With one billion users using 380 exchanges, the security of blockchains and cryptocurrencies remains a major concern as billions are lost to hackers every year. Cryptocurrency hacks negatively impact cryptocurrency markets introducing volatility. Each major scam/hack incident results in a significant price dip for most cryptocurrencies, decelerating the growth of the blockchain economy. Existing blockchain vulnerabilities are further amplified by the impending existential threat from quantum computers. While there’s no reprieve yet from the scam/hack prone blockchain economy, quantum resilience is being aggressively pursued by post quantum cryptography (PQC) researchers, despite 80 of 82 candidate PQCs failing. As PQC has no role in combating inherent vulnerabilities, securing over 1000 existing blockchains against scammers/hackers remains a top priority for this industry. This research proposes a novel Quantum-safe Ledger Technology (QLT) framework that not only secures DLTs/cryptocurrencies and exchanges from current vulnerabilities but protects them from the impending Q-day threats from future quantum computers. As blockchain-agnostic technology, the QLT framework can be easily adapted to secure any blockchain or crypto exchange.
Zeng Huang, Ming‐Tian Zhang, Tengfei Liu, Anjia Yang
Federated learning is an important distributed model training technique in Internet of Things (IoT), in which participant selection is a key component that plays a role in improving training efficiency and model accuracy. This module enables a central server to select a subset of participants to perform model training based on data and device information. By doing so, selected participants are rewarded and actively perform model training, while participants that are detrimental to training efficiency and model accuracy are excluded. However, in practice, participants may suspect that the central server may have miscalculated and thus not made the selection honestly. This lack of trustworthiness problem, which can demotivate participants, has received little attention. Another problem that has received little attention is the leakage of participants’ private information during the selection process. We will therefore propose a federated learning framework with auditable participant selection. It supports smart contracts in selecting a set of suitable participants based on their training loss without compromising the privacy. Considering the possibility of malicious campaigning and impersonation of participants, the framework employs commitment schemes and zero-knowledge proofs to counteract these malicious behaviors. Finally, we analyze the security of the framework and conduct a series of experiments to demonstrate that the framework can effectively improve the efficiency of federated learning.
Interest in supporting Federated Learning (FL) using blockchains has grown significantly in recent years. However, restricting access to the trained models only to actively participating nodes remains a challenge even today. To address this concern, we propose a methodology that incentivizes model parameter sharing in an FL setup under Local Differential Privacy (LDP). The nodes that share less obfuscated data under LDP are awarded higher quantum of tokens, which they can later use to obtain session keys for accessing encrypted model parameters updated by the server. If one or more of the nodes do not contribute to the learning process by sharing their data, or share only highly perturbed data, they earn less number of tokens. As a result, such nodes may not be able to read the new global model parameters if required. Local parameter sharing and updating of global parameters are done using the distributed ledger of a permissioned blockchain, namely HyperLedger Fabric (HLF). Being a blockchain-based approach, the risk of a single point of failure is also mitigated. Appropriate chaincodes, which are smart contracts in the HLF framework, have been developed for implementing the proposed methodology. Results of an extensive set of experiments firmly establish the feasibility of our approach.
Weiqi Dai, Jinkai Liu, Yang Zhou, Kim‐Kwang Raymond Choo · 7 authors
While blockchain is known to support open and transparent data exchange, partly due to its nontamperability property, it can also be (ab)used to facilitate the spreading of fake and misleading information or information that was subsequently discredited. Hence, this paper proposes a practical, redactable blockchain framework with a public trapdoor (hereafter referred to as PRBFPT). PRBFPT comprises an editing scheme for adding blocks using a new type of blockchain with a chameleon hash. Specifically, PRBFPT is able to involve all nodes in the blockchain in the editing operations by means of a public trapdoor, without requiring additional trapdoor management by predefined nodes or organizations. PRBFPT is also designed to audit and record the content of each editing operation. In other words, after editing and deleting the original data, PRBFPT can still verify its legitimacy. We also propose a contract-based locked voting scheme to better support voting. We then evaluate the prototype implementation of PRBFPT, whose findings show that the total time consumption of adding modules is at the millisecond level, with a negligible impact on the performance of the original system. In addition, the evaluation findings show that the cost of initiating the special transactions is comparable to the consumption of normal Ethereum transactions and is within a manageable range.
