Ke Huang

The Internet of Medical Things (IoMT) enables large-scale sensing and cloud-based sharing of sensitive medical data, where access control must remain fine-grained, dynamic, and robust. In practical healthcare scenarios, access privileges frequently change due to real-world incidents such as physician resignation, role reassignment, emergency response, or patient consent withdrawal, which require both user-level and attribute-level revocation mechanisms. To address these challenges, we propose a Dual Revocable CP-ABE (DABE) scheme that unifies direct and indirect revocation within a single framework, to support diverse medical data sharing scenarios. The proposed system allows data owners to flexibly select revocation modes based on operational needs: indirect revocation efficiently handles large-scale updates for remote medical records via a semi-trusted cloud server, while direct revocation enables immediate access termination through ciphertext updates for highly sensitive data. This dual-mode design improves system robustness and fault tolerance, thus avoiding a single point of failure. Moreover, DABE supports verifiable outsourced decryption to accommodate resource-constrained IoMT devices. Formal security analysis proves IND-CPA security and resistance to collusion attacks, while experimental results demonstrate practical efficiency: the decryption time remains nearly constant (approximately 15–20 ms) regardless of policy complexity, achieving an improvement of over two orders of magnitude compared to existing schemes, with only modest overhead in other phases. These results show that DABE is well-suited for large-scale, dynamic IoMT systems.

Ateniese et al. (EuroS&P 2017) proposed the notion of redactable blockchains (RBs), in which a designated party uses a secret key to modify blockchain history without causing a hard fork. Nevertheless, redactions may be performed mistakenly or maliciously due to misbehavior or operational errors. From a regulatory perspective, any RB design must therefore incorporate accountability and traceability mechanisms to ensure that redactions are non-abusive and publicly verifiable. As a countermeasure, we propose the notion of time-updatable policy-based chameleon hash (TPCH). This construction addresses regulatory concerns by enabling publicly verifiable proofs of redaction and traceable user identities. Our basic building block, termed time-updatable chameleon hash (TUCH), provides redaction accountability through an intrinsic property formalized as Type-2 Trapdoor Collisions. TUCH is functionally versatile and achieves acceptably efficient performance compared to peer chameleon hash schemes. Following the heuristics of Camenisch et al. (PKC 2017) and Derler et al. (NDSS 2019), we further extend TUCH by integrating attribute-based encryption (ABE) to obtain a time-updatable, policy-based variant, namely TPCH. The resulting scheme overcomes the limitations of coarse-grained redaction and the impracticality of specifying the exact modifier in advance. Overall, TPCH provides a secure, efficient, and comprehensive solution for accountable and traceable redactable blockchains under practical regulatory requirements. Our systematic analysis further demonstrates the suitability of TPCH for small scale deployment.

Internet of Things (IoT) revolutionizes data collection, especially in e-healthcare, where patients data from wearables and sensors improves medical services. However, IoT’s limitations in computing and storage require cloud outsourcing. Combining IoT with the cloud has potential but raises concerns about data security. Leveraging cloud storage presents an attractive solution for accommodating the substantial volume of data outsourced by IoT devices. As the outsourcing of real-time data to cloud storage becomes commonplace, the adoption of data auditing schemes emerges as a means to ensure data integrity. To curtail operational expenses, various deduplication techniques are commonly employed on outsourced data, effectively sidestepping redundant data and resulting in storage and bandwidth efficiencies. Although real-time data typically remains distinct due to its diverse origins, scenarios such as data sharing or trading in data-driven services and datamarkets can lead to data redundancy. Moreover, in order to fortify against any potential information leakage, encryption is implemented prior to deduplication. Convergent Encryption (CE) stands as a prominent exemplar of this approach. Effectively integrating data auditing, deduplication, and encryption for wireless sensor devices is no trivial task. To efficiently and securely accommodate data while authenticating them through a heterogeneous framework, we present a novel remote data checking scheme, denoted as the VRDC scheme. This scheme empowers IoT data to be encrypted, updated, deduplicated, and audited, aligning with the imperatives of security, privacy, and efficiency. Through comprehensive security analysis, we establish that our VRDC scheme is fortified against potential threats. Our experimental findings highlight the efficiency of our approach in the realms of auditing, deduplication, and updates. Furthermore, the evidence highlights the potential for optimization within our scheme when compared to related works. This is achieved through the careful management of dynamic update scales within a file.

