Web 3.0 is the next-generation Internet that enables participants to read, write, and own contents in a decentralized manner. It is mainly driven by blockchain, semantic communication, edge computing, and artificial intelligence, which can construct value networks to achieve participatory economics based on participatory decision making. Web 3.0 can capture the characteristics of blockchain, semantic extraction, and communication to achieve decentralized semantic sharing and transfer information precisely. However, current Web 3.0 solutions focus on the blockchain while overlooking other new technologies' roles in Web 3.0. To further unleash the advantages of semantic extraction and communication in Web 3.0, in this article, we propose a blockchain-based semantic exchange framework to realize fair and efficient interactions. In this framework, we first attempt to tokenize semantic information into Non-Fungible Token (NFT) for semantic exchange. Then we utilize a Stackelberg game to maximize buying and pricing strategies for semantic trading. We also leverage Zero-Knowledge Proof to share authentic semantic information without publishing it before receiving payments, which can achieve a fair and privacy-preserving trading compared with current NFT marketplaces. A case study about urban planning is given to show clearly the proposed mechanisms. Finally, several challenges and opportunities are identified.
The financial sector's adoption of technology-driven data analysis has enhanced operational efficiency and revenue generation by leveraging personal sensitive data. However, the inherent characteristics of blockchain hinder decentralized finance (DeFi) from accessing necessary sensitive user data. To address this challenge, we introduce a protocol that both safeguards user privacy and ensures data availability through the incorporation of homomorphic encryption and zero-knowledge-proof techniques in blockchain technology. This novel protocol helps mitigate privacy risks caused by sensitive data leaks while improving the capital efficiency of the DeFi market. Furthermore, we explore the applicability of these privacy-preserving methods in on-chain ecosystems and cross-border financial applications. Our solution contributes to secure, user-centric solutions for DeFi while upholding principles of decentralization and privacy protection.
<abstract><p>With the continuous development of Internet of Things, finance, big data and many other fields, blockchain has been widely used in these areas for transactions, data sharing, product traceability and so on. Numerous assets have appeared in the blockchain, and there are some levels of conflicts among privacy protection of these assets, transaction transparency and auditability in blockchain; so how to provide privacy preserving, make public verifications and audit the encrypted assets are challenging problems. In this paper, we propose a privacy-preserving transaction scheme with public verification and reliable audit in blockchain. First, we provide privacy preserving of transaction contents based on homomorphic encryption. It is flexible, as we decouple user identity and transaction contents. Then, we propose and design a multiplicative zero-knowledge proof with formal security analysis. Furthermore, several verification rules are defined by us in the scheme, such as balance verification and multiplicative verification based on the proposed multiplicative zero-knowledge proof. Our scheme enables reliable and offline auditing for each transaction, and we aggregate the zero-knowledge proofs to save the ledger space. Finally, we make a security analysis of our proposal in terms of transaction confidentiality, public verification and audit reliability, and we give a performance analysis of the proposed scheme.</p></abstract>
Consumers in electricity markets are becoming more proactive because of the rapid development of demand-response management and distributed energy resources, which boost the transformation of peer-to-peer (P2P) energy-trading mechanisms. However, in the P2P negotiation process, it is a challenging task to prevent private information from being attacked by malicious agents. In this paper, we propose a privacy-preserving, two-party, secure computation mechanism for consensus-based P2P energy trading. First, a novel P2P negotiation mechanism for energy trading is proposed based on the consensus + innovation (C + I) method and the power transfer distribution factor (PTDF), and this mechanism can simultaneously maximize social welfare and maintain physical network constraints. In addition, the C + I method only requires a minimum set of information to be exchanged. Then, we analyze the strategy of malicious neighboring agents colluding to attack in order to steal private information. To defend against this attack, we propose a two-party, secure computation mechanism in order to realize safe negotiation between each pair of prosumers based on Paillier homomorphic encryption (HE), a smart contract (SC), and zero-knowledge proof (ZKP). The energy price is updated in a safe way without leaking any private information. Finally, we simulate the functionality of the privacy-preserving mechanism in terms of convergence performance, computational efficiency, scalability, and SC operations.
