We present a signature scheme based on the Syndrome-Decoding problem in rank metric. It is a construction from multi-party computation (MPC), using a MPC protocol which is a slight improvement of the linearized-polynomial protocol used in [Fen22], allowing to obtain a zero-knowledge proof thanks to the MPCitH paradigm. We design two different zero-knowledge proofs exploiting this paradigm: the first, which reaches the lower communication costs, relies on additive secret sharings and uses the hypercube technique [AMGH+22]; and the second relies on low-threshold linear secret sharings as proposed in [FR22]. These proofs of knowledge are transformed into signature schemes thanks to the Fiat-Shamir heuristic [FS86].
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 with rising dependence on communication infrastructure. A common assumption made for most existing distributed/decentralized controllers is that local controllers would faithfully follow the designated controller dynamics based on the data received from communication channels. However, with increased probability of cyberattacks on Operational Technology infrastructure, such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. In this work, we leverage a cryptography technology known as zero-knowledge scalable transparent arguments of knowledge (zk-STARK) to verify the computational integrity of power grid control algorithms, with projected linear dynamics-based control schemes as the initial proof-of-concept test case. The method presented here converts the cybersecurity challenge of data integrity for grid control into a subset of computational integrity.
Jesús García-Rodríguez, Stephan Krenn, Jorge Bernal Bernabé, Antonio Skármeta
PREPRINT: The increasing user awareness and regulatory framework (e.g., GDPR) have contributed to considering data minimization and privacy-by-design as central guiding principles for new systems.<br> Among others, this has led to a paradigm shift towards Self-Sovereign Identity solutions to put the user in full control over their data.<br> Despite the promising landscape, privacy-preserving Attribute-Based Credentials (p-ABC) have not been widely adopted, mainly due to the lack of secure, flexible and efficient implementations that cover the basic and advanced needs in p-ABC systems. In this work, we tackle this gap by formalizing an improved zero-knowledge showing protocol of a distributed p-ABC scheme based on Pointcheval-Sanders Multi-Signatures to allow for modular extensions through commit-and-prove techniques. We use it to implement a flexible p-ABC system with decentralized issuance that, apart from the basic notions of p-ABCs, covers range proofs, pseudonyms, inspection and revocation. Lastly, we thoroughly evaluate the performance of the system under different testbed conditions, showing a significant efficiency improvement over previous implementations.
\n\t\n\t\t\n\t\t\t\n\t\t\tWith the rapid development of technology and the large amount of digitization in various fields of human life, it is necessary to pay attention to the security and certainty of privacy so that there is no leakage of confidential data, both in the private and governmental domains, especially in Indonesia. In this case cyber-attacks will grow and become more numerous; therefore we need a security principle that can prevent these cyber-attacks, especially in sending something that is sensitive which can be called cryptography. One of the applications that can be implemented regarding this cryptography is the Whatsapp application. WhatsApp claims that the application is safe from data theft and messages being intercepted. However, this is doubtful with the presence of Whatsapp Mod which offers more features than the official application. The security of the modified Whatsapp is questionable, so in this study a test was carried out using the MobSF Framework to find out whether there were security holes that could endanger its users. The results of this research are in the form of a report issued by MobSF regarding the level of danger of the Whatsapp Mod Application. With this research, it is hoped that it will be able to make Whatsapp Mod users aware of the dangers of modified applications and Whatsapp can provide advice and strict action against the Whatsapp Mod developers.\n\t\t\t\n\t\t\n\t\n
Rabimba Karanjai, Sangwon Shin, Xiong, and Wujie, Xinxin Fan · 11 authors
Cryptographic schemes like Fully Homomorphic Encryption (FHE) and Zero-Knowledge Proofs (ZKPs), while offering powerful privacy-preserving capabilities, are often hindered by their computational complexity. Polynomial multiplication, a core operation in these schemes, is a major performance bottleneck. While algorithmic advancements and specialized hardware like GPUs and FPGAs have shown promise in accelerating these computations, the recent surge in AI accelerators (TPUs/NPUs) presents a new opportunity. This paper explores the potential of leveraging TPUs/NPUs to accelerate polynomial multiplication, thereby enhancing the performance of FHE and ZKP schemes. We present techniques to adapt polynomial multiplication to these AI-centric architectures and provide a preliminary evaluation of their effectiveness. We also discuss current limitations and outline future directions for further performance improvements, paving the way for wider adoption of advanced cryptographic tools.
