The proliferation of AI-Generated Content (AIGC) within cloud-edge IoT ecosystems necessitates robust provenance mechanisms to ensure copyright protection and forensic traceability. However, the open distribution mechanism of AIGC exposes proprietary assets to risks of unauthorized replication and misuse. While watermarking offers a solution, existing schemes face a critical dilemma in IoT environments: they are either computationally expensive for edge deployment or structurally fragile against the dual threats of unpredictable IoT transmission failures and post-distribution image manipulations. To overcome these limitations, we propose Holo-Code, a robust and statistically lossless watermarking architecture based on a decoupled channel-coding paradigm. We introduce a holographic topological transformation to globally disperse watermark information across the latent representation. This mechanism mathematically converts structural data loss into uniform random erasures, which are robustly recovered via concatenated error correction coding. Furthermore, Holo-Code incorporates a distribution whitening mechanism that ensures the embedded signal is statistically indistinguishable from the standard Gaussian prior, thereby preserving the high fidelity of generated images. Extensive experiments validate that Holo-Code achieves a superior trade-off between robustness, quality, and efficiency. The framework guarantees reliable traceability across multiple generative models even under extreme composite degradations, seamlessly surviving heavy quantization from edge fallback mechanisms combined with severe structural occlusion. Moreover, as a training-free intervention, Holo-Code executes the complete forensic extraction on standard CPUs and achieves highly efficient identity retrieval against a database of one million users, establishing it as a practical solution for real-time AIGC provenance in large-scale IoT networks.

We revisit orthogonal lattice (OL) attacks and rounding techniques (RT) for solving the Approximate Common Divisor (ACD) problem. First, we systematically organize all existing OL algorithms within a novel logical framework proposed in this work. Specifically, we restate four existing OL algorithms, construct two OL algorithms using existing conclusions, refine the AIOL algorithm by adjusting the number of samples, and propose a new OL method (Algorithm 1: AIOL-σ). Second, by introducing the Log-Hermite-factor σ as a novel lattice quality metric, we theoretically re-analyze OL algorithms associated with σ. To establish a quantitative link between ACD parameters and σ, derive a new upper bound for short vector norms in the target lattice, and obtain a new lower bound for the required number of samples, our proposed algorithm identifies the optimal value of parameter α (a lattice parameter introduced in Xu et al.’s work) as 1. Consequently, our new algorithm remains invariant under the RT technique. Finally, experimental results demonstrate that the proposed algorithm achieves state-of-the-art performance in both attack efficiency and sample complexity. Finally, the great potential of the ACD problem in IoT applications is verified through a simple lightweight authentication protocol. In conclusion, the great potential of the ACD problem in IoT applications is verified through a simple lightweight authentication protocol.

Timed signatures are cryptographic primitives that enable senders to predefine the validity period of a signature. Currently, two primary types of timed signatures have been developed. The first type, known as Verifiable Timed Signatures (CCS'2020), implements a delay before a signature becomes effective. The second type is Short-Lived Signatures (ASIACRYPT'2022), which allows for the setting of an expiration time for signatures upon creation. However, certain applications requiring time-sensitive authorization demand both activation and expiration times to be set, a requirement not fulfilled by the existing timed signature schemes. To overcome this limitation, we propose a novel flexible timed signature scheme called Time Interval Signatures (TIS). TIS combines Verifiable Delay Functions and Short-Lived Signatures with our Zero-Knowledge Proof of Product, facilitating the flexible setting of both activation and expiration times for the signature. Building on TIS, we present TimeGuardian, a time-bound NFT rights protocol that enables presetting authorization and revocation periods for NFT usage rights. Experimental results show that TIS achieves signature size reductions of 98.67% and 57.14% compared to existing verifiable timed signature solutions.

Attribute-based encryption (ABE) provides fine-grained access control over encrypted data without restricting itself to a single access policy, making it applicable to diverse scenarios such as cloud environments. However, existing bilinear pairing-based ABE schemes are vulnerable to quantum attacks, while lattice-based ABE schemes typically lack flexible and efficient user or attribute revocation mechanisms. To address these challenges, this paper presents a fine-grained revocable attribute-based encryption (FR-ABE) scheme based on the ring learning with errors (RLWE) assumption. We introduce a two-dimensional attribute structure and an extended Shamir’s secret sharing method, which together support multi-valued attributes and flexible threshold access policies, while reducing storage and computational overhead. Furthermore, We have devised a fine-grained revocation mechanism that functions at both the attribute and user levels, thereby accommodating the frequent role and permission changes. The attribute authority centrally manages attribute revocation through an indirect revocation method, eliminating the need to re-run the sampling algorithm and instead relying solely on polynomial-level operations, which reduces time overhead. User revocation is implemented using a binary tree structure, which updates only the ciphertext and leaves all keys unchanged. Theoretical analysis suggests that our scheme performs well in terms of both computational and storage overhead, and experimental findings further corroborate its superiority. The security analysis establishes the scheme’s selective security under the RLWE assumption.

The Learning With Errors (LWE) problem serves as the security foundation for many post-quantum cryptographic schemes. Its various variants, including the sparse and small LWE problem, also play a key role in post-quantum cryptography. Accurately evaluating the computational complexity of solving LWE and its variants is important for understanding the security of related cryptographic schemes. In this paper, we propose an improved Dropping Meet-in-the-Middle (MitM) algorithm for LWE instances with sparse and small secrets. The core idea is to reduce the dimension of the MitM phase by pre-guessing τ components of the secret vector s, and to balance the additional guessing overhead against the reduction in the MitM phase, thereby achieving an overall optimization of computational cost. Experimental results show that our proposed method exhibits better performance compared with other attacks.

