# Fuzzy Multi-Criteria Based Trust Management in Heterogeneous Federated Future Internet Testbeds
## 2 Related Work  
A federation of future Internet testbeds provides various types of resources, such as wired, wireless, cloud computing and virtualized (e.g., Software Defined Networks (SDN)) resources. Thus, this section presents the most interesting trust and reputation approaches on these types of services in the literature. For general information on future internet security architectures, the interested reader can refer to [9]. [PERSON] et al. [1] presented a complete survey on trust and reputation systems for three types of web services, named single, composite and communities. The authors of [10] proposed a Bayesian network reputation and trust model for single web services that was based on direct user feedback, the recommendation of other users and QoS data. Furthermore, a credibility mechanism for the users was provided. RATEWeb [11] is a trust framework for selecting and composing web services. The reputation score is computed with a statistical method that utilizes the credibility of the users, their personalized references, the immediate knowledge and the temporal sensitivity. A game-theoretic model for composite services was proposed by [PERSON] [12]. A Bayesian model was used to derive the trust value of each service for possible collaboration with other services. This value was used to compute a trust-based cost in order to find the winner service, which was eventually allocated with tasks. Several approaches were proposed for reputation and trust management in wireless sensor and ad hoc networks. In [13], a reputation framework for data integrity in wireless sensor networks was presented, where each node evaluated the past activities and predicted the future behavior of other nodes by maintaining reputation values. A Bayesian formulation was adopted for reputation representation and evolution. Furthermore, a consensus-based outlier scheme was used as the credibility mechanism of data reading. [PERSON] et al. [14] presented a trust management approach for unattended wireless sensor networks based on subjective logic. This study aims at providing trusted data storage and generation. Furthermore, the authors used the trust similarity function to detect outliers and protect against trust pollution attacks. ART [15] aimed at detecting malicious attacks and evaluating the trustworthiness of mobile nodes and data in vehicular ad hoc networks. In this study, node trust had a two-dimensional meaning in terms of fulfilling a functionality and recommendation to other nodes. The Dempster-Shafer theory of evidence was used for data analysis, and these pieces of evidence were utilized to derive the trustworthiness of the node and data. The recommendation trust of nodes was evaluated by collaborative filtering. In the cloud computing environment, reputation and trust management systems have been broadly used for provider selection or security. CloudArmour [16] is a reputation-based trust management framework that focuses on availability and security. A credibility model was proposed to detect feedback collision and Sybil attacks, while an availability model spread the trust management service nodes in order to manage the users' feedback in a decentralized manner. [PERSON] [17] proposed a trust model for selecting resources from different cloud providers. The trust value is a weighted composition of some QoS metrics, e.g., availability and data integrity, and the candidate cloud user negotiates with the system manager to make the final decision. CloudRec [18] is a recommendation mechanism designed for mobile cloud services. It is based on adaptive QoS management, and it monitors the performance of cloud services and recommends the ideal one to users according to their contextual information. With the advent of 5G technologies, many researchers have focused on Network Function Virtualization (NFV) and SDN. The trust management of this type of networks is an open challenge.