Abstract With the widespread adoption of smart devices, vast amounts of multidimensional data are continuously generated across various sectors. Integrating and evaluating this data can provide strong support for decision-making. However, existing aggregation schemes face several challenges when handling multidimensional data tasks from multiple requesters, including single points of failure, privacy leakage, lack of result validation, and inefficiency. This paper mitigates the challenges by integrating packed secret sharing, Kate, Zaverucha and Goldberg (KZG) commitments and the Chinese Remainder Theorem to design a data aggregation scheme. For the first time, we achieve both multi-task and multi-dimensional data aggregation within a single data transmission, ensuring data integrity and privacy, while keeping the overhead minimal. Users can provide data for only certain dimensions, thereby safeguarding personal data privacy while emphasizing the user-centric approach to data control. By incorporating multiple fog nodes (FN) and blockchain, the data aggregation scheme is implemented in a decentralized manner. Both data users and FNs are accountable, ensuring the data authenticity and the correctness of the aggregation process. Moreover, it is fault-tolerant, making the system robust. Rigorous security analysis and extensive experimental evaluations demonstrate that the proposed approach excels in computational efficiency.

Abstract Can a dealer share a secret without knowing the shareholders? We provide a positive answer to this question by introducing the concept of an attribute-based secret sharing (AB-SS) scheme.With AB-SS, a dealer can distribute a secret based on attributes rather than specific individuals or shareholders. Only authorized users whose attributes satisfy a given access structure can recover the secret. Furthermore, we introduce the concept of attribute-based publicly verifiable secret sharing (AB-PVSS). An AB-PVSS scheme allows external users to verify the correctness of all broadcast messages from the dealer and shareholders, similar to a traditional PVSS scheme. Additionally, AB-SS (or AB-PVSS) distinguishes itself from traditional SS (or PVSS) by enabling a dealer to generate shares according to an arbitrary monotone access structure.To build an AB-PVSS scheme, we first implement a decentralized ciphertext-policy attribute-based encryption (CP-ABE) scheme, though not a fully-fledged one.We then incorporate non-interactive zero-knowledge (NIZK) proofs to enable public verification of the CP-ABE ciphertext. Based on the CP-ABE and NIZK proofs, we construct an AB-PVSS primitive.Finally, we conduct security analysis and comprehensive experiments on the proposed CP-ABE and AB-PVSS schemes. The results demonstrate that both schemes exhibit plausible performance compared to related works.

Traditional email systems rely on centralized servers for message storage and routing, making them vulnerable to single points of failure and privacy breaches. While blockchain technology has emerged as a decentralized alternative for internet infrastructure, its application to email systems remains underexplored. This paper fills the gaps by proposing a blockchain-based mailing system that eliminates trusted intermediaries while enhancing privacy. Our approach integrates four key components: (1) the ECIES scheme to ensure end-to-end confidentiality of email content, (2) BIP-32-derived addresses to achieve sender anonymity, (3) stealth addresses to provide receiver k-anonymity, and (4) a broadcast encryption scheme to enable efficient broadcast messaging. Moreover, our design allows the sender to prove membership in the broadcast mailing while preserving anonymity. Further, the proposed system introduces an incentive mechanism that allows recipients to charge fees for incoming emails, effectively discouraging spam. We present a proof-of-concept implementation on the Ethereum blockchain and evaluate its on-chain performance in terms of gas consumption. Experimental results demonstrate the practicality and efficiency of the proposed system.

As Large Language Model (LLM) agents emerge as intelligent coordinators, they intensify the demand for secure sharing and forwarding of sensitive data in data-driven systems. Existing Attribute-Based Proxy Re-Encryption (ABPRE) offers fine-grained access control and secure data forwarding, but suffers from the key escrow problem and lacks efficient verifiability and fairness guarantees. In this paper, we propose the first Verifiable and Fair Registered ABPRE (VF-RABPRE) scheme to eliminate reliance on trusted authorities and support multi-hop re-encryption for flexible multi-agent data sharing. To ensure efficient verifiability and fairness, we combine a lightweight verifiable tag and a non-interactive zero-knowledge proof to detect misbehavior of the proxy and prevent false accusations. As a trade-off between security and overhead, we design a more secure fairness mechanism that does not reveal plaintext using zero-knowledge Succinct Non-interactive Arguments of Knowledge (zkSNARK). Additionally, we extend VF-RABPRE with dynamic user registration and outsourced decryption, supporting flexible registration and efficient decryption for data users. Finally, we formally prove the security of our scheme and implement a prototype to evaluate its performance. Experimental results demonstrate that VF-RABPRE outperforms state-of-the-art ABPRE schemes and achieves practical efficiency, making it well-suited for secure data sharing in scenarios empowered by LLM agents.