Xin Zhou, Bin Wang, Haotian Zhao, Hongbin Sun · 6 authors
The coordination of multienergy systems has been commonly adopted to improve energy utilization performance. Reallocating profits of all systems is utilized to provide incentives for the coordination. However, some systems might forge their profits to maliciously obtain more reallocated profits. Existing works partially solve this problem by developing privacy-preserving anti-forgery methods that focus on the coordination of two energy systems with linear constraints. This article proposes a coordinated heat-electricity-gas dispatch mechanism that addresses incentive, privacy and anti-forgery issues. The coordination model based on Nash bargaining is decomposed into both a dispatch problem that maximizes the total profit and a profit reallocation problem that provides incentives. The profit reallocation problem is solved using exponential ElGamal encryption to avoid leaking the profit variation of each system before and after coordination. Furthermore, to prevent any system from forging its profit for maliciously obtaining more reallocated profit, we propose a privacy-preserving anti-forgery method based on zero knowledge proof. The method enables each system to prove that its profit variation satisfies the Karush-Kuhn-Tucker conditions of the dispatch problem with nonlinear constraints. The numerical tests show that our proposed method provides incentives for coordination and detects forgery of profit variation without leaking privacy.
With the advancement of distributed generation and information technology, energy trading in micro grid (MG) becomes popular in recent years. However, due to the lack of authority management in the MG, the traditional energy trading method with trusted system operator (SO) and market operator (MO) is no longer suitable. This paper proposes a novel, secure and privacy-preserving energy trading architecture with the state-of-the-art cryptosystem. Firstly, a zero-knowledge-proof based non-interactive protocol is proposed to authenticate prosumers. Next, a novel energy data evaluation method is proposed to achieve privacy-preserving power pricing and dispatching with the homomorphic encryption. Moreover, a lightweight tree-chained trading book is proposed to protect the transaction information. Then, we analysis the security performance and emphasize the advantages of our proposed architecture. At last, we exam the performance of our proposed methods in the IEEE benchmark systems. We observe that, our proposed architecture could achieve the privacy-preserving and secure energy trading in a low-time-cost but high-accuracy way.
Zero-knowledge proof (ZKP) frameworks have the potential to revolutionize the handling of sensitive data in various domains. However, deploying ZKP frameworks with real-world data presents several challenges, including scalability, usability, and interoperability. In this project, we present Fact Fortress, an end-to-end framework for designing and deploying zero-knowledge proofs of general statements. Our solution leverages proofs of data provenance and auditable data access policies to ensure the trustworthiness of how sensitive data is handled and provide assurance of the computations that have been performed on it. ZKP is mostly associated with blockchain technology, where it enhances transaction privacy and scalability through rollups, addressing the data inherent to the blockchain. Our approach focuses on safeguarding the privacy of data external to the blockchain, with the blockchain serving as publicly auditable infrastructure to verify the validity of ZK proofs and track how data access has been granted without revealing the data itself. Additionally, our framework provides high-level abstractions that enable developers to express complex computations without worrying about the underlying arithmetic circuits and facilitates the deployment of on-chain verifiers. Although our approach demonstrated fair scalability for large datasets, there is still room for improvement, and further work is needed to enhance its scalability. By enabling on-chain verification of computation and data provenance without revealing any information about the data itself, our solution ensures the integrity of the computations on the data while preserving its privacy.
We give a short tutorial survey of authentication protocols for two parties. We also describe a new authentication protocol based on the splitting of a secret given by a trusted third party. We describe a fast three-round mutual authentication protocol for parties A and B belonging to the same coalition group. A coalition group is a group of mutually trusted entities that act independently in an unreliable, possibly malicious, environment and communicate through unsecured open channels. Parties A and B keep their own independent long-term private keys that are used in the process of authentication and can be used for other purposes. The scheme assumes an initial setup with a trusted third party. This party initiates another secret information that includes factors of a large RSA modulus. For authentication, both parties must demonstrate each other the knowledge of their private keys without revealing them and the ability to factorize a large RSA modulus. Thus, the protocol based on the suggested scheme provides reciprocal authentication. The scheme possesses all desirable properties of an interactive proof, i.e., completeness, soundness, and honest-verifier zero-knowledge. The security of the protocol relies on assumptions of difficulty of the RSA factorization and existence of a cryptographic hash function.