The system proposed in this study uses zero-knowledge proof (ZKP) to verify the traceability of wood recorded in a public blockchain. Wood is a byproduct of several states, ranging from standing trees to logs, lumber, and wood products (hereinafter ``wood objects''). The advantage of using the blockchain for record keeping is that participants can freely record the information at their discretion, without any restrictions. However, the openness of the blockchain may allow a malicious third party to introduce disinformation. In this study, we employ ZKP and near-field communication (NFC) chips to eliminate the possibility of disinformation introduction. ZKP is used to prove/validate changes in the state of wood objects, and the unique nonce associated with that state is encrypted and recorded on an NFC chip. The nonce is concealed and id of the wood object is defined as hash value of this nonce. We developed a prototype system based on an Android application and an Ethereum smart contract. We confirm that wood traceability and verification can be performed using the prototype system.
Open access
2 source records
Digital Rights Management and Security
Advanced Steganography and Watermarking Techniques
Xin Liu, Xiaomeng Liu, Ruiling Zhang, Dan Luo · 6 authors
Manhattan distance is mainly used to calculate the total absolute wheelbase of two points in the standard coordinate system. The secure computation of Manhattan distance is a new geometric problem of secure multi-party computation. At present, the existing research secure computing protocols for Manhattan distance cannot resist the attack of malicious participants. In the real scene, the existence of malicious participants makes it necessary to study a solution that can resist malicious attacks. This paper first analyzes malicious attacks of the semi-honest model protocol of computing Manhattan distance and then designs an advanced protocol under the malicious model by using the Goldwasser–Micali encryption system and Paillier encryption algorithm, and utilizing some cryptographic tools such as the cut-choose method and zero-knowledge proof. Finally, the real/ideal model paradigm method is used to prove the security of the malicious model protocol. Compared with existing protocols, the experimental simulation shows that the proposed protocol can resist malicious participant attacks while maintaining high efficiency. It has practical value.
Cooperative perception is an essential and widely discussed application of connected automated vehicles. However, the authenticity of perception data is not ensured, because the vehicles cannot independently verify the event they did not see. Many methods, including trust-based (i.e., statistical) approaches and plausibility-based methods, have been proposed to determine data authenticity. However, these methods cannot verify data without a priori knowledge. In this study, a novel approach of constructing a self-proving data from the number plate of target vehicles was proposed. By regarding the pseudonym and number plate as a shared secret and letting multiple vehicles prove they know it independently, the data authenticity problem can be transformed to a cryptography problem that can be solved without trust or plausibility evaluations. Our work can be adapted to the existing works including ETSI/ISO ITS standards while maintaining backward compatibility. Analyses of common attacks and attacks specific to the proposed method reveal that most attacks can be prevented, whereas preventing some other attacks, such as collusion attacks, can be mitigated. Experiments based on realistic data set show that the rate of successful verification can achieve 70\% to 80\% at rush hours.
The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources and bring extreme enhancements of autonomous operations in terms of grid resilience, security, and reliability. Most effort has been on the design of distributed/decentralized controllers; however, the guarantees of the proper execution of the controls are also essential but relatively less emphasized. A common assumption is that local controllers would fully follow the designated controller dynamics based on the data received from communication channels. Such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. On the other hand, it is impractical for a verifier to repeat all the computations involved in the controls to verify the computational integrity. In this work, we leverage a type of cryptography technology, known as zero-knowledge scalable transparent arguments of knowledge to verify the computational integrity of control algorithms, such that verifiers can check the computational integrity with much less computational burden. The method presented here converts the challenge of data integrity into a subset of computational integrity. In this proof-of-concept paper, our focus will be on projected linear dynamics that are commonly seen in distributed/decentralized power system controllers. In particular, we have derived polynomial conditions in the context of zk-STARKs for the projected linear dynamics.
