted average of recommendations provided by peers, the weight assigned based on the level of trustworthiness of each peer. [9] presents a trust management model for edge computing that comprises a rating management module and a trust calculation module. Node ratings are determined by evaluating quality of service (QoS) parameters, and the trust score is calculated as a weighted average of these parameters.…”

Towards a Reputation-based Trustworthy Edge-Cloud Continuum

“…Numerous recent studies have put forth solutions to tackle distributed reputation management in the edgecloud continuum. Examples of such works encompass the research conducted by Yuan et al [5], DREAMS [6], Liang et al [7], COMITMENT [8], Latif et al [9], Liu et al [10], Feng et al [11], and Kang et al [3].…”

A Maturity Framework for Zero-Trust Security in Multiaccess Edge Computing

“…In heterogeneous environments like MEC, the infrastructure needs to examine the pertinent aspects of access requests instead of assuming trust based on a point-in-time assurance, that is, admission control or network location. Trust management for MEC introduces challenges as identified in [7,[26][27][28][29]. In the ZTS approach, the security posture of applications, users, and UE [11,24] will be continually reassessed.…”