Secure data deletion enables data owners to have full control over the erasure of their data stored on local or cloud data centers, and it is essential for preventing data leakage, especially in cloud storage. However, traditional data deletion methods based on unlinking, overwriting, and cryptographic key management are either ineffective in cloud storage or rely on impractical assumptions. In this paper, we introduce SevDel, a secure and verifiable data deletion scheme that utilizes zero-knowledge proofs to achieve verification of the encryption of outsourced data without retrieving the ciphertexts. Meanwhile, the deletion of encryption keys is guaranteed based on Intel SGX. SevDel implements secure interfaces for performing data encryption and decryption in secure cloud storage. It also utilizes smart contracts to enforce the operations of the cloud service provider, ensuring compliance with service level agreements with data owners and imposing penalties on the service provider for disclosing cloud data on its servers. Evaluation using real-world workloads demonstrates that SevDel efficiently achieves data deletion verification and maintains high bandwidth savings.
This paper provides a comprehensive review of the significant literature in the area of user data security with a specific focus on how this integrates with the area of blockchain technologies and zero-knowledge proofs within the context of educational data storage. The overall objective of this review is to provide an in-sight into what has already been made available, with regards to implementation, and how these form an overall direction for the field. The purpose of which is to assist in the efforts to provide a solution that unifies the existing solutions and frameworks and provides real world benefits by targeting the highlighted research gaps.
Mobile sign language apps have drawn a lot of interest recently as a way to minimize communication barriers between hearing people and people with hearing impairments. However, there are issues with the criteria and standards that should be taken into account when developing these apps. This study proposes a set of development criteria for sign language mobile apps and standardizes these criteria using the Fuzzy Delphi approach. Furthermore, the Fuzzy-Weighted Zero Inconsistency (FWZIC) approach is utilized to assign weights to the criteria and establish a ranking order. An initial set of requirements is developed based on the literature review. The Fuzzy Delphi technique is used, involving a panel of experts made up of developers, sign language experts, and users of sign language mobile apps, to assess the validity and reliability of the criteria. The FWZIC technique is used to give the criterion weights and determine their ranking order in order to further improve the decision-making process. The relative relevance of each criterion is determined by the FWZIC technique, which involves expert input and makes use of their knowledge and expertise. A thorough ranking is generated by taking into account the effects of each criterion on several zones, assisting in efficient decision-making during the creation of sign language mobile apps. Six Malaysian Sign Language apps that have been shortlisted are being utilized as a proof of concept to test the idea. The result of 6 apps is obtained based on the final standard criteria, their weights, and rankings.
Training contemporary AI models requires investment in procuring learning data and computing resources, making the models intellectual property of the owners. Popular model watermarking solutions rely on key input triggers for detection; the keys have to be kept private to prevent discovery, forging, and removal of the hidden signatures. We present ZKROWNN, the first automated end-to-end framework utilizing Zero-Knowledge Proofs (ZKP) that enable an entity to validate their ownership of a model, while preserving the privacy of the watermarks. ZKROWNN permits a third party client to verify model ownership in less than a second, requiring as little as a few KBs of communication.
Internet of Things (IoT) applications, such as e-healthcare departments have grown tremendously where devices gather patient data and instantly transmit it over a distance to servers. Despite its huge advantages, IoT in the healthcare sector has acquired little consideration, largely because of the threats of unauthorized access to private health data made possible by the weak wireless communication channel. The economic complexity of the current security protocols makes them inappropriate, hence new security protocols must be developed for resource-constrained and diverse IoT networks. This work suggests an authenticated key agreement protocol for the Internet of medical things (IoMT) that is based on zero-knowledge proofs (ZKP). The research will include the comparison between computational delays in traditional protocols and ZKP protocol. This paper provides a protocol to obtain privacy of data in IoMT environment on the basis of zero knowledge phenomenon and anonymous communication by ZKP.
Laasya Bangalore, Mohammad Hossein Faghihi Sereshgi, Carmit Hazay, Muthuramakrishnan Venkitasubramaniam
In this work, we introduce a lightweight secure aggregation protocol that guarantees liveness (i.e., guaranteed output delivery), robust against faulty inputs and security against malicious clients. First, we improve upon prior works in the “star”-like topology network with a central coordinating (also output) party, Bonawitz et al. (ACM CCS 2017) and Bell et al. (ACM CCS 2020), which are not robust against faulty inputs. Recent works, RoFL (Burkhalter et al.) and (concurrent work) ACORN (Bell et al.) show how to rely on zero-knowledge proofs to address such attacks at expense of significantly high computation costs. We also compare our protocol against the PRIO system by Gibbs and Boneh (USENIX 2017) which achieves the same task in an incomparable security model. We benchmark our protocol with implementation and demonstrate its concrete efficiency. Our solution scales to 1000s of clients, requires only a constant number of rounds, outperforms prior work in computational cost, and has competitive communication cost.