Accurate blastocyst grading is essential for maximizing single-embryo transfer success in in vitro fertilization (IVF). We present BlastocystMask-DINO (BM-DINO), a two-stage framework. In Stage I, a deterministic mask generator produces four-class masks from raw day-5 microscopy images at zero labeling cost. In Stage II, these masks drive a parameter-free Region of Interest (ROI)-guided pooling and are also processed by a maskencoder CNN to extract structural priors. Therefore, prompt tokens, ROI-guided features, and mask-derived structural priors are fused additively to integrate global context, local focus, and morphological cues. Particularly, we leverage pretrained DINOv2, an unsupervised vision transformer, as the backbone and fine-tune the last four blocks to adapt the model efficiently to blastocyst grading. When evaluated on the public Human Blastocyst Dataset (HBD), BM-DINO achieves macro-F1 scores of 0.78 for expansion (EXP), 0.80 for inner cell mass (ICM), and 0.73 for trophectoderm (TE). Our model exceeds expert consensus by 6% on ICM and 2% on TE, achieving state-of-the-art performance. Also, it outperforms prior works in delivering the most balanced performance across all grading tasks. The entire approach adds only 0.07 M trainable parameters and runs end-to-end in$\approx 0.24\mathrm{s}$on commodity hardware (233ms CPU +8ms GPU), making the system suitable for real-time deployment in IVF laboratory. The implementation source code and underlying dataset are available at https://github.com/WFJKh/BM-DINO.

Achieving a fair exchange between two mutually distrusting parties presents significant obstacles. The involvement of trusted third parties is often essential to ensure fairness in such exchanges. In this paper, we propose a blockchain-driven optimistic fair exchange protocol based on publicly verifiable secret sharing (PVSS) and zero-knowledge succinct non-interactive arguments of knowledge (zkSNARKs). In our solution, arbiters, i.e., PVSS shareholders, serve as decentralized trusted third parties, registering on smart contracts with both autonomy and accountability. We assume a majority of arbiters are honest, ensuring that adversaries cannot successfully collude and that the fairness of the exchange protocol is upheld. In cases where both exchange parties are honest, the involvement of arbiters is unnecessary, making the fair exchange protocol optimistic. Additionally, we leverage zkSNARKs to generate non-interactive zero-knowledge (NIZK) proofs that ensure the correctness of the exchanged data. As a result, the exchange protocol is publicly verifiable without revealing any information about the exchanged data. In abnormal cases where arbiters are involved, a threshold number of them can fairly resolve the dispute between the seller and the buyer, and earn digital assets as a reward. In addition to fairness, optimism, and public verifiability, the proposed protocol also ensures completeness, termination, and privacy. Finally, we conduct experiments to illustrate the correctness and feasibility of the optimistic fair exchange protocol.

With the widespread application of federated learning in sensitive domains such as healthcare and finance, preserving the privacy of participants’ local data while maintaining model performance has become a critical challenge. Existing secure aggregation schemes based on homomorphic encryption or pairwise masking still suffer from substantial computational and communication overhead. To address this problem, this paper presents RESA, an efficient secure aggregation protocol based on Ring Learning with Errors (RLWE) encryption. By replacing pairwise masking with the RLWE-based encryption scheme, gradients can be efficiently encrypted and decrypted. Furthermore, by combining Paillier homomorphic encryption with the homomorphic pseudorandom generator (HPRG) to aggregate all clients’ RLWE keys, our scheme effectively protects the privacy of honest clients. Also, the proposed protocol is resilient to client dropouts due to the application of secret sharing. The experimental results show that the proposed protocol achieves 5-10× speedup in the server-side computation, compared to Bell et al. (USENIX Security’23).