The audit log is a crucial component to monitor fine-grained operations over sensitive data (e.g., personal, health) for security inspection and assurance. Since such data operations can be highly sensitive, it is vital to ensure that the audit log achieves not only validity and immutability, but also confidentiality against active threats to standard data regulations (e.g., HIPAA) compliance. Despite its critical needs, state-of-the-art privacy-preserving audit log schemes (e.g., Ghostor (NSDI '20), Calypso (VLDB '19)) do not fully obtain a high level of privacy, integrity, and immutability simultaneously, in which certain information (e.g., user identities) is still leaked in the log. In this paper, we propose Harpocrates, a new privacy-preserving and immutable audit log scheme. Harpocrates permits data store, share, and access operations to be recorded in the audit log without leaking sensitive information (e.g., data identifier, user identity), while permitting the validity of data operations to be publicly verifiable. Harpocrates makes use of blockchain techniques to achieve immutability and avoid a single point of failure, while cryptographic zero-knowledge proofs are harnessed for confidentiality and public verifiability. We analyze the security of our proposed technique and prove that it achieves non-malleability and indistinguishability. We fully implemented Harpocrates and evaluated its performance on a real blockchain system (i.e., Hyperledger Fabric) deployed on a commodity platform (i.e., Amazon EC2). Experimental results demonstrated that Harpocrates is highly scalable and achieves practical performance.
Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun
Over the past few years, AI methods of generating images have been increasing in capabilities, with recent breakthroughs enabling high-resolution, photorealistic "deepfakes" (artificially generated images with the purpose of misinformation or harm). The rise of deepfakes has potential for social disruption. Recent work has proposed using ZK-SNARKs (zero-knowledge succinct non-interactive argument of knowledge) and attested cameras to verify that images were taken by a camera. ZK-SNARKs allow verification of image transformations non-interactively (i.e., post-hoc) with only standard cryptographic hardness assumptions. Unfortunately, this work does not preserve input privacy, is impractically slow (working only on 128$\times$128 images), and/or requires custom cryptographic arguments. To address these issues, we present zk-img, a library for attesting to image transformations while hiding the pre-transformed image. zk-img allows application developers to specify high level image transformations. Then, zk-img will transparently compile these specifications to ZK-SNARKs. To hide the input or output images, zk-img will compute the hash of the images inside the ZK-SNARK. We further propose methods of chaining image transformations securely and privately, which allows for arbitrarily many transformations. By combining these optimizations, zk-img is the first system to be able to transform HD images on commodity hardware, securely and privately.
Open access
2 source records
Digital Media Forensic Detection
Adversarial Robustness in Machine Learning
Generative Adversarial Networks and Image Synthesis
With the increasing value of various kinds of data in the era of big data, the demand of different subjects for data transactions has become more and more urgent. In this paper, a blockchain-based data transaction protection scheme is proposed to realize the secure transaction sharing among data. This paper carries out the following work: by analyzing the existing data transaction models, we find the data security and transaction protection problems, establish a third-party-free data transaction platform using blockchain, protect users’ data security by combining AES and improved homomorphic encryption technology, and upload the encrypted data to the Interplanetary File System (IPFS) for distributed storage. Finally, we use the powerful functions of the IPFS, combined with inadvertent transmission protocol, two-way authentication, zero-knowledge proof, and other security verification for data transactions. The security analysis proves that this scheme has higher security despite the time overhead, and we will continue to optimize the scheme to improve efficiency in the future.
Carsten Baum, Robin Jadoul, Emmanuela Orsini, Peter Schöll · 5 authors
Zero-Knowledge protocols have increasingly become both popular and practical in recent years due to their applicability in many areas such as blockchain systems. Unfortunately, public verifiability and small proof sizes of zero-knowledge protocols currently come at the price of strong assumptions, large prover time, or both, when considering statements with millions of gates. In this regime, the most prover-efficient protocols are in the designated verifier setting, where proofs are only valid to a single party that must keep a secret state.
