With the popularization of intelligent terminals, especially current trends, such as “Industrie 4.0” and the Internet of Things, mobile crowdsensing is becoming one of the promising applications built on smart devices in mobile networks. However, the existing mobile crowdsensing models are mostly based on a centralized platform, which is not fully trusted in reality and results in the existence of fraud and other security problems. Furthermore, the data quality collected through crowdsensing is varied, and the location privacy is difficult to guarantee, especially at the worker selection stage. To solve these two problems, an effective blockchain-based location-privacy-preserving crowdsensing model, CrowdBLPS, is proposed in this article. First, the idea of a blockchain is introduced into this model. The decentralized structure and the consensus approach are applied to realize the nonrepudiation and nontampering of information. Second, to improve the data sensing quality and protect worker privacy, a two-stage approach, including the preregistration stage and the final selection stage, is proposed. Finally, we further implement a prototype on the Ethereum public testing network, and the experimental results show the feasibility, availability, and reliability of CrowdBLPS.

The unprecedented proliferation of smart home together with wireless sensor networks has enriched human’s daily life. Inevitably, the smart home without the guard of authentication mechanism is bound to bring a series of security issues. Hence, a great number of authentication protocols have been designed to verify the user’s identity and ensure that the data be accessed with authorization in smart home. Recently, (M. Shuai et al., 2019) (Computers & Security, 2019) proposed a two-factor anonymous authentication scheme for smart home and presented that their scheme can be immune to various attacks. However, by careful analysis, we found that (M. Shuai et al.’s, 2019) scheme needed further improvements in session key forward secrecy and against: type-I node capture attack and node impersonation attack. As a going step to this direction, here, we first design a robust two-factor user authentication also for smart home based on the elliptic curve cryptography. Second, we give security proofs to demonstrate that the construction of the proposed scheme can be of user anonymity, session key forward secrecy, and resist all attacks shown in this article. Third, performance comparisons covered in storage/network communication/computation costs are carried out to indicate that our scheme can be comparable to those newly designed schemes, especially, the user and gateway in our scheme need only 352 and 320 bits, respectively.

Sharded blockchain offers scalability, decentralization, immutability, and linear improvement, making it a promising solution for addressing the trust problem in large-scale collaborative IoT. However, a high proportion of cross-shard transactions (CSTs) can severely limit the performance of decentralized blockchain. Furthermore, the dynamic assemblage characteristic of collaborative sensing in sharded blockchain is often ignored. To overcome these limitations, we propose HMMDShard, a dynamic blockchain sharding scheme based on the hidden Markov model (HMM). HMMDShard leverages fine-grained blockchain sharding and fully embraces the dynamic assemblage characteristic of IoT collaborative sensing. By integrating the HMM, we achieve adaptive dynamic incremental updating of blockchain shards, effectively reducing CSTs across all shards. We conduct a comprehensive analysis of the security issues and properties of HMMDShard, and evaluate its performance through the implementation of a system prototype. The results demonstrate that HMMDShard significantly reduces the proportion of CSTs and outperforms other baselines in terms of system throughput and transaction confirmation latency.

With the widespread popularity of Internet-enabled devices, mobile users can request and receive messages anytime and anywhere, which facilitates information feedback for smart city management. However, few people are willing to reflect or report some violations of law and discipline around them, and more people choose to ignore. In general, there are two major reasons for this phenomenon. First, reporting with a real name is highly recommended, but it is difficult to send trusted and reliable reporting messages without revealing the reporter’s identity. Second, generally no benefit, users usually lack the motivation to report due to worrying about being retaliated. In this paper, we propose an effective anonymous reporting system called ReportCoin, a novel Blockchain-based incentive anonymous reporting system. ReportCoin guarantees user identity privacy and reporting message reliability throughout the reporting process. On the one hand, ReportCoin allows nondeterministic mobile users to vote the reporting by signing and to send anonymous announcements in the non-fully trusted network. On the other hand, ReportCoin motivates users with incentives to report without worrying about the disclosure of identity information to be retaliated. Meanwhile, account information and transaction records in ReportCoin are open, transparent, and tamper-resistant. Theoretical analysis and extensive experimental results show that ReportCoin is efficient and practical.

Combining tiny sensors and wireless communication technology, wireless body area network (WBAN) is one of the most promising fields. Wearable and implantable sensors are utilized for collecting the physiological data to achieve continuously monitoring of people’s physical conditions. However, due to the openness of wireless environment and the significance and privacy of people’s physiological data, WBAN is vulnerable to various attacks; thus, strict security mechanisms are required to enable a secure WBAN. In this article, we mainly focus on a survey on the security issues in WBAN, including securing internal communication in WBAN and securing communication between WBAN and external users. For each part, we discuss and identify the security goals to be achieved. Meanwhile, relevant security solutions in existing research on WBAN are presented and their applicability is analyzed.

With the advent of the Internet of Things (IoT), crowdsensing, as a new emerging application of the IoT that employs ubiquitous mobile users with smartphones for data collection and processing, has further deepened our knowledge. However, the problems of the current crowdsensing systems regarding system security, user privacy, and user payment (UP) raise serious privacy and security concerns, which affect participants’ adoption of the system. The Blockchain technology allows for nondeterministic multiple parties to interact with each other anonymously in a network that is not fully trusted. In this article, we propose a new decentralized crowdsensing system, called CrowdHB . Unlike other blockchain-based crowdsensing systems, CrowdHB adopts a hybrid blockchain architecture and uses smart contracts to achieve location privacy preservation and ensure data quality while improving the system performance. Furthermore, to optimize task assignments to mobile users, we propose a location privacy-preserving optimization mechanism (LPPOM) and the approach of consistency optimization (ACO) to achieve a tradeoff between user privacy and system performance. The extensive experimental results show that the proposed CrowdHB outperforms the other crowdsensing systems in terms of task success rate and performance for a large number of mobile users and tasks.