We provide a generic construction to turn any classical Zero-Knowledge (ZK) protocol into a composable (quantum) oblivious transfer (OT) protocol, mostly lifting the round-complexity properties and security guarantees (plain-model/statistical security/unstructured functions...) of the ZK protocol to the resulting OT protocol. Such a construction is unlikely to exist classically as Cryptomania is believed to be different from Minicrypt. In particular, by instantiating our construction using Non-Interactive ZK (NIZK), we provide the first round-optimal (2-message) quantum OT protocol secure in the random oracle model, and round-optimal extensions to string and k-out-of-n OT. At the heart of our construction lies a new method that allows us to prove properties on a received quantum state without revealing additional information on it, even in a non-interactive way, without public-key primitives, and/or with statistical guarantees when using an appropriate classical ZK protocol. We can notably prove that a state has been partially measured (with arbitrary constraints on the set of measured qubits), without revealing any additional information on this set. This notion can be seen as an analog of ZK to quantum states, and we expect it to be of independent interest as it extends complexity theory to quantum languages, as illustrated by the two new complexity classes we introduce, ZKstatesQIP and ZKstatesQMA.
Lorena Chinchilla-Romero, Jonathan Prados-Garzon, Pablo Muñoz, Pablo Ameigeiras · 5 authors
Multi-Wireless Access Technology (WAT) Radio Access Networks (RANs) are becoming a key enabler in 5G and beyond networks due to the public spectrum scarcity, the level of signal confinement and security offered by some wireless technologies (e.g., Light Fidelity (Li-Fi)), and the reduction of the deployment and operational costs. For instance, Wireless Fidelity (Wi-Fi) technology is cheaper and easier to manage than 5G, and leveraging their already deployed infrastructures contributes to capital expenditures saving. Developing autonomous radio resource provisioning (RRP) solutions is fundamental to cost-effectively achieve the zero-touch management in private 5G networks while fulfilling the service requirements. However, modelling the Key Performance Indicators of the radio interface in 5G and beyond is a complex task that requires high-domain knowledge. Furthermore, the resulting models, as well as solving the respective RRP optimization problem using exact methods usually offer a high computational complexity, especially in multi-WAT scenarios. In order to cope with these issues, in this work, we propose an initial design of a Deep Reinforcement Learning-assisted solution for the RRP in a multi-WAT private 5G network. Furthermore, we contex-tualize the solution in the Open RAN architecture framework. A simulation-based proof-of-concept validates the proposal’s proper design and operation considering a realistic private 5G network scenario.
There has been a shift towards the use of Electric Vehicles (EV) in recent years. Though EVs offer many advantages, there are concerns on the cyber security of its components and the privacy of its users. When users charge their EVs at a charging station, they need to reveal their personal details. An attacker can compromise the users' privacy by identifying and tracking where users charge their EVs. Hence, there is a need to protect EVs from cyber-attacks and preserve its users' privacy. In this paper, we address the problem of privacy preservation of users while charging their EVs in a 5G-enabled vehicular charging system. We propose a user-centric authentication protocol for EV charging based on Decentralized Identifier (DID) and blockchain. We use Verifiable Credential (VC) together with DID which provides Zero-Knowledge Proof (ZKP) about the user. Users have complete control over their identities resulting in user-centric authentication. At the same time, a third party can verify the user's legitimacy before providing services. Hence, our protocol makes the charging service available in a secure way, preserving the privacy of the user.
Maryam Sheikhi Garjan, N. Gamze ORHON KILIÇ, Murat Cenk
The increasing demand for secure and anonymous transactions raises the popularity of ring signatures, which is a digital signature scheme that allows identifying a group of possible signers without revealing the identity of the actual signer. This paper presents efficient supersingular isogeny-based ring signature and linkable ring signature schemes that will find potential applications in post-quantum technologies. We develop the ring signature scheme by applying the Fiat-Shamir transform on the sigma protocol for a ring which we obtain from the supersingular isogeny-based interactive zero-knowledge identification scheme by adopting the scheme for a ring. We also extend our ring signature protocol with an additional parameter, i.e., a tag that provides to detect if a signer issues two signatures concerning the same ring by preserving anonymity and linkable anonymity. The signature size of our ring signature protocols increases logarithmically in the size of the ring thanks to the Merkle trees. We show the security proofs and efficiency analyses of the protocols offered. Moreover, we provide the implementation results of the supersingular isogeny-based ring signature, which offers small signature sizes for NIST post-quantum security levels.