Abstract Lattice-based attribute-based encryption (ABE) combines the advantages of against quantum attack and fine-grained access control. However, most existing LWE-based or RLWE-based ABE schemes from lattices have the limitations of large storage cost and lack of support for attribute privacy protection. In 2022, a new algebraically structured LWE variant-cyclic algebra LWE (CLWE), was proposed by Grover et al. in journal of cryptology (JoC). This new variant has its inherent storage and computing advantages, especially in reducing the storage overhead. Therefore, to reduce the storage cost and protect the attribute privacy, we propose a novel lattice-based ABE scheme based on CLWE. More specifically, by introducing an extended Shamir’s secret sharing scheme on cyclic algebra and a two-dimensional (attribute label, attribute value) attribute structure, we extend the CLWE-based PKE scheme in JoC22 to a CLWE-based ABE scheme. The sizes of public key, master secret key, user’s secret key and ciphertext of our proposal are remarkably reduced. In addition, we combines a semi access policy structure and the two-dimensional attribute structure to hide the user’s attribute values, thereby preventing the leakage of user attribute privacy. Performance analysis shows that compared related lattice-based ABE schemes, our proposal is more efficient in the storage cost and it supports attribute privacy protection. Finally, our scheme is proved to be secure in the standard model.

Ring confidential transactions (RingCT) is a classical protocol that enhances transaction privacy within blockchain technology. It is primarily utilized in anonymous cryptocurrencies such as Monero. In recent years, to counter the security threats posed by quantum computing to classical RingCT (C-RCT), several post-quantum RingCT (P-RCT) protocols were proposed. However, prior studies do not address the account transition from C-RCT to P-RCT, which is essential to ensure the quantum resistance and usability of user accounts following the upgrade from C-RCT to P-RCT. In this article, we introduce a RingCT account transition protocol (RAT), which allows users to migrate their accounts from the blockchain with C-RCT to that with P-RCT. The protocol consists of two cryptographic components: 1) a zero-knowledge proof scheme used to prove that two group generators correspond to the same witness and 2) a cross-cryptosystems commitment transition protocol. RAT is fully decentralized and does not require any trusted third parties. Additionally, the transition process does not disclose the account balance and maintains both atomicity and consistency. The security of our protocol relies on the cryptographic components within RingCT, without the need for additional security assumptions, such as a trusted setup. The experimental results demonstrate the effectiveness of our protocol in practice.

Cross-chain technology facilitates the interoperability among isolated blockchains, where users can transfer and exchange coins. While the heterogeneity between Turing-complete (TC) blockchains like Ethereum and non-Turing-complete (NTC) blockchains like Bitcoin presents a significant challenge for cross-chain transactions. Payment Channel Hubs (PCHs) offer a promising solution for enabling TC-NTC cross-chain payments with high throughput and low confirmation delays. However, existing schemes still face two key challenges: (i) significant computation and communication overhead for variable-amount payment, and (ii) limited unlinkability, i.e., vulnerable to the abort attack. This paper proposes EC2P, the first TC-NTC cross-chain PCH that achieves variable-amount payment unlinkability while resisting the abort attack and minimizing reliance on non-interactive zero-knowledge (NIZK) proofs. EC2P introduces two protocols: the NTC-to-TC and TC-to-NTC payment protocols. The NTC-to-TC payment protocol replaces the traditional puzzle-promise and puzzle-solve paradigm with a semi-blind approach, where only one side is blinded and the blinded side’s interactions are eliminated. This achieves unlinkability and resists the abort attack without NIZK. The TC-to-NTC payment protocol enhances the paradigm by utilizing Turing-complete functionality to constrain the inability to carry out an abort attack. Through rigorous security analysis, we show that EC2P is secure and variable-amount payment unlinkable while resisting the abort attack. We implement EC2P on Ethereum and Bitcoin test networks. Our evaluation demonstrates that EC2P outperforms both in terms of communication and computation overhead and reduces communication costs by 3 orders of magnitude compared to existing variable-amount methods.

Blockchain technology, known for its decentralization and immutability, has been widely applied across various domains. However, this immutability reveals limitations in adapting to rapidly changing legal environments and preventing malicious misuse. To introduce a degree of flexibility, various transaction-level redactable blockchain solutions have been proposed. Yet, current schemes grant modifiers redaction privileges by providing access to the trapdoor, potentially posing risks of malicious dissemination and abuse of the trapdoor. In this paper, we first propose an RSA-based threshold chameleon hash (TCH) construction, allowing the distribution of the trapdoor among a group of authorities. Building on TCH, we develop a threshold policy-based chameleon hash (TPCH). Compared to the Policy-Based Chameleon Hash (PCH) proposed by Derler at NDSS'19, our TPCH supports authorization without exposing the trapdoor. Furthermore, leveraging TPCH, we introduce a novel transaction-level redactable blockchain (TPRB). TPRB supports decentralized authorization without trapdoor exposure and fine-grained rewriting control. Finally, through implementation and evaluation, we demonstrate the practicality and efficiency of our TCH and TPCH schemes.

Ring Confidential Transactions (RingCT) is a classic cryptographic protocol for anonymous transactions on blockchains, currently used in the popular anonymous cryptocurrency Monero. The proof size of RingCT transactions is linearly related to the ring size, which limits the use of larger ring sizes due to the significant communication overhead it incurs. However, reducing the ring size also leads to decreased anonymity. Therefore, in recent years, many studies have focused on optimizing the proof sizes for RingCT, with the latest known solutions reducing the proof size to be logarithmic with the ring size. In this paper, we propose a new compact RingCT protocol (CRCT) for smaller proof sizes. To this end, we first design three extended schemes of the Sum Argument (CRYPTO’21), which are used to generate logarithmic-sized proofs for three distinct zero-knowledge arguments, respectively. We then introduce a new zero-knowledge proof scheme called the Difference Argument. It is used to prove that one has the knowledge of two secret values, with their difference being public. Based on these schemes, we construct our CRCT protocol, whose proof size is independent of the ring size and logarithmic with the number of source accounts. We provide concrete constructions and security proofs for the proposed cryptographic schemes. The experimental results demonstrate that CRCT exhibits significant advantages in computational efficiency and proof size over existing solutions when dealing with large ring sizes and moderate numbers of source accounts.