Commitment schemes are cryptographic schemes that can be applied to zero-knowledge proof construction and blockchain construction. Recently, lattice-based cryptography has been intensively investigated due to the promising potential in quantum cryptography. Accordingly, commitment schemes based on lattice assumptions have been studied for practical applications. Notably, applications often require committing an arbitrary message with low communication costs, so commitment schemes must be satisfied with fewer length restrictions and fewer extensions to the messages. Several studies have been conducted to achieve the problem, including the study published by Baum et al. in 2018. However, the scheme in question still utilizes the message domain for extraneous purposes. We design a length-extension-free commitment scheme ComMWMin which the length of the message string is large relative to the length of the commitment string, improving on the commitment scheme of Baum et al. Furthermore, we prove that the hiding and binding properties of ComMWMare based on the hardness of the decisional search knapsack problem and extended search knapsack problems, respectively. Finally, we evaluate the computation costs of generating commitment value between ours and Baum et al.’s commitment scheme.
Charity donations are a critical mechanism for social resource distribution. However, traditional donation systems, typically centralized, are prone to issues such as data redundancy, vulnerability to single-point failures, and a deficiency in transparency and traceability. Although blockchain-based donation programs have emerged to address trust issues inherent in centralized models, they often neglect critical security concerns like privacy protection and identity authentication. This paper introduces Eisdspa, a blockchain-based donation system designed to offer identity authentication, auditability, and privacy protection. Specifically, we introduce an identity credential system that facilitates anonymous donations, shielding the identities of both donors and donees through the use of BBS+ signatures and zero-knowledge proofs of knowledge (ZKPoKs). Additionally, we ensure the integrity of goods donations by offering robust auditability and protecting user privacy with Pedersen commitments and ZKPoKs. We formally define the privacy aspects of Eisdspa and conduct a security analysis of the system under the random oracle model. A prototype implementation of the scheme, along with a comparative analysis with existing solutions, highlights the benefits of Eisdspa. Moreover, we assess the computational efficiency of Eisdspa, with experimental results indicating its high performance in computational overhead.
<abstract><p>The rapid development of blockchain transactions highlights the importance of privacy protection (including anonymity and confidentiality) and underscores the necessity for auditability. Some schemes, such as PGC and Miniledger, support privacy protection and auditability. However, they only offer incomplete privacy protection (i.e., supporting anonymity or confidentiality exclusively). In response to these issues, we propose a scheme that achieves partial anonymity, confidentiality, auditability, and traceability. By integrating a variant of Pedersen commitments and randomizable signatures, we achieve partial anonymity for users and the auditability of transactions, thereby protecting user privacy under audit conditions. Based on the twisted ElGamal encryption algorithm and specially constructed zero-knowledge proofs, we achieve confidentiality of transaction amounts under legal and regulatory conditions. System test results indicate that this scheme effectively meets the above requirements. The feasibility of this scheme is confirmed through system testing, comparative analysis, and security analysis.</p></abstract>
The dynamic landscape of the Internet of Things (IoT) is set to revolutionize the pace of interaction among entities, ushering in a proliferation of applications characterized by heightened quality and diversity. Among the pivotal applications within the realm of IoT, as a significant example, the Smart Grid (SG) evolves into intricate networks of energy deployment marked by data integration. This evolution concurrently entails data interchange with other IoT entities. However, there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT ecosystem. In this paper, we introduce a hierarchical secure data-sharing platform empowered by cloud-fog integration. Furthermore, we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data, especially SG data. The security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data providers. Compared with previous IoT data sharing schemes, the proposed scheme has advantages in both computational and transmission efficiency, and has more superiority with the increasing volume of shared data or increasing number of participants.