We consider a project (model) owner that would like to train a model by utilizing the local private data and compute power of interested data owners, i.e., trainers. Our goal is to design a data marketplace for such decentralized collaborative/federated learning applications that simultaneously provides i) proof-of-contribution based reward allocation so that the trainers are compensated based on their contributions to the trained model; ii) privacy-preserving decentralized model training by avoiding any data movement from data owners; iii) robustness against malicious parties (e.g., trainers aiming to poison the model); iv) verifiability in the sense that the integrity, i.e., correctness, of all computations in the data market protocol including contribution assessment and outlier detection are verifiable through zero-knowledge proofs; and v) efficient and universal design. We propose a blockchain-based marketplace design to achieve all five objectives mentioned above. In our design, we utilize a distributed storage infrastructure and an aggregator aside from the project owner and the trainers. The aggregator is a processing node that performs certain computations, including assessing trainer contributions, removing outliers, and updating hyper-parameters. We execute the proposed data market through a blockchain smart contract. The deployed smart contract ensures that the project owner cannot evade payment, and honest trainers are rewarded based on their contributions at the end of training. Finally, we implement the building blocks of the proposed data market and demonstrate their applicability in practical scenarios through extensive experiments.
The Internet of Things (IoT) is ubiquitous in our lives. However, the inherent vulnerability of IoT smart devices can lead to the destruction of networks in untrustworthy environments. Therefore, authentication is a necessary tool to ensure the legitimacy of nodes and protect data security. Naturally, the authentication factors always include various sensitive users’ information, such as passwords, ID cards, even biological information, etc. How to prevent privacy leakage has always been a problem faced by the IoT. Zero-knowledge authentication is a crucial cryptographic technology that uses authenticates nodes on the networks without revealing identity or any other data entered by users. However, zero-knowledge proof (ZKP) requires more complex data exchange protocols and more data transmission compared to traditional cryptography technologies. To understand how zero-knowledge authentication works in IoT, we produce a survey on zero-knowledge authentication in privacy-preserving IoT in the paper. First, we overview the IoT architecture and privacy, including security challenges and open question in different IoT layers. Next, we overview zero-knowledge authentication and provide a comprehensive analysis of designing zero-knowledge authentication protocols in various IoT networks. We summarize the advantages of ZKP-based authentication in IoT. Finally, it summarizes the potential problems and future directions of ZKP in IoT.
Zero-knowledge proof is one of the techniques implemented in a variety of data security applications. ZKP is a security procedure between two parties, one as the prover and the other as the verifier. The prover and the verifier exchange information without allowing any kind of sensitive information to leak. In this paper, we mention the challenges and limitations that face the zero-knowledge technique when utilized in authentication and privacy protection processes in different environments. We help to produce improvements to the most common zero-knowledge protocol to show many factors that would have greatly contributed to the success of the authentication process.
Abstract As an electronic form of traditional voting, electronic voting is becoming more and more popular in today’s information society. Most of the existing electronic voting protocols need a trusted center to calculate the voting result, but the requirement of a trusted center is often unrealistic and prone to single point of failure. In this regard, the decentralized electronic voting protocols based on blockchain have been proposed. Unfortunately, most existing blockchain-based voting protocols fail to ensure anonymity, legitimacy, and correctness of counting. Besides, they do not satisfy robustness, i.e., the voting result cannot be counted in the event of voter abstention. To address the above challenges, we propose a novel blockchain-based self-tallying voting protocol, where the group signature and zero-knowledge proof are utilized in a way that the voter can securely distribute anonymous and unlinkable electronic ballots, thereby guaranteeing complete anonymity and legitimacy. Meanwhile, a novel signcryption algorithm is designed by combining distributed ElGamal encryption and Paillier encryption algorithms, which enhances the computational efficiency of voting results while supporting robustness. The security proof shows that our protocol ensures the confidentiality of ballots, complete anonymity, legitimacy, fairness, dispute-freeness and resistance against multi-voting. In addition, our protocol satisfies robustness, i.e., voting result can be correctly calculated and verified even if some voters abstain from voting. Finally, extensive experiments show that our protocol greatly reduces the computational cost and communication overhead, and is more practical than existing self-tallying voting protocols.