Ring signatures enable a user to sign a message on behalf of a group while preserving both anonymity and unforgeability. Despite these strong privacy guarantees, they present regulatory challenges. To address these issues, we introduce a novel cryptographic primitive:timed anonymous ring signatures(TARS). Unlike group signatures, which rely on a trusted third party, TARS maintains the decentralization and unforgeability of traditional ring signatures while incorporatingtimed anonymity, allowing the signer’s identity to be disclosed by any user after a predetermined time period, denoted asT. To realize this, we propose a new CCA-securetimed public key encryption(TPKE) scheme that ensures correct decryption without the secret key after the timeT. Building upon TPKE, we present two concrete TARS constructions that guarantee anonymity until timeTand unforgeability at all times. To demonstrate its applicability, we apply TARS to a decentralized bidding system that is anticollusion between the auctioneer and the bidders. The system ensures anonymous bidding while disclosing the winner’s identity after the bid announcement, maintaining a transparent, fair, and decentralized bidding process. Finally, experimental evaluations confirm the practicality and efficiency of the proposed schemes. Crucially, the TARS scheme extends conventional ring signature schemes with timed anonymity by introducing only a moderate computational overhead (experimentally measured at ≈1.37 seconds under our configuration) while preserving their cryptographic robustness.

The immutability of blockchain has exposed its limitations in adapting to rapidly evolving legal requirements and preventing malicious misuse. To address these issues, transaction-level redactable blockchain solutions based on the policy-based chameleon hash (PCH) have been introduced. These solutions allow users to create transactions and encrypt trapdoors under specific attribute policies. However, current transaction-level rewriting schemes face two security challenges: Firstly, transactions encrypted with the invalid trapdoor are difficult to rewrite; Secondly, due to lacking version detection on transactions, malicious modifiers may rollback the version of the transaction to launch a reversion attack. In this paper, we present a resilient and redactable blockchain (RRB) with 2-level rewriting and transaction version detection. Specifically, we propose a new redactable blockchain structure that supports both transaction-level and block-level rewriting. To tackle the invalid trapdoor problem, we propose two protocols: a fine-grained, controllable transaction-level rewriting protocol and a centrally controlled block-level rewriting protocol. Moreover, for the transaction reversion attack, we design a version detection mechanism for RRB by using an accumulator. Through security analysis and performance evaluation, we demonstrate the security and practicality of our RRB scheme.

Blockchain is renowned for its immutability, a feature that ensures recorded data cannot be modified or deleted. However, malicious entities can exploit this immutability to permanently embed objectionable data. Moreover, the immutability of blockchain can conflict with the “right to be forgotten” provision in the privacy protection laws of the GDPR. Therefore, a seminal redactable blockchain solution is proposed to address the above problem. Recently, one of the primary focuses in redactable blockchain solutions is the design of global editing permission control. The design leverages the consensus voting mechanism, with its core objective being to prevent excessive centralization of editing power, thereby preserving the decentralized nature of blockchain technology. Meanwhile, such schemes exhibit the following phenomena: (i) the members of the editorial decision-making group are fixed and unchanging, and (ii) blockchain nodes display lazy voting behaviors during the editorial voting process. Considering these factors, we introduce a Publicly Redactable Blockchain scheme with an off-chain reputation-based Consensus Protocol (PRBCP). In this scheme, any node in the blockchain network has the opportunity to become an editorial node and perform editing operations. We design a reputation-based off-chain editorial voting consensus protocol leveraging the threshold signature scheme, which enables dynamic updates to the editorial decision-making group membership and enhances nodes’ participation in editorial voting. In addition, we conduct rigorous security proofs and experimental efficiency analyses for our scheme. The results demonstrate that the PRBCP is both secure and efficient. Finally, we instantiate our scheme as a redactable medical blockchain (RMB) system for storing electronic medical records (EMRs).

Fully homomorphic encryption (FHE) scheme allows for performing computations on encrypted data without decrypting it which makes it more popular in various domains. Most previous FHE constructions are limited by the large ciphertext expansion rate and error growth rate. Learning with errors (LWE) problem is a popular primitive for constructing lattice-based FHE. Many algebraic variants of LWE are also developed with further promising cryptographic features. Most previous known LWE variants (over the commutative base rings) are unified into a general framework by Peikert et al. at TCC 2019. In 2022, a new algebraically structured LWE problem over the d-degree cyclic algebra (CLWE) (with modulus q), a typical non-commutative ring, was proposed by Grover et al.. To further explore the utility and potential advantages of this new variant, it is interesting to design new lattice-based FHE schemes by using CLWE. In this paper, by following the diagrams of Gentry-Sahai-Waters (GSW13 for short), we propose a FHE scheme based on the CLWE with an even small ciphertext size. Due to our further expansion of the plaintext space, the average ciphertext expansion rate (CER for short) is smaller. More precisely, compared to original GSW13 and the related GSW-style constructions, the ciphertext size of our proposal is reduced by almost at least 23.69%, and the average CER is reduced about 96% due to our expansion of the plaintext space. Besides, our FHE has an even small error growth rate (EGR for short). After one time multiplication of two ciphertexts, the asymptotical EGR is reduced about 49.8% compared to the original GSW13 and the related GSW-style constructions. Typically, the smaller ciphertext size, CER and EGR make our FHE scheme more efficient in trusted computing environment.

Data sharing among vehicles can effectively address the traffic congestion and accidents caused by the increasing number of vehicles, thereby enhancing traffic efficiency and the travel experience. However, it also introduces security and privacy challenges related to confidentiality, authentication, identity privacy, identity revocation, and tamper resistance. To address the above challenges, we propose a bilateral access control data sharing scheme by extending Matchmaking Encryption. Our proposal ensures data confidentiality and data source authentication by combining attribute-based encryption with identity-based encryption. Most importantly, we verify the bilateral policies within a single logical step. To achieve identity revocation, we propose a revocation scheme based on a pseudo-identity list, which can revoke all the pseudo-identities associated with a malicious user and ensure the privacy of legitimate real identity. Security analysis indicates that apart from ensuring confidentiality and authentication, our proposal resists attacks, such as tampering, guessing, and collusion. We conduct theoretical complexity analysis and experimental performance evaluations to demonstrate the efficiency and practicality of our proposal for Internet of Vehicles (IoV) data sharing.

Ring Confidential Transactions (RingCT) is a typical privacy-preserving protocol for blockchain, which is used for the most popular anonymous cryptocurrency Monero in recent years. RingCT provides the user's identity anonymity based on the linkable ring signature. At the cost of that, the transaction size is increased linearly to the involved users. In this article, we aim to overcome this inefficient aspect of RingCT by introducing the linkable threshold ring signature (LTRS). We first propose a construction of threshold ring signatures for homomorphic cryptosystems, and present an efficient instantiation based on the intractability assumption of the discrete logarithm problem. Based on this framework, an efficient LTRS scheme and a novel construction of the RingCT protocol are presented. Our proposed RingCT protocol enables multiple payers to co-construct an anonymous transaction without revealing their secret account keys, and it is more concise under multiple input accounts. For a transaction with a ring size of 100 and the input accounts number of 64, the communication overhead is about 4% of the original RingCT protocol.

