Proof of work (PoW), the most popular consensus mechanism for blockchain, requires ridiculously large amounts of energy but without any useful outcome beyond determining accounting rights among miners. To tackle the drawback of PoW, we propose a novel energy-recycling consensus algorithm, namely proof of federated learning (PoFL), where the energy originally wasted to solve difficult but meaningless puzzles in PoW is reinvested to federated learning. Federated learning and pooled-mining, a trend of PoW, have a natural fit in terms of organization structure. However, the separation between the data usufruct and ownership in blockchain lead to data privacy leakage in model training and verification, deviating from the original intention of federal learning. To address the challenge, a reverse game-based data trading mechanism and a privacy-preserving model verification mechanism are proposed. The former can guard against training data leakage while the latter verifies the accuracy of a trained model with privacy preservation of the task requester's test data as well as the pool's submitted model. To the best of our knowledge, our article is the first work to employ federal learning as the proof of work for blockchain. Extensive simulations based on synthetic and real-world data demonstrate the effectiveness and efficiency of our proposed mechanisms.

The Internet of things (IoT) changed our lives with a huge amounts of data production. Due to source-limited IoT devices, one of the best ways to process the data is the cloud storage. However, a series of security and privacy issues arise, such as illegal data access, data tampering and privacy leak. Though symmetric encryption can guarantee the data confidentiality, it cannot realize fine-grained data sharing and searching. The keyword-based searchable attribute-based encryption (KSABE) can achieve the data confidentiality and fine-grained access control. More importantly, it realizes keyword-based search for data users. However, the heavy decryption computation burden and the management of massive user keys appear when implement ABE schemes to IoT. Therefore, this paper proposes a blockchain-aided searchable attribute-based encryption (BC-SABE) with efficient revocation and decryption. Where the traditional centralized server is replaced with a decentralized blockchain system being in charge of the threshold parameter generation, key management and user revocation. All revocation tasks are done by the blockchain and it is on longer necessary for ciphertext re-encryption and key update. Moreover, users utilize the coalition blockchain to generate partial tokens. Besides, the cloud server contained in our scheme not only stores the massive encrypted data, but also performs search and pre-decryption for users who only require one exponentiation in the group G to decrypt fully. Security analyses prove that our scheme realizes the security under the chosen plaintext attack and the chosen keyword attack. Simulations show that the decryption and token generation cost of our scheme are preferable.

IoT-based E-commerce is a new business model that relies on autonomous transaction management on IoT-devices. The management system towards IoT-based E-commerce demands autonomy, lightweight and legitimacy. As blockchain is an innovative technology that is competent in governing the decentralized network, we adopt it to design the autonomous transaction management system on IoT E-commerce. However current blockchain solutions, most namely cryptocurrencies, have fatal drawbacks of non-supervisability and huge computational overhead, and hence cannot be directly applied on IoT-based E-commerce. In this paper, we propose NormaChain, a blockchain-based normalized autonomous transaction settlement system for IoT-based E-commerce. By designing a special three-layer sharding blockchain network, we can significantly increase transaction efficiency and system scalability. Additionally, by designing an innovative decentralized public key searchable encryption scheme (Decentralized PEKS scheme), we can uncover illegal and criminal transactions and achieve crime traceability. Our new DPEKS scheme cryptographically eliminates the dependence of a trusted central authority in the original PEKS scheme and instead expands it to a fully decentralized governance, which distributes the supervision power equally among all parties. More importantly, by proving NormaChain is secure against chosen ciphertext attacks (CCA) and against the stealing of the secret key, we show that NormaChain prevents a legitimate user’s privacy from being violated by banks, supervisors or malicious adversaries. Finally, we deliver the NormaChain system with design details and full implementations. Experiments show that the average transaction-per-second (TPS) on IoT devices is around 113, and the supervision accuracy is 100% when proper target illegal keywords are provided.

Due to the complexity and volume, outsourcing ciphertexts to a cloud is deemed to be one of the most effective approaches for big data storage and access. Nevertheless, verifying the access legitimacy of a user and securely updating a ciphertext in the cloud based on a new access policy designated by the data owner are two critical challenges to make cloud-based big data storage practical and effective. Traditional approaches either completely ignore the issue of access policy update or delegate the update to a third party authority; but in practice, access policy update is important for enhancing security and dealing with the dynamism caused by user join and leave activities. In this paper, we propose a secure and verifiable access control scheme based on the NTRU cryptosystem for big data storage in clouds. We first propose a new NTRU decryption algorithm to overcome the decryption failures of the original NTRU, and then detail our scheme and analyze its correctness, security strengths, and computational efficiency. Our scheme allows the cloud server to efficiently update the ciphertext when a new access policy is specified by the data owner, who is also able to validate the update to counter against cheating behaviors of the cloud. It also enables (i) the data owner and eligible users to effectively verify the legitimacy of a user for accessing the data, and (ii) a user to validate the information provided by other users for correct plaintext recovery. Rigorous analysis indicates that our scheme can prevent eligible users from cheating and resist various attacks such as the collusion attack.

Blockchain creates a secure environment on top of strict cryptographic assumptions and rigorous security proofs. It permits on-chain interactions to achieve trustworthy properties such as traceability, transparency, and accountability. However, current blockchain trustworthiness is only confined to on-chain, creating a ‘`trust gap’' to the physical, off-chain environment. This is due to the lack of a scheme that can truthfully reflect the physical world in a real-time and consistent manner. Such an absence hinders further blockchain applications in the physical world, especially for the security-sensitive ones. In this paper, we propose a framework to extend blockchain trust from on-chain to off-chain, and take trustworthy vaccine tracing as an example scheme. Our scheme consists of 1) a Trusted Execution Environment (TEE)-enabled trusted environment monitoring system built with the Arm Cortex-M33 microcontroller that continuously senses the inside of a vaccine box through trusted sensors and generates anti-forgery data; and 2) a consistency protocol to upload the environment status data from the TEE system to blockchain in a truthful, real-time consistent, continuous and fault-tolerant fashion. Our security analysis indicates that no adversary can tamper with the vaccine in any way without being captured. Our experiment shows a small system latency of 84 ms.

One of the best ways to deal with the massive data generated by the Internet of things (IoT) is storing them in the cloud. However outsourced storage raises some security and privacy issues such as data leaking and illegal access. The attribute-based signcryption (ABSC) is one of the most promising approaches which can ensure the confidentiality and authenticity of data simultaneously. Nonetheless, it not only inherits the fine-grained access control but also the heavy computational cost which is intolerable for most resource-limited IoT devices. In this paper, we propose LH-ABSC, a lightweight ABSC scheme which adopts ciphertext-policy encryption (CPABE) and key-policy attribute-based signature (KPABS). CPABS leads the decision-making that who can decrypt to the data owners directly. Meanwhile, the signature is related with data owners’ attribute set which can be used to testify the authenticity of data. In particular, LH-ABSC has constant signature size and satisfies public verification which is deeply important for IoT devices. Moreover, LH-ABSC outsources most computing overhead to fog nodes including signature, verify and decryption. Comprehensive theoretical analyses such as confidentiality, unforgeability and verifiability are provided. Also, the selective chosen ciphertext security, the selective chosen message security and signers anonymity are achieved.