Tim Güneysu, Philip Hodges, Georg Land, Mike Ounsworth · 6 authors
Certificate authorities in public key infrastructures typically require entities to prove possession of the secret key corresponding to the public key they want certified. While this is straightforward for digital signature schemes, the most efficient solution for public key encryption and key encapsulation mechanisms (KEMs) requires an interactive challenge-response protocol, requiring a departure from current issuance processes. In this work we investigate how to non-interactively prove possession of a KEM secret key, specifically for lattice-based KEMs, motivated by the recently proposed KEMTLS protocol which replaces signature-based authentication in TLS 1.3 with KEM-based authentication. Although there are various zero-knowledge (ZK) techniques that can be used to prove possession of a lattice key, they yield large proofs or are inefficient to generate. We propose a technique called verifiable generation, in which a proof of possession is generated at the same time as the key itself is generated. Our technique is inspired by the Picnic signature scheme and uses the multi-party-computation-in-the-head (MPCitH) paradigm; this similarity to a signature scheme allows us to bind attribute data to the proof of possession, as required by certificate issuance protocols. We show how to instantiate this approach for two lattice-based KEMs in Round 3 of the NIST post-quantum cryptography standardization project, Kyber and FrodoKEM, and achieve reasonable proof sizes and performance. Our proofs of possession are faster and an order of magnitude smaller than the previous best MPCitH technique for knowledge of a lattice key, and in size-optimized cases can be comparable to even state-of-the-art direct lattice-based ZK proofs for Kyber. Our approach relies on a new result showing the uniqueness of Kyber and FrodoKEM secret keys, even if the requirement that all secret key components are small is partially relaxed, which may be of independent interest for improving efficiency of zero-knowledge proofs for other lattice-based statements.
Lorenzo Grassi, Dmitry Khovratovich, Reinhard Lüftenegger, Christian Rechberger · 6 authors
We propose a new hash function Reinforced Concrete, which is the first generic purpose hash that is fast both for a zero-knowledge prover and in native x86 computations. It is suitable for a various range of zero-knowledge proofs and protocols, from set membership to generic purpose verifiable computation. Being up to 15x faster than its predecessor Poseidon hash, Reinforced Concrete inherits security from traditional time-tested schemes such as AES, whereas taking the zero-knowledge performance from a novel and efficient decomposition of a prime field into compact buckets.
We study the problem of constructing succinct zero knowledge proof systems for floating point computations. The standard approach to handle floating point computations requires conversion to binary circuits, following the IEEE-754 floating point standard. This approach incurs a poly(w) overhead in prover efficiency for computations with w-bit precision, resulting in very high prover runtimes -- already the key bottleneck in the design of succinct arguments. We make the following contributions: -We propose a new model for verifying floating point computations that guarantees approximate correctness w.r.t. a relative error bound. This model is inspired by numerical analysis, and is very meaningful for applications such as machine learning and scientific computing. -Using this model, we present a general method for constructing succinct zero-knowledge proofs for floating point computations starting from existing public-coin "commit-and-prove'' systems. For computations with w-bit precision, our approach incurs only a log(w) overhead in prover running time. Our compiler nearly preserves (up to a factor of 2) the communication complexity of the underlying protocol, and requires sub-linear verification time. The resulting proof can be made non-interactive in the random oracle model. Concretely, our scheme is ~57x faster than the method following IEEE standard exactly [35] for 32-bit floating point computations. Central to our main result, and of independent interest, is a new batch range proof system in standard prime order groups that does not rely on bit decomposition.
