Industrial Internet of Things (IIoT) plays an indispensable role for Industry 4.0, people are committed to implementing a general, scalable and secure IIoT system to be adopted across various industries. However, existing IIoT systems are vulnerable to single point of failure and malicious attacks, which cannot provide stable services. Due to the resilience and security promise of blockchain, the idea of combining blockchain and IoT gains considerable interest. However, blockchains are power-intensive and low-throughput, which are not suitable for power-constrained IoT devices. To tackle these challenges, we present a blockchain system with credit-based consensus mechanism for IIoT. We propose a credit-based proof-of-work (PoW) mechanism for IoT devices, which can guarantee system security and transaction efficiency simultaneously. In order to protect sensitive data confidentiality, we design a data authority management method to regulate the access to sensor data. In addition, our system is built based on directed acyclic graph (DAG)-structured blockchains, which is more efficient than the satoshi-style blockchain in performance. We implement the system on Raspberry Pi, and conduct a case study for the smart factory. Extensive evaluation and analysis results demonstrate that credit-based PoW mechanism and data access control are secure and efficient in IIoT.

The Internet of Things (IoT) is impacting the world’s connectivity landscape. More and more IoT devices are connected, bringing many benefits to our daily lives. However, the influx of IoT devices poses non-trivial challenges for the existing cloud-based computing paradigm. In the cloud-based architecture, a large amount of IoT data is transferred to the cloud for data management, analysis, and decision making. It could not only cause a heavy workload on the cloud but also result in unacceptable network latency, ultimately undermining the benefits of cloud-based computing. To address these challenges, researchers are looking for new computing models for the IoT. Edge computing, a new decentralized computing model, is valued by more and more researchers in academia and industry. The main idea of edge computing is placing data processing in near-edge devices instead of remote cloud servers. It is promising to build more scalable, low-latency IoT systems. Many studies have been proposed on edge computing and IoT, but a comprehensive survey of this crossover area is still lacking. In this survey, we first introduce the impact of edge computing on the development of IoT and point out why edge computing is more suitable for IoT than other computing paradigms. Then, we analyze the necessity of systematical investigation on the edge-computing-driven IoT (ECDriven-IoT) and summarize new challenges occurring in ECDriven-IoT. We categorize recent advances from bottom to top, covering six aspects of ECDriven-IoT. Finally, we conclude lessons learned and propose some challenging

Internet of Vehicles (IoV) has become an indispensable technology to bridge vehicles, persons and infrastructures, and is promising to make our cities smarter and more connected. It enables vehicles to exchange vehicular data (e.g., GPS, sensors, and brakes) with different entities nearby. However, sharing these vehicular data over the air raises concerns about identity privacy leakage. Besides, the centralized architecture adopted in existing IoV systems is fragile to single point of failure and malicious attacks. With the emergence of blockchain technology, it has the chance to solve these problems due to its features of tamper-proof, traceability and decentralization. In this paper, we propose a privacy-preserving vehicular data sharing framework based on blockchain. In particular, we design an anonymous and auditable data sharing scheme using Zero-Knowledge Proof (ZKP) technology so as to protect the identity privacy of vehicles while preserving the vehicular data auditability for Trusted Authorities (TAs). In response to high mobility of vehicles, we design an efficient multi-sharding protocol to decrease blockchain communication costs without compromising the blockchain security. We implement a prototype of our framework and conduct extensive experiments and simulations on it. Evaluation and analysis results indicate that our framework can not only strengthen system security and data privacy, but also reduce communication complexity by \(O(\frac{n\sqrt {m}}{m^2}) \) times comparing to existing sharding protocols.

Mobile crowdsensing (MCS) can promote data acquisition and sharing among mobile devices. Traditional MCS platforms are based on a triangular structure consisting of three roles: data requester, worker ( i.e . , sensory data provider) and MCS platform. However, this centralized architecture suffers from poor reliability and difficulties in guaranteeing data quality and privacy, even provides unfair incentives for users. In this paper, we propose a blockchain-based MCS platform, namely BlockSense, to replace the traditional triangular architecture of MCS models by a decentralized paradigm. To achieve the goal of trustworthiness of BlockSense, we present a novel consensus protocol, namely Proof-of-Data (PoD), which leverages miners to conduct useful data quality validation work instead of “useless” hash calculation. Meanwhile, in order to preserve the privacy of the sensory data, we design a homomorphic data perturbation scheme, through which miners can verify data quality without knowing the contents of the data. We have implemented a prototype of BlockSense and conducted case studies on campus, collecting over 7,000 data from workers' mobile phones. Both simulations and real-world experiments show that BlockSense can not only improve system security, preserve data privacy and guarantee incentives fairness, but also achieve at least 5.6x faster than Ethereum smart contracts in verification efficiency.

With the emergence of the sixth-generation (6G) communication technologies, the Internet of Vehicles (IoV) is rapidly developing with the coordination between intelligent networked vehicles, road infrastructures, and the cloud. However, the openness and dynamic nature of the IoV raise significant security and privacy concerns, highlighting the need for efficient authentication schemes. Conventional authentication schemes are no longer suitable for 6G-enabled IoV due to high latency, single point of failure, and heavy management costs. Additionally, existing literature on multi-domain authentication mainly investigates vehicle mobility, ignoring the challenges posed by vehicle heterogeneity. To fill this gap, we propose a multi-domain authentication scheme with conditional privacy preservation (MACPP) that considers administrative domains ( AD ) and geographic domains ( GD ) in the IoV. In MACPP, we design a novel identity-based signature scheme without requiring bilinear pairing for efficient authentication. Additionally, we propose a blockchain-assisted pseudonym management scheme (BAPM) to further improve system security by designing a dynamical sparse Merkle tree structure (DSMT). We demonstrate that the proposed MACPP satisfies the security requirements through an in-depth security analysis. Moreover, the experimental results demonstrate the effectiveness and efficiency of both MACPP and BAPM.