Immutability is widely recognized as one of the blockchain’s key security attributes. However, in recent years, incidents involving the use of blockchain for disseminating illegal or malicious information have raised concerns over its strict immutability. To address these issues, redactable blockchains are proposed as a novel solution, permitting authorized content redactions without compromising the structural integrity of the blockchain. Unfortunately, current solutions are unable to restrict the abuse of redaction privilege, except for relying on a trusted authority or committee, which contradicts the trustlessness principle of blockchain. In this paper, we propose a controlled redactable blockchain protocol that allows for a limited number of redactions and supports a transparent setup. The cryptographic tools enabling this functionality are our proposed t-times chameleon hash (t-CH) and signature (t-CS) schemes, where generating more than t collisions will expose the trapdoor. We present security models, discrete logarithm-based instantiations, and formal security proofs for both t-CH and t-CS. Subsequently, we present the construction of our redaction protocol in both permissioned and permissionless settings. Finally, we experimentally demonstrate the effectiveness of the proposed protocol in practice.

Recent studies have demonstrated that malicious adversaries are capable of fingerprinting Internet of Things (IoT) devices in a smart home and further causing privacy breaches. However, many existing anti-fingerprinting schemes, either by traffic padding or traffic mutation, are less effective in defending against state-of-the-art fingerprinting methods. To meet this gap, we in this paper propose the HomeSentinel, an intelligent anti-fingerprinting scheme to counter IoT traffic fingerprinting in smart homes. Specifically, we first design a LightGBM-based IoT traffic extraction model to accurately distinguish IoT traffic from raw network traffic in a smart home without user operations. Second, we develop a dummy IoT traffic generation model to produce dummy IoT traffic in desired spatial-temporal patterns. Third, an IoT traffic mixing strategy is crafted to heuristically merge dummy IoT traffic with real IoT traffic in desired spatial-temporal patterns. Extensive experiments on three real-world datasets (i.e., two public and one custom) demonstrate that our proposed HomeSentinel scheme can effectively defend against state-of-the-art IoT traffic fingerprinting methods, and outperforms existing IoT traffic anti-fingerprinting schemes. Further, real-world experiments are conducted on a self-built testbed show that, reasonably low communication delays can be caused when implementing the HomeSentinel in smart homes.

Blockchain technology was originally designed to ensure data security and trustworthiness through decentralization and immutability. However, in recent years, the misuse of immutability limits the development of blockchain. To address this challenge, several redactable blockchain solutions have been proposed. However, existing solutions either struggle to maintain block consistency or compromise the decentralization principles of blockchain. In this paper, we present a novel redactable blockchain to address these issues. Firstly, we propose a decentralized trapdoor verifiable delay function (DTVDF) based on Wesolowski’s verifiable delay function (VDF) scheme (EUROCRYPT’2019), which distributes trapdoor shares among a group of participants. Then, we leverage the proposed DTVDF to construct our redactable blockchain solution (DTRB), where redacting blocks requires consensus from threshold nodes. Moreover, DTRB provides accountability for malicious modifications and supports aggregate verification of redacted blocks, significantly improving the efficiency of our scheme. Through experimental analysis and comparison with existing solutions, our approach demonstrates superior performance.

BACKGROUND: As one of the fundamental problems in bioinformatics, the double digest problem (DDP) focuses on reordering genetic fragments in a proper sequence. Although many algorithms for dealing with the DDP problem were proposed during the past decades, it is believed that solving DDP is still very time-consuming work due to the strongly NP-completeness of DDP. However, none of these algorithms consider the privacy issue of the DDP data that contains critical business interests and is collected with days or even months of gel-electrophoresis experiments. Thus, the DDP data owners are reluctant to deploy the task of solving DDP over cloud. RESULTS: Our main motivation in this paper is to design a secure outsourcing computation framework for solving the DDP problem. We at first propose a privacy-preserving outsourcing framework for handling the DDP problem by using a cloud server; Then, to enable the cloud server to solve the DDP instances over ciphertexts, an order-preserving homomorphic index scheme (OPHI) is tailored from an order-preserving encryption scheme published at CCS 2012; And finally, our previous work on solving DDP problem, a quantum inspired genetic algorithm (QIGA), is merged into our outsourcing framework, with the supporting of the proposed OPHI scheme. Moreover, after the execution of QIGA at the cloud server side, the optimal solution, i.e. two mapping sequences, would be transferred publicly to the data owner. Security analysis shows that from these sequences, none can learn any information about the original DDP data. Performance analysis shows that the communication cost and the computational workload for both the client side and the server side are reasonable. In particular, our experiments show that PP-DDP can find optional solutions with a high success rate towards typical test DDP instances and random DDP instances, and PP-DDP takes less running time than DDmap, SK05 and GM12, while keeping the privacy of the original DDP data. CONCLUSION: The proposed outsourcing framework, PP-DDP, is secure and effective for solving the DDP problem.

As one of the crucial features of the blockchain technique, immutability plays the most important role in winning the so-called praise of the “trust machine” for blockchain. However, there are two sides to everything. The property of immutability of blockchain is applied maliciously sometimes, say publishing harmful or even dangerous data and hindering authorities’ law enforcement. To address this issue, authorized redactability of blockchain was introduced to support block modification without lowering the fundamental basis of security and trust that is cherished on the blockchain. During the past years, several techniques of redactable blockchain were proposed, mainly based on the well-known chameleon hashing. Different from existing methodologies, we propose a new redactable blockchain scheme for permissioned settings in this article. We first employ the trapdoor verifiable delay function to attach a time-lapse proof to each block. Moreover, the trapdoor is used to quickly construct a chain fork to redact blocks that are authorized to alter. Our proposal does not need to rollback irrelevant blocks. As a remarkable and unique feature, our proposal realizes the property of strong synchronization of redaction, which means that all nodes in the blockchain will have identical views on the chain even after some blocks are altered. Security analysis shows that the consistency of the chain is guaranteed, and the long-range attack can be resisted effectively. The performance comparison shows that our method is feasible and practical.