Ning Luo, Timos Antonopoulos, William R. Harris, Ružica Piskač · 6 authors
Zero-knowledge (ZK) protocols enable one party to prove to others that it knows a fact without revealing any information about the evidence for such knowledge. There exist ZK protocols for all problems in NP, and recent works developed highly efficient protocols for proving knowledge of satisfying assignments to Boolean formulas, circuits and other NP formalisms. This work shows an efficient protocol for the converse: proving formula unsatisfiability in ZK (when the prover posses a non-ZK proof). An immediate practical application is efficiently proving safety of secret programs.
In recent years, with 5G and other key technology breakthroughs, IoT technology is accelerating penetration into various industries, and the era of Internet of Everything is coming. However, while the industry is promoting the rapid development of industrial IoT, IoT security issues are also coming up. Based on this, this paper proposes a data privacy protection method for the smart IoT platform, which first adopts zero-knowledge identity proof technology to complete the identity access authentication of a large number of IoT terminal devices; then the data is downscaled and aggregated in the intermediate data collection device, and then the processed data is added to the noise based on Laplace distribution, and finally the data is transmitted to the main server, thus realizing the smart IoT platform Data privacy protection in the process of data transmission.
The assignment problem is an essential problem in many application fields and frequently used to optimize resource usage. The problem is well understood and various efficient algorithms exist to solve the problem. However, it was unclear what practical performance could be achieved for privacy-preserving implementations based on multiparty computation (MPC) by leveraging more efficient solution strategies than MPC-based generic simplex solvers for linear programs. We solve this question by implementing and comparing different optimized MPC algorithms to solve the assignment problem for reasonable problem sizes. Our empirical approach revealed various insights to MPC-based optimization and we measured a significant (50x) speed-up compared to the known simplex-based approach. Furthermore, we also study the overhead introduced by making the results publicly verifiable by means of non-interactive zero-knowledge proofs. By leveraging modern proof systems we also achieve significant speed-up for proof and verification times compared to the previously proposed approaches as well as compact proof sizes. Our research was motivated by a real-world use case, based on detailed discussions with representative stakeholders from the aviation industry.
This brief addresses the robust lateral control problem for self-driving racecars. It proposes a discrete-time estimation and control solution consisting of a delayed unknown input-state observer (UIO) and a robust tracking controller. Based on a nominal vehicle model, describing its motion with respect to a generic desired trajectory and requiring no information about the surrounding environment, the observer reconstructs the total force disturbance signal, resulting from imperfect knowledge of the time-varying tire-road interface characteristics, presence of other vehicles nearby, wind gusts, and other model uncertainty. Then, the controller actively compensates the estimated force and asymptotically steers the tracking error to zero. The brief also presents a closed-loop stability proof of the method, ensuring perfect asymptotic estimation and tracking by the controlled vehicle. The proposed solution advantageously needs no a-priori information about the total disturbance boundedness, additional variables to model uncertainty, or observer parameters to be tuned. Its effectiveness and superiority to existing methods are studied in theory and shown in simulations where a full racecar model, based on the vehicle dynamics blockset, is required to track aggressive maneuvers. Through a faster and more accurate disturbance estimation, the solution robustly ensures better dynamic responses even with measurement noise.
Jin Wang, Wei Ou, Osama Alfarraj, Amr Tolba · 6 authors
Since transactions in blockchain are based on public ledger verification, this raises security concerns about privacy protection. And it will cause the accumulation of data on the chain and resulting in the low efficiency of block verification, when the whole transaction on the chain is verified. In order to improve the efficiency and privacy protection of block data verification, this paper proposes an efficient block verification mechanism with privacy protection based on zero-knowledge proof (ZKP), which not only protects the privacy of users but also improves the speed of data block verification. There is no need to put the whole transaction on the chain when verifying block data. It just needs to generate the ZKP and root hash with the transaction information, then save them to the smart contract for verification. Moreover, the ZKP verification in smart contract is carried out to realize the privacy protection of the transaction and efficient verification of the block. When the data is validated, the buffer accepts the complete transaction, updates the transaction status in the cloud database, and packages up the chain. So, the ZKP strengthens the privacy protection ability of blockchain, and the smart contracts save the time cost of block verification.