Monero is a privacy-centric cryptocurrency that allows users to obscure their transactions with multiple input and output addresses. Current research on Monero mainly focuses on identifying design vulnerabilities or optimizing towards stronger privacy, security, etc. For example, improving the design of ring confidential transaction (RingCT) protocol proposed by Noether et al. As revealed by Ali et al. in USENIX 2016, new blockchains have inadequate nodes and network computing resources to resist powerful attack (e.g. 51% attack). Obviously, Monero blockchain is not an exception. Ateniese et al. proposed the notion of redactable blockchain in EuroS&P 2017, which begins the trend of formalizing blockchain with extra cryptographic primitives. The motivation is to turn an immutable blockchain into a mutable ledger by adapting the blockchain design and integrating with new cryptographic schemes. In such a setting, users could use their private keys to perform the secure multi-party computation to reverse blockchain history. The idea of redactable blockchain has attracted many researchers to pursuit this topic. However, few works have considered the privacy-preserving setting. Even fewer have practised their designs in an actual cryptocurrency. In this paper, we seek to adapt the RingCT protocol with several building blocks. Our proposal achieves most of the desired properties for blockchain redaction. It allows multiple tracing authorities to collaboratively trace users' identities, and a system manager to perform multi-grained (including block-level, transaction-level, accumulator-level and commitment-level) redaction on block contents. Our proposal can be seen as an extension of RingCT protocol. We give rigorous security requirements and comprehensive analysis of our scheme. The performance evaluation suggested that our scheme suffers from some unscalabilities in large-scale implementations. A more elegant design to achieve stronger security and ideal scalability is deemed as a challenging and interesting future work.

The integration of Internet of Things (IoT) and cloud computing are always seen as promising technologies to enhance streamlined data collection, share and exchange. Although the advances in edge computing, particularly mobile edge computing (MEC), could enhance the performance of data collection and computation via computing offloading, security and privacy impediments have made new challenges to data integrity and confidentiality, in particular when multiple edges or nodes at different locations collect IoT data. Homomorphic encryption therefore has shown promising advantages for cloud computing, offering arithmetic operations to be carried out on the encrypted data without revealing the secret key. While fully homomorphic encryption introduced by Gentry, in 2009, allows both additive and multiplicative operations, it has shown significant implementation drawbacks due to the parameters generation and memory consumption. In this work, we focus on partially homomorphic encryption, which can be efficiently computed. However, it is challenging to add authentication feature for the verification and aggregation capability. We propose a novel secure and privacy preserving authenticable homomorphic encryption (AHEC) scheme. We demonstrate an application of our AHEC scheme for MEC-based IoT systems and provide security analysis to prove that our scheme is secure against chosen plaintext attack (IND-CPA) and unforgeability (UNF) under DDH-ZN2 and Lift-DH-ZN2 assumptions. Experimental results show that our proposed scheme is efficient for practical applications.

Cloud storage is an ideal platform to accommodate massive data. However, with the increasing number of various devices and improved processing power, the amount of generated data is becoming gigantic. Therefore, this calls for a cost‐effective way to outsource massively generated data to a remote server. Cloud service providers utilise deduplication technique which deduplicates redundant data by aborting identical uploading requests and deleting redundant files. However, current deduplication mechanisms mainly focus on the storage saving of the server, and ignore the sustainable and long‐term financial interests of servers and users. This is not helpful to expand outsourcing and deduplication services. Blockchain is an ideal solution to achieve an economical and incentive‐driven deduplication system. Though some current research studiess have integrated deduplication with blockchain, they did not utilise blockchain as a financial tool. Meanwhile, it lacks an arbitration mechanism to settle disputes between the server and the user, especially in a Bitcoin payment where the payment is not confirmed immediately and a dispute may occur. This creates a burden to achieve fair and transparent incentive‐based deduplication service. In this work, we construct a deduplication system with financial incentives for the server and the user based on Bitcoin. The data owner will pay money via Bitcoin to the server for outsourcing the file, but this fee can be compensated by charging deduplication users with some fees to acquire the deduplication service. The server and the user can receive revenues using deduplication service. Disputes on the fair distribution of incentives can be settled by our arbitration protocol with chameleon hashes as arbitration tags. We give concrete construction and security requirements for our proposed . The security analysis shows that our is theoretically secure. The performance evaluation shows that our proposed is acceptably efficient for the deduplication. Meanwhile, we evaluate and conclude that 1% of outsourcing fee (or less) is a reasonable and preferable price for each deduplication user to pay as compensation for data owner.