Anonymous cryptocurrencies are distributed applications based on blockchain technology that enhance the anonymity of user transactions. However, they also provide cover for many criminal activities. Existing traceable modifications of anonymous transaction protocols do not support public verification of the traceability of transactions, meaning dishonest users can still evade tracing by forging partial proofs. In this paper, we first propose EPoK, which is a partially extractable zero-knowledge proof scheme designed to address this issue. We provide the instantiation of EPoK, as well as its formal security proofs. Combined with EPoK and the classic anonymous transaction protocol RingCT, we propose a traceable anonymous transaction protocol TRCT for tracing participants’ addresses and transaction amounts in anonymous transactions. Compared to previous works, TRCT is the first to implement public verification of the transaction’s traceability while still maintaining anonymity. This ensures that users cannot forge relevant proofs to evade tracing. We present and prove the security properties of TRCT, and experimentally compare its efficiency with the original RingCT protocol. The result shows that the extra overhead generated by TRCT is small.

As an important driving factor of emerging Internet-of-Things (IoT) applications, machine learning algorithms are currently facing the challenge of how to “clean” data noise, that is introduced during the training process (e.g., asynchronous execution and lossy data compression and quantization). In an attempt to guarantee data quality, various data cleaning approaches have been proposed to filter out abnormal data entries based on the global data distribution. However, most existing data cleaning approaches are based on a centralized paradigm and thus cannot be applied to future edge-based IoT applications, where each edge node (EN) has only a limited view of the global data distribution. Moreover, the increasing demand for privacy preservation largely prevents ENs from combining their data for centralized cleaning. In this study, we propose a federated data cleaning protocol, coined as FedClean, for edge intelligence (EI) scenarios that is designed to achieve data cleaning without compromising data privacy. More specifically, different ENs first generate Boolean shares of their data and distribute them to two noncolluding servers. These two servers then run the FedClean protocol to privately and efficiently compute the attribute value frequency (AVF) scores of the collected data entries, which are then sorted in ascending order via a bitonic sorting network without revealing their values. As a result, data entries with lower AVF scores are considered as abnormal and filtered out. The security, efficiency, and effectiveness of the proposed approach are then demonstrated via concrete security analysis and comprehensive experiments.

Abstract Online taxi-hailing has become people’s most popular trip mode due to its convenience and low cost. However, it also poses a privacy threat to passengers and drivers, since the online taxi-hailing service providers are able to track their precise mobility trajectories. In addition, there is a certain time delay between the time of a passenger makes a request and the time of the driver arrives the passenger’s boarding position in current online taxi-hailing system. To solve these two problems, we present a new and efficient location privacy protection scheme based on the MinHash algorithm (LPPM). With the LPPM, the exact positions of passengers and drivers are generalized into a set of points of interest around them, and the distance between them is transformed into the similarity between the two sets. Thus a service provider can efficiently match passengers and drivers by using MinHash algorithm without revealing their specific location information. In this paper, we use mobile edge computing technology in the online taxi-hailing system to address the second challenge. It can speed up data processing, drivers can make decisions in advance and reduce the possibility of road congestion. Security analysis shows that LPPM has high security, and the final experimental results confirmed that LPPM is effective.

At present, with the popularity of Internet of things (IoT), a huge number of datasets generated by IoT devices are being uploaded to the cloud storage in remote data management service, but a series of security and privacy defects also arises, where one of the best ways for preventing data disclosure is encryption. Among them, searchable encryption (SE) is considered to be a very attractive cryptographic technology, since it allows users to search records in an encrypted form and to protect user’s data on an untrusted server. For the sake of enhancing search permission, attribute-based keyword search (ABKS) is an efficient method to provide secure search queries and fine-grained access authentications over ciphertexts. However, most existing ABKS schemes concentrate on single keyword search, which usually returns redundant and irrelevant results, so it would cost some unnecessary computation and communication resources. Furthermore, existing work in the literature mostly only supports unshared multiowner where a specific data owner owns each file, which is not able to satisfy more desired expressive search. In this work, we propose a novel attribute-based multikeyword search for shared multiowner (ABMKS-SM) primitive in IoT to achieve enhanced access control for users; meanwhile, it can support multikeyword search over ciphertexts and give a formal security analysis in the adaptive against chosen keyword attack (IND-CKA) model. Finally, we have also implemented this prototype to show efficiency when compared with some previous schemes.

As it is difficult to directly share data among different organizations, data federation brings new opportunities to the data-related cooperation among different organizations by providing abstract data interfaces. With the development of Cloud computing, organizations store data on the Cloud to achieve elasticity and scalability for data processing. The existing data placement approaches generally only consider one aspect, which is either communication cost or time cost, and do not consider the features of jobs that process the data. In this paper, we propose an approach to enable secure data processing on the Cloud with the data from different organizations. The approach consists of a data federation platform for secure data processing on the Cloud named FedCube and a greedy data placement algorithm that creates a plan to store data on the Cloud in order to achieve multiple objectives based on a cost model. The cost model is composed of two objectives, i.e., reducing both monetary cost and execution time. We present an experimental evaluation by comparing our data placement algorithm with the existing methods based on the data federation platform. The experiments show that our proposed algorithm significantly reduce the total cost (up to 69.8%).

Data privacy, especially location privacy, is paramountly important for protecting individual's information in smart cities in the big data era. One of the examples is in spatial crowdsourcing (SC). It enables people not only to issue spatiotemporal tasks to ask for help as requesters but also to solve others' tasks as workers on the SC platform. While SC brings convenience to people, it also produces severe location privacy problems, which have been recently paid more attention from both academia and industries. In this article, we address the location privacy problem in SC in a practical and secure way. We propose a location privacy-preserving framework for almost all existed mainstream distance computations in the SC system, namely, Euclidean-L3P, Minkowski-L3P, Manhattan-L3P, and Chebyshev-L3P, among which the first two are constructed based on homomorphic encryption and composite-order multilinear mapping while the latter two on the homomorphic encryption and prefix membership verification approach. Location privacy is resolved because of the above techniques having enabled that all distance computations are evaluated through ciphertexts without disclosing any location information. Security analysis shows that our framework can prevent a strong adversary from obtaining participants' location privacy. Performance analysis evaluates computation and communication overheads between protocols. The results show that Euclidean-L3P is more efficient than Manhattan-L3P and Chebyshev-L3P in terms of computation overheads when the SC applications require a small number of participants, a large plaintext space, and a small number of base stations. Moreover, compared with Manhattan-L3P and Chebyshev-L3P, Euclidean-L3P is a better choice in terms of communication overhead.