Moyixi Lei, Shuangyin Liu, Na Luo, Xinting Yang · 5 authors
Traceability systems have changed the way food safety is managed and data is stored. Blockchain tracking services now provide customers with an infrastructure that allows them to easily access data online. However, there are limitations to these new capabilities, such as a lack of transparency and the existence of privacy and security challenges. Additionally, as the need for more agile, private, and traceability secure data solutions continues to grow exponentially, rethinking the current structure of blockchain agricultural traceability is mission-critical for a country. By leveraging and building upon blockchain's unique attributes, including tamper-evident, security hash crypto-data, and distributed ledger, we have proposed a prototype that allows traceability data to be reliably stored via blockchain while simultaneously being secured, with completeness auditing to enhance credibility. The result, the trusted auditing chain (TA chain), is a flexible solution that assures data security and solves challenges such as scalability and privacy-preserving. The TA chain works through Schnorr-style non-interactive Zero-knowledge proof to support security automatical choose privacy augmented. In addition, The TA chain can audit more than 1000 transactions within 1ms, and its error stabilizes below the 250 μs, which proves a security and fair traceability system to assure that data is distributed and reliably, and provably audited.
We study the problem of simultaneously addressing both ballot stuffing and participation privacy for pollsite voting systems. Ballot stuffing is the attack where fake ballots (not cast by any eligible voter) are inserted into the system. Participation privacy is about hiding which eligible voters have actually cast their vote. So far, the combination of ballot stuffing and participation privacy has been mostly studied for internet voting, where voters are assumed to own trusted computing devices. Such approaches are inapplicable to pollsite voting where voters typically vote bare handed. We present an eligibility audit protocol to detect ballot stuffing in pollsite voting protocols. This is done while protecting participation privacy from a remote observer - one who does not physically observe voters during voting. Our protocol can be instantiated as an additional layer on top of most existing pollsite E2E-V voting protocols. To achieve our guarantees, we develop an efficient zero-knowledge proof (ZKP), that, given a value $v$ and a set $Φ$ of commitments, proves $v$ is committed by some commitment in $Φ$, without revealing which one. We call this a ZKP of reverse set membership because of its relationship to the popular ZKPs of set membership. This ZKP may be of independent interest.
Miguel Díaz Montiel, Rachid Guerraoui, Pierre-Louis Roman
Blockchain intercommunication systems enable the exchanges of messages between blockchains. This interoperability promotes innovation, unlocks liquidity and access to assets. However, blockchains are isolated systems that originally were not designed for interoperability. This makes cross-chain communication, or bridges for short, insecure by nature. More precisely, cross-chain systems face security challenges in terms of selfish rational players such as maximal extractable value (MEV) and censorship. We propose to solve these challenges using zero knowledge proofs (ZKPs) for cross-chain communication. Securing cross-chain communication is remarkably more complex than securing single-chain events as such a system must preserve user security against both on- and off-chain analysis. To achieve this goal, we propose the following pair of contributions: the DACT protocol and the SurferMonkey infrastructure that supports the DACT protocol. The DACT protocol is a global solution for the anonymity and security challenges of agnostic blockchain intercommunication. DACT breaks on- and off-chain analysis thanks to the use of ZKPs. SurferMonkey is a decentralized infrastructure that implements DACT in practice. Since SurferMonkey works at the blockchain application layer, any decentralized application (dApp) can use SurferMonkey to send any type of message to a dApp on another blockchain. With SurferMonkey, users can neither be censored nor be exposed to MEV. By applying decentralized proactive security, we obtain resilience against selfish rational players, and raise the security bar against cyberattacks. We have implemented a proof of concept (PoC) of SurferMonkey by reverse engineering Tornado Cash and by applying IDEN3 ZKP circuits. SurferMonkey enables new usecases, ranging from anonymous voting and gaming, to a new phase of anonymous decentralized finance (aDeFi).