As a global virtual environment, the metaverse poses various challenges regarding data storage, sharing, interoperability, and privacy preservation. Typically, a trusted third party (TTP) is considered necessary in these scenarios. However, relying on a single TTP may introduce biases, compromise privacy, or lead to single-point-of-failure problem. To address these challenges and enable secure data exchange in the metaverse, we propose a system based on decentralized TTPs and the Ethereum blockchain. First, we use the threshold ElGamal cryptosystem to create the decentralized TTPs, employing verifiable secret sharing (VSS) to force owners to share data honestly. Second, we leverage the Ethereum blockchain to serve as the public communication channel, automatic verification machine, and smart contract engine. Third, we apply discrete logarithm equality (DLEQ) algorithms to generate non-interactive zero knowledge (NIZK) proofs when encrypted data is uploaded to the blockchain. Fourth, we present an incentive mechanism to benefit data owners and TTPs from data-sharing activities, as well as a penalty policy if malicious behavior is detected. Consequently, we construct a data exchange framework for the metaverse, in which all involved entities are accountable. Finally, we perform comprehensive experiments to demonstrate the feasibility and analyze the properties of the proposed system.

Data sharing is ubiquitous in the metaverse, which adopts blockchain as its foundation. Blockchain is employed because it enables data transparency, achieves tamper resistance, and supports smart contracts. However, securely sharing data based on blockchain necessitates further consideration. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising primitive to provide confidentiality and fine-grained access control. Nonetheless, authority accountability and key abuse are critical issues that practical applications must address. Few studies have considered CP-ABE key confidentiality and authority accountability simultaneously. To our knowledge, we are the first to fill this gap by integrating non-interactive zero-knowledge (NIZK) proofs into CP-ABE keys and outsourcing the verification process to a smart contract. To meet the decentralization requirement, we incorporate a decentralized CP-ABE scheme into the proposed data sharing system. Additionally, we provide an implementation based on smart contract to determine whether an access control policy is satisfied by a set of CP-ABE keys. We also introduce an open incentive mechanism to encourage honest participation in data sharing. Hence, the key abuse issue is resolved through the NIZK proof and the incentive mechanism. We provide a theoretical analysis and conduct comprehensive experiments to demonstrate the feasibility and efficiency of the data sharing system. Based on the proposed accountable approach, we further illustrate an application in GameFi, where players can play to earn or contribute to an accountable DAO, fostering a thriving metaverse ecosystem.

Abstract Fair exchange is a challenging problem for two mutually distrusting players. It is widely known that fair exchange is impossible without a trusted third party (TTP). However, relying on a single TTP can cause a single-point failure. An intuitive idea is to adopt multiple TTPs to distribute trust. This paper constructs a two-party optimistic fair exchange (OFE) protocol using decentralized ciphertext-policy attribute-based encryption (CP-ABE), achieving decentralized TTPs. This is achievable because decentralized CP-ABE ciphertext supports a nested access control policy. A nested access control policy fits perfectly in a fair exchange protocol which contains multiple roles (i.e. players and TTPs). Further, we apply non-interactive zero knowledge proofs to prove the well-formedness of ciphertexts, so as to enforce players to follow the protocol specification honestly. Consequently, we construct an OFE protocol in which each player’s operations are publicly verifiable without revealing secret information. Also, we obtain decentralized TTPs with optimism (i.e. the TTPs are involved only when arbitration is required), autonomy (i.e. the TTPs do not need to interact with each other), statelessness (i.e. the TTPs do not need to store data for the exchange protocol) and verifiability (i.e. the TTPs are publicly verifiable). Compared with previous work, our protocol assumes only a public communication channel and each party’s operations are publicly verifiable. Besides, it achieves a favorable $O(n)$ verification complexity in the normal case, where $n$ is the number of TTPs. Finally, we present a proof-of-concept implementation to demonstrate the feasibility.

Secure and efficient healthcare data sharing plays a key role in cross-enterprise document sharing (XDS). However, security management for healthcare data is equally important. The emergence of blockchain technology is a great solution for healthcare data sharing. However, the problem that incorrect messages are permanently preserved in the blockchain must be considered. Fortunately, the redactable blockchain is an effective solution. The redactable blockchain allows for modifying incorrect data stored on the blockchain. In this paper, we propose a safe, effective, and patient-centered medical data sharing and revision framework based on a redactable blockchain. Firstly, we leverage ciphertext-policy attribute-based encryption (CP-ABE) scheme to enable data-sharing on blockchain. Then, we introduce the chameleon hash function to achieve a data revision mechanism that enables the modification of incorrect historical medical records. At the same time, we adopt a verifiable secret sharing (VSS) scheme to decentralize the revision privilege in order to eliminate the single-point failure problem. Further, we show the feasibility and practicality of our framework by conducting comprehensive experiments.