The increased internet usage after the pandemic led the UN Forum to improve cybersecurity measures, with zero-knowledge proofs (ZKP) being a viable solution for securing confidential information. ZKP protocols can be demonstrated through the binary puzzle, an NP-complete logic puzzle with four specific constraints. The key contribution of this paper is its successful implementation of the genetic algorithm as a new method to solve the binary puzzle. The optimized fitness function determined the solution at an average of 1.33-2.33 generations for populations ranging from 100 to 500. Its quadratic property calculated the solution faster than the ordinary linear fitness function.
Omar Ahmed, Charles Gouert, Nektarios Georgios Tsoutsos
Cloud computing has been a prominent technology that allows users to store their data and outsource intensive computations. However, users of cloud services are also concerned about protecting the confidentiality of their data against attacks that can leak sensitive information. Although traditional cryptography can be used to protect static data or data being transmitted over a network, it does not support processing of encrypted data. Homomorphic encryption can be used to allow processing directly on encrypted data, but a dishonest cloud provider can alter the computations performed, thus violating the integrity of the results. To overcome these issues, we propose PEEV (Parse, Encrypt, Execute, Verify), a framework that allows a developer with no background in cryptography to write programs operating on encrypted data, outsource computations to a remote server, and verify the correctness of the computations. The proposed framework relies on homomorphic encryption techniques as well as zero-knowledge proofs to achieve verifiable privacy-preserving computation. It supports practical deployments with low performance overheads and allows developers to express their encrypted programs in a high-level language, abstracting away the complexities of encryption and verification.
Muhammad Noman Sohail, Adeel Anjum, Iftikhar Ahmed Saeed, Madiha Haider Syed · 6 authors
Connecting smart industrial components to computer networks revolutionizes business operations. However, in the Industrial Internet of Things (IIoT), the sharing of data has bandwidth, computational, and privacy issues. Researchers presented cloud computing and fine-grained access control to overcome these challenges. However, traditional centralized computing systems involve single points of failure. To mitigate these challenges, we have proposed a secure and incentive-based data-sharing framework for IIoT systems using blockchain technology. We leverage blockchain due to its ability to provide secure and tamper-resistant data storage and sharing as participants store their data on a distributed ledger (DL), preventing unauthorized access. A security protocol is designed that utilizes the properties of elliptic curve cryptography (ECC). Moreover, Shapley value is employed to calculate revenue and distribute it fairly. To perform the formal security evaluation, we have conducted extensive simulations using the Automated Validation of Internet Security Protocols and Applications (AVISPA) and Scyther protocol simulation tools, which demonstrated that our protocol is robust against various adversarial attacks. The experimental results show that the proposed incentive distribution framework demonstrated fairness in the distribution of revenue among participants.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Apurva K. Vangujar, Buvana Ganesh, Alia Umrani, Paolo Palmieri
This article presents a novel e-voting scheme that combines Group Identity-based Identification (GIBI) with Homomorphic Encryption (HE) based on the discrete logarithmic assumption. The proposed scheme uses the Schnorr-like GIBI scheme for voter identification and authorization using zero-knowledge proofs to ensure the anonymity and eligibility of voters. The voter$\textsf {v}_{i,j}$is granted the authorization to cast a valid vote for a single candidate$\textsf {C}_{k}$. The use of distributed ElGamal provides fairness while the use of partial shares for decryption enables individual and universal verifiability without the need for a central authority. The proposed scheme is secure under various scenarios and robust in the random oracle model. The GIBI-HE scheme offers a promising solution for e-voting, providing a sustainable and accessible environment for voters while supporting the unreusability of votes and protecting the privacy of voters.