This paper designs an "institution-business-system" multi-level security sandbox system from the perspective of cross-department data sharing and combined with Fabric blockchain technology. The system makes full use of the characteristics of blockchain technology, such as decentralization, immutable and consensus mechanism, to achieve collaborative services of secure sandbox facilities. Then this paper proposes a distributed and regulated privacy protection scheme that combines group signature, private address protocol, zero-knowledge proof and attribute encryption. This algorithm improves the group manager mechanism of group signature. The experimental results show that the scheme can ensure the data traceability and realize the supervision of both sides of the transaction, and improve the level of privacy protection of data on the chain.
Vaishnavi Nagaraja, Muhammad Rezal Kamel Ariffin, Terry Shue Chien Lau, Nurul Nur Hanisah Adenan · 7 authors
The identification protocol is a type of zero-knowledge proof. One party (the prover) needs to prove his identity to another party (the verifier) without revealing the secret key to the verifier. One can apply the Fiat–Shamir transformation to convert an identification scheme into a signature scheme which can be used for achieving security purposes and cryptographic purposes, especially for authentication. In this paper, we recall an identification protocol, namely the RankID scheme, and show that the scheme is incorrect and insecure. Then, we proposed a more natural approach to construct the rank version of the AGS identification protocol and show that our construction overcomes the security flaws in the RankID scheme. Our proposal achieves better results when comparing the public key size, secret key size, and signature size with the existing identification schemes, such as Rank RVDC and Rank CVE schemes. Our proposal also achieves 90%, 50%, and 96% reduction for the signature size, secret key size, and public key size when compared to the Rank CVE signature scheme.
Copyright protection, including copyright registration, copyright transfer and infringement penalty, plays a critical role in preventing illegal usage of original works. The mainstream traditional copyright protection schemes need an authority online all the time to handle copyright issues and face some problems such as intricate copyright transfer, single point of failure and so on. To alleviate the burden of the authority, a few blockchain-based copyright protection schemes are proposed. However, most of them do not consider copyright transfer, and their infringement penalty may only happen after copyright owners discover the infringement behavior (i.e., “ex-post penalty”). In this article, we propose a new security strategy, called “Proactive Defense” in copyright protection which can prevent infringement before it occurs. With our proposed proactive defense strategy, we design a secure copyright protection scheme which provides advantages of compact copyright transfer and prior infringement penalty. More concrete, both copyright registration and transfer are regarded as transactions and recorded to the blockchain. Based on the double-authentication-prevention signature and non-interactive zero-knowledge proof techniques, illegal copyright transfer can be detected and the infringement penalty can be done automatically with a tailored smart contract before the completion of the transfer. Our security analysis shows that the proposed scheme can achieve all desirable security properties. Moreover, we implement our scheme in Java and evaluate the performance experimentally. Experimental results show that the proposed scheme has good security and efficiency, which can be applied for the copyright protection.
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Yao Xiao, Lei Xu, Can Zhang, Liehuang Zhu · 5 authors
The metaverse is an advanced digital world where users can have interactive and immersive experiences. Users enter the metaverse through digital objects created by extended reality and digital twin technologies. The ownership issue regarding these digital objects can be solved by the blockchain-based nonfungible token (NFT), which is of vital importance for the economics of the metaverse. Users can utilize NFTs to engage in various social and economic activities. However, current NFT protocols expose the owner’s information to the public, which may contradict with the privacy requirement. In this article, we propose a protocol, NFTPrivate, that can realize anonymous and confidential trading of digital objects. The key idea is to utilize cryptographic commitments to hide users’ addresses. By constructing proper zero-knowledge proofs, the owner can initiate privacy-preserving yet publicly verifiable transactions. Illustrative results show that the proposed protocol has higher computation and storage overhead than traditional NFT protocols. We think this is an acceptable compromise for privacy protection.
