No Arabic abstract
The salient features of blockchain, such as decentralisation and transparency, have allowed the development of Decentralised Trust and Reputation Management Systems (DTRMS), which mainly aim to quantitatively assess the trustworthiness of the network participants and help to protect the network from adversaries. In the literature, proposals of DTRMS have been applied to various Cyber-physical Systems (CPS) applications, including supply chains, smart cities and distributed energy trading. In this chapter, we outline the building blocks of a generic DTRMS and discuss how it can benefit from blockchain. To highlight the significance of DTRMS, we present the state-of-the-art of DTRMS in various field of CPS applications. In addition, we also outline challenges and future directions in developing DTRMS for CPS.
The public key infrastructure (PKI) based authentication protocol provides the basic security services for vehicular ad-hoc networks (VANETs). However, trust and privacy are still open issues due to the unique characteristics of vehicles. It is crucial for VANETs to prevent internal vehicles from broadcasting forged messages while simultaneously protecting the privacy of each vehicle against tracking attacks. In this paper, we propose a blockchain-based anonymous reputation system (BARS) to break the linkability between real identities and public keys to preserve privacy. The certificate and revocation transparency is implemented efficiently using two blockchains. We design a trust model to improve the trustworthiness of messages relying on the reputation of the sender based on both direct historical interactions and indirect opinions about the sender. Experiments are conducted to evaluate BARS in terms of security and performance and the results show that BARS is able to establish distributed trust management, while protecting the privacy of vehicles.
There has been tremendous interest in the development of formal trust models and metrics through the use of analytics (e.g., Belief Theory and Bayesian models), logics (e.g., Epistemic and Subjective Logic) and other mathematical models. The choice of trust metric will depend on context, circumstance and user requirements and there is no single best metric for use in all circumstances. Where different users require different trust metrics to be employed the trust score calculations should still be based on all available trust evidence. Trust is normally computed using past experiences but, in practice (especially in centralised systems), the validity and accuracy of these experiences are taken for granted. In this paper, we provide a formal framework and practical blockchain-based implementation that allows independent trust providers to implement different trust metrics in a distributed manner while still allowing all trust providers to base their calculations on a common set of trust evidence. Further, our design allows experiences to be provably linked to interactions without the need for a central authority. This leads to the notion of evidence-based trust with provable interactions. Leveraging blockchain allows the trust providers to offer their services in a competitive manner, charging fees while users are provided with payments for recording experiences. Performance details of the blockchain implementation are provided.
Technical advances in ubiquitous sensing, embedded computing, and wireless communication are leading to a new generation of engineered systems called cyber-physical systems (CPS). CPS promises to transform the way we interact with the physical world just as the Internet transformed how we interact with one another. Before this vision becomes a reality, however, a large number of challenges have to be addressed. Network quality of service (QoS) management in this new realm is among those issues that deserve extensive research efforts. It is envisioned that wireless sensor/actuator networks (WSANs) will play an essential role in CPS. This paper examines the main characteristics of WSANs and the requirements of QoS provisioning in the context of cyber-physical computing. Several research topics and challenges are identified. As a sample solution, a feedback scheduling framework is proposed to tackle some of the identified challenges. A simple example is also presented that illustrates the effectiveness of the proposed solution.
The proliferation of digitization and complexity of connectivity in Cyber-Physical Systems (CPSs) calls for a mechanism that can evaluate the functionality and security of critical infrastructures. In this regard, Digital Twins (DTs) are revolutionizing the CPSs. Driven by asset-centric data, DTs are virtual replicas of physical systems that mirror every facet of a product or process and can provide actionable insights through monitoring, optimization, and prediction. Furthermore, replication and simulation modes in DTs can prevent and detect security flaws in the CPS without obstructing the ongoing operations of the live system. However, such benefits of DTs are based on an assumption about data trust, integrity, and security. Data trustworthiness is considered to be more critical when it comes to the integration and interoperability of multiple components or sub-components among different DTs owned by multiple stakeholders to provide an aggregated view of the complex physical system. Moreover, analyzing the huge volume of data for creating actionable insights in real-time is another critical requirement that demands automation. This article focuses on securing CPSs by integrating Artificial Intelligence (AI) and blockchain for intelligent and trusted DTs. We envision an AI-aided blockchain-based DT framework that can ensure anomaly prevention and detection in addition to responding against novel attack vectors in parallel with the normal ongoing operations of the live systems. We discuss the applicability of the proposed framework for the automotive industry as a CPS use case. Finally, we identify challenges that impede the implementation of intelligence-driven architectures in CPS.
In this paper, we propose a trust-centric privacy-preserving blockchain for dynamic spectrum access in IoT networks. To be specific, we propose a trust evaluation mechanism to evaluate the trustworthiness of sensing nodes and design a Proof-of-Trust (PoT) consensus mechanism to build a scalable blockchain with high transaction-per-second (TPS). Moreover, a privacy protection scheme is proposed to protect sensors real-time geolocatioin information when they upload sensing data to the blockchain. Two smart contracts are designed to make the whole procedure (spectrum sensing, spectrum auction, and spectrum allocation) run automatically. Simulation results demonstrate the expected computation cost of the PoT consensus algorithm for reliable sensing nodes is low, and the cooperative sensing performance is improved with the help of trust value evaluation mechanism.In addition, incentivization and security are also analyzed, which show that our design not only can encourage nodes participation, but also resist to many kinds of attacks which are frequently encountered in trust-based blockchain systems.