Spatial crowdsourcing (SC) enables task owners (TOs) to outsource spatial-related tasks to a SC-server who engages mobile users in collecting sensing data at some specified locations with their mobile devices. Data aggregation, as a specific SC task, has drawn much attention in mining the potential value of the massive spatial crowdsensing data. However, the release of SC tasks and the execution of data aggregation may pose considerable threats to the privacy of TOs and mobile users, respectively. Besides, it is nontrivial for the SC-server to allocate numerous tasks efficiently and accurately to qualified mobile users, as the SC-server has no knowledge about the entire geographical user distribution. To tackle these issues, in this paper, we introduce a fog-assisted SC architecture, in which many fog nodes deployed in different regions can assist the SC-server to distribute tasks and aggregate data in a privacy-aware manner. Specifically, a privacy-aware task allocation and data aggregation scheme (PTAA) is proposed leveraging bilinear pairing and homomorphic encryption. PTAA supports representative aggregate statistics (e.g.,sum, mean, variance, and minimum) with efficient data update while providing strong privacy protection. Security analysis shows that PTAA can achieve the desirable security goals. Extensive experiments also demonstrate its feasibility and efficiency.

In mobile crowdsensing, truth discovery (TD) enables a crowdsensing server to extract truthful information from possibly conflicting crowdsensing data. TD provides a more accurate truth estimation than traditional truth inference methods like majority voting and averaging. However, there still exist crucial data privacy (including sensory data, inferred truths, and intermediates) and practicability ( e.g. , efficiency, utility, and non-interaction) concerns in real-world crowdsensing applications. Existing researches either fail to provide adequate data privacy protection throughout the entire TD procedure or suffer from low practicability. In this paper, we propose two schemes: a basic privacy-aware TD scheme (BPTD) and a privacy-enhanced TD scheme (PETD) with two servers for mobile crowdsensing, comprehensively considering both privacy and practicability. BPTD is straightforwardly conducted on shared data with few user-side interactions, while achieving high efficiency. To further liberate mobile users and prevent disclosure of the intermediates, PETD incorporates a novel partial decryption-based Paillier Cryptosystem to work with secret sharing, offering enhanced privacy protection without relying on any user-side involvement. Additionally, we improve the efficiency of PETD via data packing. Security analysis shows the desired privacy goals. Compared to prior studies with the best security guarantees, our extensive experiments demonstrate a comparable and superior performance regarding different metrics.

The ubiquity of crowdsourcing has reshaped the static sensor-enabled data sensing paradigm with cost efficiency and flexibility. Still, most existing triangular crowdsourcing systems only work under the centralized trust assumption and suffer from various attacks mounted by malicious users. Although incorporating the emerging blockchain technology into crowdsourcing provides a possibility to mitigate some of the issues, how to concretely implement the crucial components and their functionalities in a verifiable and privacy-aware manner remains unaddressed. In this article, we present BRPC, a blockchain-based decentralized system for general crowdsourcing. BRPC integrates the confident-aware truth discovery algorithm to provide task requesters with reliable task truths while evaluating each worker’s data quality. To mitigate the biased evaluation of malicious requesters, we propose a privacy-aware verification protocol leveraging the threshold Paillier cryptosystem, with which a certain number of workers can collaboratively verify the evaluation results without knowing any sensory data. Furthermore, we define the three roles of a user and elaborate a comprehensive reputation evaluation model enforced by smart contracts for its trustworthy running. Financial and social incentives are both offered to motivate users’ honest participation. Finally, we implement a prototype of BRPC and deploy it on the Ethereum blockchain. Theoretical analyses and experiment results show its security and practicality.

The early development of blockchain technology (BCT) has already demonstrated the technology's potential to serve the needs of different industries. BCT has also become established as a popular research topic in different scientific disciplines. This paper aims at introducing how several relevant scientific disciplines—supply chain management; management, economics and finance; computer science; security engineering—see the research and education perspectives for BCT. A field review is conducted to present challenges and opportunities of BCT, as well as suggestions for future research and education on the topic as seen from the selected different perspectives. The paper also presents methods for combining relevant disciplines in a modular online course to address the stated challenges and promote interdisciplinary blockchain education.

Privacy-preserving authentication is designed to protect vehicular ad-hoc networks (VANETs) from illegitimate users and fake messages while maintaining the privacy of legitimate users’ identities. However, existing authentication schemes have disadvantages such as non-transparent certificate issuance and revocation, high identity authentication and certificate revocation overhead. In this paper, we propose an efficient privacy-preserving authentication scheme with on-chain certificate management (PACM) in VANETs, where the service manager (SM) of each domain serves as a node of the blockchain to build a distributed system. Specifically, based on elliptic curve cryptography (ECC) and exclusive-OR operations, we achieve secure and lightweight mutual authentication between vehicles and roadside units (RSUs) by regularly updated pseudonyms. Then, we adopt the blockchain to record the issuance and revocation of all certificates, which makes SM’s activities transparent. Moreover, we introduce the counting garbled bloom filter (CGBF) to enable fast query and revocation of certificates. Besides, we design a non-forgeable and non-repudiable billing mechanism based on the hash chain technology. Security analysis and experimental results show that PACM achieves stronger security with less overhead.