Trustee: A Trust Management System for Fog-Enabled Cyber Physical Systems

Abstract

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, badmouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasures the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e. CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system.

A Multi-Dimensional and Multi-Factor Trust Computation Framework for Cloud Services

“…The evidence can be aggregated in two ways, subjective logic [5] and real-time adaptive trust computation [9,10]. The main difference between the two approaches is the manner in which weights are assigned; in the former, they are assigned manually and/or based on personal preferences, and in the latter, they are assigned using the maximizing deviation method [10], information entropy [9], and regression [11][12][13]. Besides these, some studies employ both subjective and objective trust to evaluate the trustworthiness of systems [6,10,14,15].…”

“…The trust is computed at the fog layer to ensure the trust ratings are accessible in real-time with no and/or negligible delay and latency. Recently, the work in [13] proposes a trust management system to compute the trust for different entities in a fog-based cyberphysical system (CPS). This is an objective trust computation model wherein the final trust in fog nodes is computed by combining the evidence gathered from IoT devices and a fog monitoring node.…”

“…This module monitors the QoS parameters of CSP by pulling in the run-time service statistics. Our choice of parameters is motivated by [13], but they have used it for fog nodes. Since the cloud services are like large-scale fog nodes, it was rational for us to use the same parameters as them.…”

A Secure Integrated Framework for Fog-Assisted Internet-of-Things Systems

“…For trust computation of fog nodes, two sources of evidence, namely QoS parameters and network communication features, similar to [23], are used. Precisely, the trust of a fog node T f og is computed by aggregating the trust computed from QoS evidence monitored by FO and the network communication parameters sent by IoT devices.…”

Dynamic resource provisioning for cyber-physical systems in cloud-fog-edge computing

“…In [71], Junejo et al integrates CPS with fog computing for its timeliness and low latency but they also point out that the FC-CPS systems are usually deployed in an open and relatively unprotected environment which means both the CPS devices and these fog nodes are very vulnerable and are in a situation where numerous attacks such as collusion and ballot-stuffing may happen from time to time. To deal with those challenges, a Trust Management System is proposed where the FC-CPS devices are the trustor and fog assisted nodes are the trustee.…”