Federated learning (FL) has been widely used in both academia and industry all around the world. FL has advantages from the perspective of data security, data diversity, real-time continual learning, hardware efficiency, etc. However, it brings new privacy challenges, such as membership inference attacks and data poisoning attacks, when parts of participants are not assumed to be fully honest. Moreover, selfish participants can obtain others’ collaborative data but do not contribute their real local data or even provide fake data. This violates the fairness of FL schemes. Therefore, advanced privacy and fairness techniques have been integrated into FL schemes including blockchain, differential privacy, zero-knowledge proof, etc. However, most of the existing works still have room to enhance the practicality due to our exploration. In this paper, we propose a Blockchain-based Pseudorandom Number Generation (BPNG) protocol based on Verifiable Random Functions (VRFs) to guarantee the fairness for FL schemes. Next, we further propose a Gradient Random Noise Addition (GRNA) protocol based on differential privacy and zero-knowledge proofs to protect data privacy for FL schemes. Finally, we implement both two protocols on Hyperledger Fabric and analyze their performance. Simulation experiments show that the average time that proof generation takes is 18.993 s and the average time of on-chain verification is 2.27 s under our experimental environment settings, which means the scheme is practical in reality.
In this paper we consider nonnegatively curved finite dimensional Alexandrov spaces with a non-collapsing condition, i.e., such that unit balls have volumes uniformly bounded from below away from zero. We study the relation between the isoperimetric profile, the existence of isoperimetric sets, and the asymptotic structure at infinity of such spaces. In this setting, we prove that the following conditions are equivalent: the space has linear volume growth; it is Gromov--Hausdorff asymptotic to one cylinder at infinity; it has uniformly bounded isoperimetric profile; the entire space is a tubular neighborhood of either a line or a ray. Moreover, on a space satisfying any of the previous conditions, we prove existence of isoperimetric sets for sufficiently large volumes, and we characterize the geometric rigidity at the level of the isoperimetric profile. Specializing our study to the $2$-dimensional case, we prove that unit balls have always volumes uniformly bounded from below away from zero, and we prove existence of isoperimetric sets for every volume, characterizing also their topology when the space has no boundary. The proofs exploit a variational approach, and in particular apply to Riemannian manifolds with nonnegative sectional curvature and to Euclidean convex bodies. Up to the authors' knowledge, most of the results are new even in these smooth cases.
With the growing popularity of smartphone photography in recent years, web photos play an increasingly important role in all walks of life. Source camera identification of web photos aims to establish a reliable linkage from the captured images to their source cameras, and has a broad range of applications, such as image copyright protection, user authentication, investigated evidence verification, etc. This paper presents an innovative and practical source identification framework that employs neural-network enhanced sensor pattern noise to trace back web photos efficiently while ensuring security. Our proposed framework consists of three main stages: initial device fingerprint registration, fingerprint extraction and cryptographic connection establishment while taking photos, and connection verification between photos and source devices. By incorporating metric learning and frequency consistency into the deep network design, our proposed fingerprint extraction algorithm achieves state-of-the-art performance on modern smartphone photos for reliable source identification. Meanwhile, we also propose several optimization sub-modules to prevent fingerprint leakage and improve accuracy and efficiency. Finally for practical system design, two cryptographic schemes are introduced to reliably identify the correlation between registered fingerprint and verified photo fingerprint, i.e. fuzzy extractor and zero-knowledge proof (ZKP). The codes for fingerprint extraction network and benchmark dataset with modern smartphone cameras photos are all publicly available at https://github.com/PhotoNecf/PhotoNecf 1.
Open access
3 source records
cs.CV
Digital Media Forensic Detection
Advanced Steganography and Watermarking Techniques
Guilherme Albuquerque, Carlo Kleber da Silva Rodrigues
Zcash is a proof-of-work (PoW) cryptocurrency that has gained attention due to its promise of enhanced user privacy. Notwithstanding, Zcash’s thorough acceptance notably depends on how profitable its mining process can be. To tackle this issue, we propose an analytical model to compute the mining hashrate under solo mining to achieve a liquid revenue equal to the minimum wage in the United States. In the sequence, we then estimate how profitable Zcash solo mining is based on that computed mining hasrate. Our proposed model spans crucial parameters of the whole mining process. In the experiments, we compare Zcash with the popular Bitcoin and also present a competitive analysis encompassing the ten top cryptocurrencies by market capitalization. Final results highlight that: (i) Zcash owns a value of hmin which is about eight orders of magnitude smaller than that of Bitcoin in all investigated scenarios, which refer to the ten least and most expensive american states in terms of electricity tariff; and (ii) Zcash is the second best cryptocurrency for solo mining among the aforementioned ten cryptocurrencies, being the only one whose protocol implements the concept of zero-knowledge proofs. Within this context, our key contribution is to provide the scientific literature with valuable insights to formally pave the way to develop practical analytical models for PoW-cryptocurrency systems, which may be chiefly valuable regarding competitive analyses in general.