Linear secret-sharing scheme (LSSS) is a useful tool for supporting flexible access policy in building attribute-based encryption (ABE) schemes. But in lattice-based ABE constructions, there is a subtle security problem in the sense that careless usage of LSSS-based secret sharing over vectors would lead to the leakage of the master secret key. In this paper, we propose a new method that employs LSSS to build lattice-based key-policy attribute-based encryption (KP-ABE) that resolves this security issue. More specifically, no adversary can reconstruct the master secret key since we introduce a new trapdoor generation algorithm to generate a strong trapdoor (instead of a lattice basis), that is, the master secret key, and remove the dependency of the master secret key on the total number of system attributes. Meanwhile, with the purpose of reducing the storage cost and support dynamic updating on attributes, we extended the traditional 1-dimensional attribute structure to 2-dimensional one. This makes our construction remarkably efficient in space cost, with acceptable time cost. Finally, our scheme is proved to be secure in the standard model.

Federated machine learning systems have been widely used to facilitate the joint data analytics across the distributed datasets owned by the different parties that do not trust each others. In this paper, we proposed a novel Gradient Boosting Machines (GBM) framework SecureGBM built-up with a multi-party computation model based on semi-homomorphic encryption, where every involved party can jointly obtain a shared Gradient Boosting machines model while protecting their own data from the potential privacy leakage and inferential identification. More specific, our work focused on a specific “dualparty” secure learning scenario based on two parties — both party own an unique view (i.e., attributes or features) to the sample group of samples while only one party owns the labels. In such scenario, feature and label data are not allowed to share with others.To achieve the above goal, we firstly extent — LightGBM — a well known implementation of tree-based GBM through covering its key operations for training and inference with SEAL homomorphic encryption schemes. However, the performance of such re-implementation is significantly bottle-necked by the explosive inflation of the communication payloads, based on ciphertexts subject to the increasing length of plaintexts. In this way, we then proposed to use stochastic approximation techniques to reduced the communication payloads while accelerating the overall training procedure in a statistical manner. Our experiments using the real-world data showed that SecureGBM can well secure the communication and computation of LightGBM training and inference procedures for the both parties while only losing less than 3% AUC, using the same number of iterations for gradient boosting, on a wide range of benchmark datasets. More specific, compared to LightGBM, the proposed SecureGBM would slowdown with $3\mathrm{x} \sim 64\mathrm{x}$ time consumption per iteration in the training procedure, while SecureGBM becomes more and more efficient when the scale of the training dataset increases (i.e., the larger training set, the lower slowdown ratio).

In recent years, the Ethereum platform has rapidly emerged, but its privacy issue has become the largest obstacle to the implementation of Ethereum projects. Unlike UTXO-based Bitcoin, Ethereum, the account-based blockchain, requires realtime updates of the account balance. Therefore, its corresponding hidden operation has certain difficulties. We propose a privacy protection scheme called RZcash to solve this problem. It implements the hiding of account balances that are updated in real time, and uses rangeproofs to ensure that the amount of each transaction does not exceed the payer's existing balance. For hiding the payee, we improve the related technology of Monero by using the ciphertext equivalent commitment scheme. We also provide the conversion mechanism and trading method between hidden coins and open coins and describe how RZcash can be combined with an existing account-based blockchain system (such as Ethereum). Finally, we implement the core model of RZcash and evaluate its performance. The evaluation results show that the scheme not only guarantees the privacy and security of the blockchain, but also has good performance in practical applications.

Information sharing solves the problem of information asymmetry between banks to a certain extent, but it also brings about the leakage of customer privacy. Therefore, how to protect data privacy while sharing data is an urgent issue. Blockchain protects the privacy of accounts and data while sharing data. Therefore, we propose a blockchain-based loan over-prevention mechanism. The program can hide the customer loan/repayment amount and thus protect the customer's privacy; we prove that the customer's loan amount is within a certain range and does not exceed the remaining loanable amount via a range proof. In order to share customer loan information between banks, we store the commitment of customers' amounts in the blockchain, and banks can obtain relevant information directly from the chain, which also reduces the amount of communication between banks. Finally, we implement the model and performe a performance analysis.

BACKGROUND: In computational biology, the physical mapping of DNA is a key problem. We know that the double digest problem (DDP) is NP-complete. Many algorithms have been proposed for solving the DDP, although it is still far from being resolved. RESULTS: We present DDmap, an open-source MATLAB package for solving the DDP, based on a newly designed genetic algorithm that combines six genetic operators in searching for optimal solutions. We test the performance of DDmap by using a typical DDP dataset, and we depict exact solutions to these DDP instances in an explicit manner. In addition, we propose an approximate method for solving some hard DDP scenarios via a scaling-rounding-adjusting process. CONCLUSIONS: For typical DDP test instances, DDmap finds exact solutions within approximately 1 s. Based on our simulations on 1000 random DDP instances by using DDmap, we find that the maximum length of the combining fragments has observable effects towards genetic algorithms for solving the DDP problem. In addition, a Maple source code for illustrating DDP solutions as nested pie charts is also included.

Abstract With the development of Lie theory, Lie groups have attained profound significance in several branches of Mathematics and Physics. In Lie theory, the matrix exponential plays a crucial role between Lie groups and Lie algebras. Meanwhile, as the finite analogue of Lie groups, finite groups of Lie type have potential applications in cryptography due to their unique mathematical structures. In this paper, we first put forward a novel idea of designing cryptosystems based on Lie theory. First of all, combing with discrete logarithm problem and group factorization problem, we proposed several new intractable assumptions based on the matrix exponential in finite groups of Lie type. Subsequently, in analog with Boyen’s scheme (Asiacrypt 2007), we designed a public-key encryption scheme based on the non-abelian factorization problem in finite groups of Lie type. Finally, our proposal was proved to be indistinguishable against adaptively chosen-ciphertext attack in the random oracle model. It is encouraging that our scheme also has the potential to resist against Shor’s quantum algorithm attack.

