Over the years, the flourish of crowd computing has enabled enterprises to accomplish computing tasks through crowdsourcing in a large-scale and high-quality manner, and therefore how to efficiently and securely implement crowd computing becomes a hotspot. Some recent work innovatively adopted a P2P (peer-to-peer) network as the communication environment of crowdsourcing. Based on its decentralized control, issues like single-point-of-failure or DDoS attack can be overcome to some extent, but the huge computing capacity and storage costs required by this scheme is always unbearable. Federated learning is a distributed machine learning that supports local storage of data, and clients implement training through interactive gradient values. In our work, we combine blockchain with federated learning and propose a crowdsourcing framework named CrowdSFL, that users can implement crowdsourcing with less overhead and higher security. In addition, to protect the privacy of participants, we design a new re-encryption algorithm based on Elgamal to ensure that interactive values and other information will not be exposed to other participants outside the workflow. Finally, we have proved through experiments that our framework is superior to some similar work in accuracy, efficiency, and overhead.

Access control in Internet of Things (IoT) systems has long been facing with single-point-of-failure, collusion and other security issues. Deploying most of the access control procedures on blockchain makes it more trustworthy. However, the miscellaneous transaction data on the public blockchain incurs an extra burden on computing and communication overhead, which hinders its application for IoT devices. Additionally, the demands of rapid response in industrial IoT scenarios (e.g., edge computing scenarios) is hardly realized under a public blockchain. In this paper, we propose an IoT-applicable access control model under an original double-layer blockchain architecture, in which the mortgage/registration and control processes can be disaggregated. Depending on this architecture, the communication overhead for IoT devices is reduced and a rapid response is achieved. With linear secret sharing scheme, attribute-based access policies for resource objects are established to ensure fine-grained access control. We further implement a smart contract prototype on Ethereum and Fisco Bcos. Extensive experiments and numerical analysis demonstrate the feasibility of our proposed model.

With the rapid development of physical networks, tens of billions of Internet of Things (IoT) devices have been deployed worldwide. Access control is essential in the IoT system, which manages user access to vital IoT data. However, access control for the IoT is mainly based on centralized trusted servers, which face problems such as a single point of failure and data leakage. To tackle these challenges, we propose an access control framework for the IoT by combining blockchain and Intel software guard extension (SGX) technology. A blockchain validates both IoT devices and edge servers added to the network. The access control contract is deployed on the blockchain, which can manage attribute-based access control policies in a fine-grained manner and make access control decisions flexibly. SGX technology is introduced into the edge computing server to realize the confidentiality of data processing. Finally, we implemented the prototype of the framework on Quorum and conducted extensive experiments and theoretical analyses on the performance of the blockchain. The results of the experimental tests and theoretical analyses show that our framework has more advantages in computing costs and on-chain storage costs.

Searchable encryption enables users to enjoy search services while protecting the security and privacy of their outsourced data. Blockchain-enabled searchable encryption delivers the computing processes that are executed on the server to the decentralized and transparent blockchain system, which eliminates the potential threat of malicious servers invading data. Recently, although some of the blockchain-enabled searchable encryption schemes realized that users can search freely and verify search results, unfortunately, these schemes were inefficient and costly. Motivated by this, we proposed an improved scheme that supports fine-grained access control and flexible searchable encryption. In our framework, the data owner uploads ciphertext documents and symmetric keys to cloud database and optional KMS, respectively, and manipulates the access control process and searchable encryption process through smart contracts. Finally, the experimental comparison conducted on a private Ethereum network proved the superiority of our scheme.