This paper formally investigates the problem of unauthorized yet required access to electronically protected information, a.k.a. Break-the-Glass (BtG) access. Reflecting on the rising deployment of such protocols in the current digitized healthcare system, we present Mjolnir, a blockchain-based BtG framework that offers accountability of unauthorized accesses by healthcare practitioners, dependable right of notification to patients, and privacy of healthcare records accesses. Mjolnir is a smart contract-based protocol which provides undisputed public verifiability of the identity of BtG access entities while maintaining their anonymity except from concerned individual patients, hence protecting the patients’ privacy. We employ an application specific non-interactive cryptographic zero knowledge proof system which ensures that the signing entity (healthcare practitioner) belongs to a given authorized group and that the anonymity of their identity is only revocable by a given opening entity (patient). The security of our system relies on the hardness of the discrete logarithm and decisional Diffie–Hellman problems in elliptic curve groups, and the utilized proof system requires no trusted setup. We formally define and prove the security goals of Mjolnir, provide a proof of concept blockchain implementation on Ethereum, and report on performance experiments and comparisons with other generic zero knowledge proof systems.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
In this paper, we propose a practically efficient model for securely computing rank-based statistics, e.g., median, percentiles and quartiles, over distributed datasets in the malicious setting without leaking individual data privacy. Based on the binary search technique of Aggarwal et al. (EUROCRYPT \textquotesingle 04), we respectively present an interactive protocol and a non-interactive protocol, involving at most $\log ||R||$ rounds, where $||R||$ is the range size of the dataset elements. Besides, we introduce a series of optimisation techniques to reduce the round complexity. Our computing model is modular and can be instantiated with either homomorphic encryption or secret-sharing schemes. Compared to the state-of-the-art solutions, it provides stronger security and privacy while maintaining high efficiency and accuracy. Unlike differential-privacy-based solutions, it does not suffer a trade-off between accuracy and privacy. On the other hand, it only involves $O(N \log ||R||)$ time complexity, which is far more efficient than those bitwise-comparison-based solutions with $O(N^2\log ||R||)$ time complexity, where $N$ is the dataset size. Finally, we provide a UC-secure instantiation with the threshold Paillier cryptosystem and $Σ$-protocol zero-knowledge proofs of knowledge.
In view of the problem that the transaction privacy in the current blockchain technology service is easy to be leaked, a bulletproof alliance chain technology service transaction privacy protection mechanism is proposed. Firstly, this paper uses digital certificates as access mechanisms and stores them on the chain to ensure that the identity of technical service transactions is trusted. Secondly, the transaction data of the technical service user is hidden in the Pedersen commitment, and the Bulletproof is used to build the scope proof. Enable the verifier to conduct confidential verification of the legitimacy of the transaction without obtaining the sensitive information of the transaction, so as to ensure that the user’s transaction privacy is not disclosed. Finally, the security and privacy of the proposed privacy protection scheme are analyzed, and the comparison with other zero-knowledge proof schemes shows that the scheme has the advantages of strong privacy, scalability, and low storage cost.
We demonstrate how to leverage Apple's Find My protocol, most well known as the underlying protocol of the AirTag, for arbitrary data-muling and location services. This provides a new "infrastructure-free" deployment, where areas with frequent human activity can take advantage of this zero-cost backhaul network. While there are severe limitations (e.g. no acknowledgement channel back to the sending device), Find My-based networking could still be a reliable backhaul with sufficient transmission redundancy and knowledge of deployment context. Towards that end, we develop TagAlong, a protocol for scalable, efficient data transmission on the Find My network. We implement a proof-of-concept and demonstrate throughput up to 12.5 bytes/sec and up to a 97% data reception rate.