Summary Based on cloud servers' powerful storage and computing resources, users can store mass encrypted data in the cloud and outsource complex encryption computations to the cloud servers. Since cloud servers cannot be completely trusted, then data privacy and integrity are concerned about hot issues. We focus on the following problems in outsourced encryptions: how to protect the data privacy and how to check the integrity of data and the correctness of cloud server's outsourcing computations. In this paper, we at first propose a verifiable chaotic encryption based on Chebyshev polynomials. The scheme supports verifiable function for data integrity. To further improve the efficiency of the scheme, a corresponding outsourced encryption scheme is constructed, where the heavy overhead evaluations of Chebyshev polynomials are transferred from the user side to the cloud server. The outsourced encryption also provides the checkability for data integrity and correctness of cloud computations. The scheme is suitable for mobile users with limited computing resources. Moreover, the newly proposed scheme no longer depends upon the simple heuristic analysis. It achieves the indistinguishability under chosen‐ciphertext attacks (IND‐CCA) in the standard model based on the Chebyshev‐based Decisional Diffie‐Hellman (CDDH) assumption. Thus, we answer a long‐term open problem for building a chaotic encryption scheme with provable security in the sense of the IND‐CCA.

Efficient medical image sampling and transferring becomes one of key research areas in computer science and healthcare application industries. In particular, the technique of body area networking and personal area networking are very useful in various image-based medical monitoring systems that cover a wide range of healthcare services, such as early detecting of emergency conditions and remote online instructing of surgeries. However, medical images are highly privacy sensitive and redundant. Thus, proper protection on privacy and secure data aggregation/compression are also highly expected in medical image processing. Based on compressive sensing theory, we conceive a so-called “one-stone-three-bird” solution for medical image acquisition and transmission in this paper. The size of the original medical images can be reduced to 20%, the resulted images have very well confidentiality and supporting additively homomorphic aggregation.

The consumer Internet of Things (IoT), which exploits wireless personal area network (WPAN) technology, is undergoing rapid growth. Although the consumer IoT enables users to control many devices and offers conveniences and benefits for daily life, its long-term operation capabilities are subject to a bottleneck related to power management. To save energy and prolong the lifetime of an IoT system, the basic idea is to allow idle devices to go to sleep. Because excessively frequent switching between the awake and asleep phases will consume a significant amount of power, it is essential to properly schedule the order of multiple communication streams among multiple devices such that the total number of wake-up events is as small as possible. Based on the typical communication protocols deployed in IoT systems, this problem can be divided into two cases: 1) the inter-superframe case and the 2) intrasuperframe case. The former case has been well studied in existing works, whereas research on the latter case is currently immature. In this paper, we propose an efficient scheme for addressing the stream order scheduling (SOS) problem in the intrasuperframe case. Mobile edge computing technology is utilized in the proposed scheme to reduce the network load, and three heuristic algorithms are proposed to improve the scheme's performance. We report various tests conducted on 4800 random original IoT topologies and 19000 random Hamiltonian edge-dual topologies, and the experimental results demonstrate that our scheme achieves optimal solutions with a very high success probability.

Blockchain, as one of the crypto-intensive creatures, has become a very hot topic recently. Although many surveys have recently been dedicated to the security and privacy issues of blockchains, there still lacks a systematic examination on the cryptographic primitives in blockchains. To this end, we in this paper conduct a systematic study on the cryptographic primitives in blockchains by comprehensive analysis on top-30 mainstream cryptocurrencies, in terms of the usages, functionalities, and evolutions of these primitives. We hope that it would be helpful for cryptographers who are going to devote themselves to the blockchain research, and the financial engineers/managers who want to evaluate cryptographic solutions for blockchain-based projects.

A new integration of wireless communication technologies into the automobile industry has instigated a momentous research interest in the field of Vehicular Ad Hoc Network (VANET) security. Intelligent Transportation Systems (ITS) are set up, aiming to offer promising applications for efficient and safe communication for future automotive technology. Vehicular networks are unique in terms of characteristics, challenges, architecture, and applications. Consequently, security requirements related to vehicular networks are more complex as compared to mobile networks and conventional wireless networks. This article presents a survey about developments in vehicular networks from the perspective of lightweight cryptographic protocols and privacy preserving algorithms. Unique characteristics of vehicular networks are presented which make the embedded security applications computationally hard as well as memory constrained. The current study also deals with the fundamental security requirements, essential for vehicular communication. Furthermore, awareness of security threats and their cryptographic solutions in terms of future automotive industry are discussed. In addition, asymmetric, symmetric, and lightweight cryptographic solutions are summarized. These strategies can be enhanced or incorporated all in all to meet the security perquisites of future cars security.

Summary Lattice has become an attractive cryptographic tool due to its potential resistance to quantum attacks, worst‐case hardness, simple computation kind, and flexibility. The pre‐image sample algorithm is the most fundamental algorithm in lattice‐based cryptography for its comprehensive applications in various primitives. Currently, due to Micciancio and Peikert (MP) sample algorithm is the most efficient pre‐image sample algorithm. However, this algorithm also needs massive computations. On the one hand, it expenses the cube of the lattice dimension multiplications over reals to set matrices as Gaussian parameters. On the other hand, it needs complex discrete convolution computations. First, this paper proposes an efficient pre‐image sample algorithm with outputs obeying irregular Gaussian distribution. Two measures are adopted to prevent the leakage of the geometrical property of trapdoor caused by irregular Gaussian outputs. A variant of MP trapdoor is proposed, and a new trapdoor is randomly assembled from a big enough space in each sample. Although still using a matrix as the Guassian parameter, in the proposed algorithm, the computational cost to set Gaussian parameters is zero. Meanwhile, the computational overhead for every sample is far less than that of MP sample algorithm. Second, to demonstrate the security and efficiency of the proposed sample algorithm, a hierarchical identity‐based signature scheme is put forward. This scheme is proved existentially unforgeable against selective identity adaptively chosen‐message attacks. Furthermore, the theoretical analysis shows that the proposed identity‐based signature is more efficient than the existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.