Edge computing fundamentally changes the architecture in which applications are deployed and how resources are managed, especially in the 5G/6G era. Automated guided vehicles (AGV) are critical means of transportation in future society. We aim at investigating a privacy-preserving AGV collision-resistance paradigm leveraging edge computing. We define a model containing all potential collision occasions and propose a method to handle collisions using “virtual” traffic lights generated by edge servers. The proposed paradigm is AGV-centered, for AGVs ought not to care about where the nearby edge servers are in a broadcasting environment. In case of privacy leakage, we incorporate ciphertext-policy attribute-based encryption (CP-ABE) to protect AGV information. Besides, the use of CP-ABE leads to a location-based encryption (LBE) scheme, where AGV encrypts its running state information leveraging its current position rather than an edge server's public key. That is achievable due to the support of integer comparison in the CP-ABE access policy. To our knowledge, we are the first to implement an LBE scheme based on CP-ABE. Part of the paradigm has been deployed in a wharf yard in Shanghai. Throughout the article, we take a yard as an example and conduct concrete experiments to highlight the feasibility and efficiency.

Patient-centered healthcare data sharing and data usage consent are gaining popularity. Cross-enterprise document sharing (XDS) is the crucial system of sharing personalized healthcare data. Furthermore, dynamic consent is vital to the XDS system, because it respects people's autonomy and achieves recognition of data sovereignty. Because of its transparency, blockchain is a powerful system for managing storage and computing without a trusted third party. Besides, ciphertext-policy attribute-based encryption (CP-ABE) extends public-key encryption by implying access control policies in ciphertexts, making it suitable for protecting the privacy of individual healthcare data in versatile cases. Particularly, we use hospital name, "date" and "department" as attribute strings in the access control policies. Consequently, based on consortium blockchain and CP-ABE, we propose a patient-centered XDS and a dynamic consent framework. Compared with previous related literature, we make the proposed framework consistent with current practices and achieve favorable criteria, such as data confidentiality, data recoverability and time-aware ciphertext. Further, we conduct comprehensive experiments to show the feasibility and practicality.

We aim at building a generic future-generation, secure communication framework on top of blockchain using signcryption. A publicly verifiable signcryption scheme not only ensures data confidentiality and authentication, but also enables messages to be verified or audited non-interactively. With blockchain as trustworthy computation and storage services, the proposed secure communication framework achieves tamper-resistance, non-repudiation, availability and public verification. Moreover, we consider both large-size data (e.g., file) and small-size data (e.g., cryptographic hash or key) transfer paradigms, where blockchain and signcryption schemes are seamlessly combined. In particular, IPFS is used as a hash oracle and decentralized storage platform in big data transfer.

Distributed key generation (DKG) is widely used in multi-party computation and decentralized applications. DKG has two phases, namely sharing and reconstruction. Most of the prior DKG protocols need at least 2 rounds for the sharing phase, in case some party raises a dispute. The existing 1-round DKG protocol [Fouqueet al., PKC’01], built based on a publicly verifiable secret sharing (PVSS) scheme, assumes a static adversary model and its reconstruction phase requires$O(n^{2})$communication complexity. Motivated by the observation that a ciphertext-policy attribute-based encryption (CP-ABE) scheme hides secret sharing (SS) in ciphertext, we utilize decentralized CP-ABE to achieve the first adaptively secure 1-round DKG protocol. Firstly, a CP-ABE scheme enables the ciphertexts in DKG to be externally decrypted, making our protocol superior to the PVSS-based DKG protocol in reconstruction. The communication and computation complexities are both lowered to$O(n)$thanks to the constant-sized decryption key and the proposed batch decryption. The use of CP-ABE also makes our DKG protocol storage-friendly, i.e., the parties store no ciphertext after the sharing phase. Secondly, we add non-interactive zero-knowledge (NIZK) proofs to make the CP-ABE ciphertext publicly verifiable by leveraging the sigma protocol and the Fiat-Shamir heuristic. Thirdly, we demonstrate our protocol’s feasibility by presenting a proof-of-concept implementation over Ethereum, which is used as a public channel and a trustworthy computation platform. The implementation is a non-trivial task due to Ethereum’s incompatibility with the bilinear mapping group.