Threshold signatures, notably ECDSA, are fundamental for securing decentralized applications.Their non-linear structure poses challenges in distributed signing, often tackled by pairwise multiplicative-to-additive share conversion, leading to O(n) communication and O(n 2 ) verification costs for each of n signers.Moreover, most schemes lack robustness, necessitating a complete restart upon fault.A pioneering work by Wong et al. (NDSS '23) still requires rolling back to the preceding round to resume signing after another round to convince all other signers.We revisit secure multiparty computation from threshold linearly homomorphic encryption (LHE).Realizing its public verifiability and fault recovery, we encompass two technical contributions to Castagnos-Laguillaumie LHE (CT-RSA '15): a 2-round robust distributed key generation (DKG) protocol in the dishonest majority setting and an accompanying zero-knowledge proof allowing extraction in an unknown-order group.We extend the DKG with dual-code-based verification (ACNS '17), upgrading its O(tn 2 )-cost private verifiability to an O(n 2 ) public one.Built on our DKG, we present the first threshold ECDSA protocol with O(1) communication and O(n) verification perparty costs while matching the lowest round complexity of nonrobust schemes (CCS '20).Empirically, we halve the computation and communication costs of the signing phase compared to stateof-the-art robust threshold ECDSA (NDSS '23).We also illustrate the versatility of our techniques with an improved threshold extension (IEEE S&P '23) of BBS+ signatures (IEEE Syst.J. '13).
Lennart Braun, Guilhem Castagnos, Ivan Damgård, Fabien Laguillaumie · 7 authors
We present distributed key generation and decryption protocols for an additively homomorphic cryptosystem based on class groups, improving on a similar system proposed by Braun, Damgård, and Orlandi at CRYPTO ‘23. Our key generation is similarly constant round but achieves lower communication complexity than the previous work. This improvement is in part the result of relaxing the reconstruction property required of the underlying integer verifiable secret sharing scheme. This eliminates the reliance on potentially costly proofs of knowledge in unknown order groups. We present a new method to batch zero-knowledge proofs in unknown order groups which strengthens these improvements. We also present a protocol which is proven secure against adaptive adversaries in the single inconsistent player (SIP) model. Our protocols are secure in the universal composability (UC) framework and provide guaranteed output delivery. We demonstrate the relative efficiency of our techniques by presenting the running times and communication costs associated with our implementation of the statically secure protocol and provide a direct comparison with alternate state of the art constructions.
Thế Dũng Bùi, Geoffroy Couteau, Pierre Meyer, Alain Passelègue · 5 authors
Pseudorandom Correlation Functions (PCFs) allow two parties, given correlated evaluation keys, to locally generate arbitrarily many pseudorandom correlated strings, e.g. Oblivious Transfer (OT) correlations, which can then be used by the two parties to jointly run secure computation protocols. In this work, we provide a novel and simple approach for constructing PCFs for OT correlation, by relying on constrained pseudorandom functions for a class of constraints containing a weak pseudorandom function (wPRF). We then show that tweaking the Naor-Reingold pseudorandom function and relying on low-complexity pseudorandom functions allow us to instantiate our paradigm. We further extend our ideas to obtain efficient public-key PCFs, which allow the distribution of correlated keys between parties to be non-interactive: each party can generate a pair of public/secret keys, and any pair of parties can locally derive their correlated evaluation key by combining their secret key with the other party’s public key. In addition to these theoretical contributions, we detail various optimizations and provide concrete instantiations of our paradigm relying on the Boneh-Ishai-Passelègue-Sahai-Wu wPRF and the Goldreich-Applebaum-Raykov wPRF. Putting everything together, we obtain public-key PCFs with a throughput of 15k–40k OT/s, which is of a similar order of magnitude to the state-of-the-art interactive PCFs and about 4 orders of magnitude faster than state-of-the art public-key PCFs. As a side result, we also show that public-key PCFs can serve as a building block to construct reusable designated-verifier non-interactive zero-knowledge proofs (DV-NIZK) for NP. Combined with our instantiations, this yields simple and efficient reusable DV-NIZKs for NP in pairing-free groups.