The cloud-enabled Internet of controlled things (IoCT) envisions a network of sensors, controllers, and actuators connected through a local cloud in order to intelligently control physical devices. Because cloud services are vulnerable to advanced persistent threats (APTs), each device in the IoCT must strategically decide whether to trust cloud services that may be compromised. In this paper, we present iSTRICT, an interdependent strategic trust mechanism for the cloud-enabled IoCT. iSTRICT is composed of three interdependent layers. In the cloud layer, iSTRICT uses FlipIt games to conceptualize APTs. In the communication layer, it captures the interaction between devices and the cloud using signaling games. In the physical layer, iSTRICT uses optimal control to quantify the utilities in the higher level games. Best response dynamics link the three layers in an overall "game-of-games," for which the outcome is captured by a concept called Gestalt Nash equilibrium (GNE). We prove the existence of a GNE under a set of natural assumptions and develop an adaptive algorithm to iteratively compute the equilibrium. Finally, we apply iSTRICT to trust management for autonomous vehicles that rely on measurements from remote sources. We show that strategic trust in the communication layer achieves a worst-case probability of compromise for any attack and defense costs in the cyber layer.
@cite_24: An increasingly large number of cars are being equipped with global positioning system and Wi-Fi devices, enabling vehicle-to-vehicle (V2V) communication with the goal of providing increased passenger and road safety. This technology actuates the need for agents that assist users by intelligently processing the received information. Some of these agents might become self-interested and try to maximize car owners' utility by sending out false information. Given the dire consequences of acting on false information in this context, there is a serious need to establish trust among agents. The main goal of this paper is then to develop a framework that models the trustworthiness of the agents of other vehicles, in order to receive the most effective information. We develop a multifaceted trust modeling approach that incorporates role-, experience-, priority-, and majority-based trust and this is able to restrict the number of reports that are received. We include an algorithm that proposes how to integrate these various dimensions of trust, along with experimentation to validate the benefit of our approach, emphasizing the importance of each of the different facets that are included. The result is an important methodology to enable effective V2V communication via intelligent agents.
@cite_15: Consumers' feedback is a good source to help assess overall trustworthiness of cloud services. However, it is not unusual that a trust management system experiences malicious behaviors from its users (i.e., collusion or Sybil attacks). In this paper, we propose techniques for the detection of reputation attacks to allow consumers to effectively identify trustworthy cloud services. We introduce a credibility model that not only identifies misleading trust feedbacks from collusion attacks but also detects Sybil attacks, either strategic (in a long period of time) or occasional (in a short period of time). We have collected a large collection of consumer's trust feedbacks given on real-world cloud services (over 10, 000 records) to evaluate and demonstrate the applicability of our approach and show the capability of detecting such malicious behaviors.
@cite_21: Cloud computing trust management has become an important subject in recent years. Trust management is a difficult and complicated work in cloud computing due to features such as distributed, dynamic and non-transparent environment. Since most trust management frameworks predict trust values based on received feedbacks, the validation and authenticity of feedback are highly necessary. In this paper, two new methods are presented to identify fake feedbacks. One is feedback evaluation component and the other is Bayesian game model. The feedback evaluation component is used to examine the received feedback and identify its probable fake identity. Our results reveal that the feedback evaluation component can correctly identify and rectify fake feedbacks. Bayesian game model is presented to detect malicious users and prevent their feedbacks. Simulation results coincided well with analytical results, indicating that our Bayesian game model can correctly recognize malicious user. Received feedbacks from malicious user are identified as fake feedbacks. Eventually, two new methods were compared.
@cite_32: Cloud computing brings in a novel paradigm to foster ITbased service economy in scalable computing infrastructures by allowing guaranteed on-demand resource allocation with flexible pricing models. Scalable computing infrastructures not only require autonomous management abilities but also the compliance to users' requirements through Service Level Agreements (SLAs). Such infrastructures should automatically respond to changing components, workload, and environmental conditions as well as prevent violations of agreed SLAs. The essential requirements for SLA-based orchestration of services include agile component-based infrastructure to support these orchestrations; proactive validation of SLAs to prevent violations; and business enabling requirements including trust, privacy and breach management to address penalty enforcement, renegotiation and recovery. In this paper we outline a systematic approach that weaves together three different SLA management models, which cater the above mentioned issues by localizing and addressing them at different but interrelated scopes pertaining to resource, infrastructure, and business domains. In our framework Cloud components (e.g., meta negotiator, broker, automatic service deployer) are loosely coupled using SLAs and can be exchanged on demand considering current load, systems failures, and the whole Cloud ecosystem. Thereafter, SLAs are validated based on high level goals (e.g., business rules, VO policies) ensuring trust, privacy, and breach management in layered Cloud infrastructures.
black In the IoCT, however, agents may not have sufficient number of interactions, which makes reputation challenging to obtain @cite_24 . In addition, trust value-based cloud trust management systems can be compromised by reputation attacks through fake feedback which can severely degrade the system performance @cite_21 @cite_15 . Therefore, in this work, we aim to design a strategic trust mechanism which is predictive rather than reactive through an integrative game-theoretic framework. Rather than using trust value @cite_32 @cite_15 , IoCT devices in our iSTRICT model make decisions based on the strategies of players at the cloud layer as well as based on the physical system performance. This multi-layer design provides resilience to reputation attacks.