Electronic auction is a popular platform to sell goods, task assignment, and resources’ allocation due to reductions of transaction costs and has attracted a huge number of potential buyers. However, it is challenging to address the disputes between the buyer and the auctioneer. The main reason is, on the one hand, solving such problem leverages to the broad domain of research aspects, such as economic theory, engineering, and cryptography, and, on the other hand, it is difficult to arbitrate in a decentralized and anonymous setting. In this work, we consider a more general framework to solve the potential disputes by enforcing bidirectional confirmation and public verification. Hence, the bidding procedure is clear to inspect and potential disputes can be erased. To achieve this goal, we propose policy-driven chameleon hash and revised linkable-and-redactable ring signature as building blocks. We used these two tools to build a bidirectional and anonymous auction protocol called P. In our P protocol, the bidders can competitively and anonymously place their bids to outbid others. At the end of the auction protocol, everyone can verify the validity of the bidding proof and decide the winner. Thus, dispute-freeness feature is achieved. The analysis suggests that our proposal is provably secure and practically efficient, and it trades some efficiencies with dispute-freeness feature.

Cloud computing has promoted the success of Internet of Things (IoT) with offering abundant storage and computation resources where the data from IoT sensors can be remotely outsourced to the cloud servers, whereas storing, exchanging and processing data collected through IoT sensors via centralised or decentralised cloud servers make cloud-based IoT systems prone to internal or external attacks. To protect IoT data against potential malicious users and adversaries, some cryptographic schemes have been applied to ensure confidentiality and integrity of IoT data. It is however a challenging task to perform any arithmetical computations once data items are encrypted. Fully-homomorphic encryption which is based on lattices can, in principle, provide a solution, but it is unfortunately inefficient in computation and hence cannot be applied to IoT. Fully-homomorphic encryption is feasible when we allow an involvement of semi-trusted server. However, it is challenging to provide such a system in the situation of distributed environments for shared IoT data. We solve this problem and provide a fully-homomorphic encryption scheme for cloud-based IoT applications. We introduce a new method with the aid of semi-trusted server who can help in the computation of the homomorphic multiplications without gaining any useful information of the encrypted data.

The captured data from smart devices via Internet of Things (IoT) wireless sensors are vulnerable to numerous online and offline attacks and unauthorized accesses, hence, some digital signature and encryption solutions have been designed to ensure public verifiability, data integrity, and confidentiality. However, there are still some issues to be addressed. For example, the data source is revealed to the public due to the public verifiability of digital signatures, in which authentication is transferrable. Moreover, computation of these data can only be done after decryption, restricting outsourced computation, such as a computing facility from a cloud. The best approach of private computation, which supports outsourced computation, is based on homomorphic encryption. However, significant computational overhead is a concern. To deal with these issues, in this article, we propose an efficient and provably secure scheme based on designated-verifier proofs, deniable authentication and homomorphic encryption for secure and lightweight data collection, batch verification, and data analysis in the privacy-preserved IoT wireless sensors applications. The main contribution of our work is the privacy-preserved IoT wireless sensors system along with a novel deniable authenticated homomorphic encryption scheme that can securely aggregate data from IoT wireless sensors for secure outsourced applications. To prove the security and efficiency of our proposed scheme, we provide formal security analysis and performance comparisons for IoT wireless sensors.