Blockchain Technology and Emerging Applications

Functional encryption is a novel form of public key encryption that has captured significant attention since its inception, with researchers proposing a series of theoretical constructions. Functional encryption can be investigated for specific real-world applications such as the evaluation and output from the ciphertexts using the different decryption keys. In this paper, we investigate one of the more popular recent developments in functional encryption, i.e., inner product functional encryption. We address potential issues that inner product functional encryption might encounter in certain scenarios, including the inability to specify the identity of the ciphertext recipient, privacy leakage related to the master secret key vector, and the susceptibility of the decryption key to malicious tampering. In specific contexts, there might be a requirement for ciphertext recipients to be carefully designated. Malicious adversaries holding the decryption key can exploit it to gain insight into the master key or even alter the decryption key information. Consequently, key verification becomes necessary. To address this, we propose an identity-based key verifiable inner product functional encryption scheme (IBVE-IPE), which can effectively resolve the aforementioned issues and is validated for security and practicality through security proofs and performance analyses.

Remote attestation (RA) is an essential feature in many security protocols to verify the memory integrity of remote embedded (IoT) devices. Several RA techniques have been proposed to verify the remote device binary at the time when a checksum function is executed over a specific memory region. A self-relocating malware may try to move itself to avoid being “caught” by the checksum function because the attestation provides no information about the device binary before the current checksum function execution or between consecutive checksum function executions. Several software-based that lack of dedicated hardware rely on detecting the extra latency incurred by the moving process of self-relocating malware by setting tight time constraints. In this paper, we demonstrate the shortcomings of existing software-based approaches by presenting Debug Register-based Self-relocating Attack (DRSA). DRSA monitors the execution of the checksum function using the debug registers and erases itself before the next attestation. Our evaluation demonstrates that DRSA incurs low overhead, and it is extremely difficult for the verifier to detect it.

With the widespread application of Unmanned Aerial Vehicle (UAV) technology, its security issues have also attracted much attention, among which the configuration attack against the UAV flight control system is one of the current research hotspots. Attackers always upload seemingly normal configuration combinations and cause an imbalance in the UAV state by exploiting configuration item verification vulnerabilities. This paper accumulates flight data through simulation, generates configuration combinations within the security range using differential evolution-based fuzz testing, uses neural networks to guide configuration item variants, and applies these configuration combinations to the AutoTest of UAV flight control systems. The experimental results show that the configuration combinations generated by fuzz testing can guide the UAV to course deviation, spin, crash and other unstable states; the code coverage and function coverage of the position and attitude code library base in the flight control system have also reached a high level.

Lattice-based encryption schemes derive their security from the presumed complexity of solving the Shortest Vector Problem (SVP) within the lattice structure. Numerous algorithms have been proposed to address the SVP, targeting both exact and approximate solutions. However, it is noteworthy that the time complexity associated with these algorithms predominantly exceeds polynomial bounds. This paper succinctly delineates these algorithms while providing a comprehensive summary of existing parallel implementations of sieving and enumeration methods. Furthermore, it introduces distinguished instances from the Hall of Fame of the SVP challenge.

Nowadays, e-voting systems are receiving a lot of attention. Voters can cast their votes for the candidates they support on the e-voting system. However, how to reflect the voters’ support level for the candidates in the e-voting system in a fair and privacy-preserving way is still a problem that needs to be solved. This article proposes a private support-weighted sum (PSWS) protocol, which is a fair, and privacy-preserving weighted sum protocol. The PSWS protocol privately calculates the weighted sum of each voter’s support degree for a candidate. After the protocol’s execution, others on the system can only access the weighted sum, without any additional information. The PSWS protocol has two novel characteristics. Firstly, the voting terminal or polling station provides encryption services for ballots immediately after each ballot is cast. All voting information is expressed in ciphertext throughout the weighting and counting processes, until the final result of the weighted vote is passed to the decryption server in ciphertext. This design avoids the disclosure of voter privacy and ballot information, and the ciphertext format also prevents malicious users from cheating or tampering with voter or ballot information during the counting process. Security analysis is conducted to validate security properties. Secondly, our protocol not only achieves the function of privacy-preserving support-weighted voting but also is relatively lightweight and efficient. Finally, the efficiency analysis results of the experiments in terms of calculation show that the protocol meets the requirements applicable to real-world applications. In summary, PSWS can be harmoniously applied to candidate election in blockchain systems.

Recently, numerous challenges concerning personal identity security along with other security issues regarding privacy have been introduced. While the blockchain offers a solution for recording personal information and facilitating matching needs, existing researches have indicated the absence of privacy and traceability. In this paper, we introduce an information matching scheme rooted in cross-chain technology. This approach employs a public blockchain for information matching and a consortium blockchain for transmitting private data. Cross-chain consensus protocols are leveraged to accomplish privacy protection and validation for cross-chain information transmission. The scheme serves the purpose of achieving information matching between two parties within the public blockchain framework. It enhances users’ identity and information privacy, while also bolstering the auditability of cross-chain information.

With the development of Blockchain, cloud computing, and artificial intelligence, smart transportation is highly likely to drive urban transportation in the direction of intelligence and digitalization. However, when connected vehicle devices share data in edge networks, there are security and privacy issues, e.g. leakage of sensitive information will cause serious threats. The separation of user data ownership and physical control requires users to impose access control on the outsourced data. Existing privacy protection schemes still suffer from problems such as a lack of supervision of centralized third-party cloud servers, which face the challenge of data leakage. In this paper, Blockchain and proxy re-encryption techniques are used to address these challenges. To enable sharing of the outsourced data in a secure way, Attribute-Based Proxy Re-encryption (ABPRE) is a popular technique. At the same time, verifiability enables the shared user to verify that the re-encrypted ciphertext returned by the server is correct. In addition, the introduction of a decentralized Blockchain provides distributed storage and it is tamper-proof for enhancing the trustworthiness of the connected vehicle devices as well as the security of the communication between the entities. The security and performance analyses demonstrate that our proposed scheme can achieve the desirable security features and it is efficient for protecting data privacy.

With the development of information technology, people can share their health records (PHRs) through the Internet and obtain rapid medical services, which makes mobile health become a promising field. PHRs are collected from wireless body area networks (WBANs) and will be shared with people in different fields through public channels, increasing the risk of leaking personal privacy. Ciphertext-policy attribute-based encryption (CP-ABE) is a popular solution for fine-grained access control, but most existing schemes cannot be directly applied to the WBANs with limited resources and dynamic changes in user roles. In this paper, to meet the requirement of the mHealth System, we propose blockchain-based hierarchical access control with efficient revocation in the mHealth system. We use the Extendable Hierarchical attribute-based encryption (EH-ABE), a file-related hierarchical access control scheme, to encrypt PHRs, which reduces the repetitive computation and storage overhead. The proposed scheme adds the function of offline/online encryption, which can greatly save the energy consumption of the sensors in the WBANs. In addition, this scheme can provide attribute-level user revocation and is proven to be IND-CCA secure.