Mobile healthcare social networks (MHSN) integrated with connected medical sensors and cloud-based health data storage provide preventive and curative health services in smart cities. The fusion of social data together with real-time health data facilitates a novel paradigm of healthcare big data analysis. However, the collaboration of healthcare and social network service providers may pose a series of security and privacy issues. In this paper, we propose a secure health and social data sharing and collaboration scheme in MHSN. To preserve the data privacy, we realize secure and fine-grained health data and social data sharing with attribute-based encryption and identity-based broadcast encryption techniques, respectively, which allows patients to share their private personal data securely. In order to achieve enhanced data collaboration, we allow the healthcare analyzers to access both the reencrypted health data and the social data with authorization from the data owner based on proxy reencryption. Specifically, most of the health data encryption and decryption computations are outsourced from resource-constrained mobile devices to a health cloud, and the decryption of the healthcare analyzer incurs a low cost. The security and performance analysis results show the security and efficiency of our scheme.

The Cramer-Shoup cryptosystem has attracted much attention from the research community, mainly due to its efficiency in encryption/decryption, as well as the provable reductions of security against adaptively chosen ciphertext attacks in the standard model. At TCC 2005, Vasco et al. proposed a method for building Cramer-Shoup like cryptosystem over non-abelian groups and raised an open problem for finding a secure instantiation. Based on this work, we present another general framework for constructing Cramer-Shoup like cryptosystems. We firstly propose the concept of index exchangeable family (IEF) and an abstract construction of Cramer-Shoup like encryption scheme over IEF. The concrete instantiations of IEF are then derived from some reasonable hardness assumptions over abelian groups as well as non-abelian groups, respectively. These instantiations ultimately lead to simple yet efficient constructions of Cramer-Shoup like cryptosystems, including new non-abelian analogies that can be potential solutions to Vasco et al.'s open problem. Moreover, we propose a secure outsourcing method for the encryption of the non-abelian analog based on the factorization problem over non-commutative groups. The experiments clearly indicate that the computational cost of our outsourcing scheme can be significantly reduced thanks to the load sharing with cloud datacenter servers.

Abstract Signcryption as a cryptographic primitive can carry out signature and encryption simultaneously at a remarkably reduced cost. Identity‐based cryptography is more convenient than public key infrastructure‐based cryptography in certificate management. As a result, identity‐based signcryption has been studied extensively, and many efficient and provably secure constructions have been proposed. However, most of these schemes are based on intractability assumptions from number theory, and these assumptions have been threatened by the booming quantum computation. Therefore, a recent trend in cryptography is to construct cryptosystems that are based on lattice‐based intractability assumptions because of their plausible features of quantum attack resistance. In this paper, several identity‐based signcryption schemes from lattice hardness assumptions are proposed. In the standard model, these schemes are indistinguishable againstinneradaptively chosen ciphertext attacks (IND‐CCA2) and strongly unforgeable againstinnerchosen message attacks. In our construction, it does not matter whether the original encryption scheme used to construct signcryption is deterministic or probabilistic; the resulted signcryption schemes can reach IND‐CCA2 security. To achieve this, we carefully combine three techniques—the identity‐based encryption from lattice due to Agrawal–Boneh–Boyen (EUROCRYPT 2010), the framework of lattice‐based short signature due to Boyen (Public Key Cryptography 2010), and the Canetti–Halevi–Katz (abbr. CHK) technique, with necessary and tailored optimization—for transforming an (ℓ+ 1)‐level indistinguishable under chosen plaintext attack secure hierarchical identity‐based encryption (HIBE) into anℓlevel IND‐CCA2 secure HIBE scheme. In addition, our security proof also contains a more efficient simulation tool that might have separate interest in cryptographic applications. Copyright © 2015 John Wiley & Sons, Ltd.

In threshold public-key encryption (TPKE), the decryption key is divided into n shares, each one of which is given to a different decryption user in order to avoid single points of failure. A robust TPKE is that if threshold decryption of a valid ciphertext fails, the combiner can identify the decryption users that supplied invalid partial decryption shares. In this paper, we propose a practical and efficient TPKE scheme which is robust and non-interactive. Security against chosen-ciphertext attacks (CCAs) can be proved in the standard model under the hashed Diffie–Hellman assumption in bilinear groups. The security reduction is tight and simple. We use an instantiation hash function of the Kiltz's key encapsulation mechanism and Lai et al.'s chosen-ciphertext secure technique to construct a TPKE scheme. Moreover, our scheme is more simple and shown to be more efficient than currently existing CCA-secure TPKE schemes.

In this paper, we build a family of chameleon hash functions and strongly unforgeable one-time signature schemes based on the intractability assumption of the discrete logarithm problem (DLP) over inner automorphism groups. Since the DLP assumption over inner automorphism groups does not admit sub-exponential attacks, thus the sizes of the working parameters used in our constructions are shorten significantly. This leads to remarkable gains for our proposals both in running time and in storage space. In addition, as far as we know, this is the first time to build CHF and OTS based on noncommutative groups.

ABSTRACT Two novel public key encryption schemes based on the non‐Abelian factorization problems were proposed. Both of them are proved to be indistinguishable against adaptively chosen ciphertext attack (IND‐CCA2) in the random oracle models. These constructions have the potential to resist Shor's quantum algorithm attack proposed in 1994 and give affirmative answers for the open question announced by Myasnikov, Shpilrain and Ushakov in 2011. Copyright © 2013 John Wiley & Sons, Ltd.

ABSTRACT We propose a new public‐key cryptosystem named conjugacy search problem‐based Diffie–Hellman integrated encryption scheme (CSP‐DHIES), by using conjugation‐related assumptions for a special monoid of matrices of truncated multi‐variable polynomials over the ring ℤ12where the CSP is assumed to be intractable. Our construction can be viewed as the first noncommunicative variant of the well‐known DHIES cryptosystem. Under the assumptions of the intractability of the CSP‐based hash Diffie–Hellman problem and the CSP‐based oracle Diffie–Hellman problem, our scheme is provably secure against both chosen‐plaintext attacks and secure against chosen‐ciphertext attacks. Our proofs are constructed in the standard model. We also discuss the possibility of implementing our proposal using braid groups. Copyright © 2011 John Wiley & Sons, Ltd.