This paper proposes a novel voting system that incorporates an intersectional Privilege Index to address social inequalities and power imbalances that often lead to marginalized groups being underrepresented in the political sphere. The Privilege Index is a composite measure that takes into account various factors, such as race, gender, socioeconomic status, and education, which contribute to an individual's social privilege. By incorporating this index into the voting process, the proposed blockchain-based system aims to counteract the effects of systemic inequalities and ensure that underrepresented groups have a more significant impact on the outcome of elections and other democratic processes. This paper provides a comprehensive analysis of the proposed Privilege Index-based voting system, outlining its design, potential benefits, and associated ethical, legal, and practical challenges. The system incorporates zero-knowledge proofs to protect the privacy of citizens' personal information and assigns a vote token based on the Privilege Index score. During the voting process, citizens burn their vote tokens to cast their ballots, and the final results are determined by the sum of the token values for each candidate or option. Despite the potential benefits of the Privilege Index-based voting system, it also raises several ethical, legal, and practical challenges that must be carefully considered, such as accuracy of the Privilege Index, privacy concerns, potential for manipulation, legal and ethical considerations, and practical challenges. This paper examines these challenges and presents strategies for mitigating them to ensure a fair and inclusive democratic process.
Ning Lin, Shaocong Wang, Yi Li, Bo Wang · 22 authors
The human brain is a complex spiking neural network (SNN), capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains minimal power consumption through event-based signal propagation. However, replicating the human brain in neuromorphic hardware presents both hardware and software challenges. Hardware limitations, such as the slowdown of Moore's law and Von Neumann bottleneck, hinder the efficiency of digital computers. Additionally, SNNs are characterized by their software training complexities. To this end, we propose a hardware-software co-design on a 40 nm 256 Kb in-memory computing macro that physically integrates a fixed and random liquid state machine (LSM) SNN encoder with trainable artificial neural network (ANN) projections. We showcase the zero-shot LSM-based learning of multimodal events on the N-MNIST and N-TIDIGITS datasets, including visual and audio data association, as well as neural and visual data alignment for brain-machine interfaces. Our co-design achieves classification accuracy comparable to fully optimized software models, resulting in a 152.83 and 393.07-fold reduction in training costs compared to SOTA contrastive language-image pre-training (CLIP) and Prototypical networks, and a 23.34 and 160-fold improvement in energy efficiency compared to cutting-edge digital hardware, respectively. These proof-of-principle prototypes demonstrate zero-shot multimodal events learning capability for emerging efficient and compact neuromorphic hardware.
The exponential growth in connected devices with Internet-of-Things (IoT) and next-generation wireless networks requires more advanced and dynamic spectrum access mechanisms. Blockchain-based approaches to Dynamic Spectrum Access (DSA) seem efficient and robust due to their inherited characteristics such as decentralization, immutability, and transparency. However, conventional consensus mechanisms used in blockchain networks are expensive to be used due to the cost, processing, and energy constraints. Moreover, addressing spectrum violations (i.e., unauthorized access to the spectrum) is not well-discussed in most blockchain-based DSA systems in the literature. In this work, we propose a newly tailored energy-efficient consensus mechanism called “Distributed-Proof-of-Sense (DPoS)” that is specially designed to enable DSA and detect spectrum violations. The proposed consensus algorithm motivates blockchain miners to perform spectrum sensing, which leads to the collection of a full spectrum of sensing data. An elliptic curve cryptography-based zero-knowledge proof is used as the core of the proposed mechanism. We use MATLAB simulations to analyze the performance of the consensus mechanism and implement several consensus algorithms in a microprocessor to highlight the benefits of adopting the proposed system.
We propose a middleware solution designed to facilitate seamless integration of privacy using zero-knowledge proofs within various multi-chain protocols, encompassing domains such as DeFi, gaming, social networks, DAOs, e-commerce, and the metaverse. Our design achieves two divergent goals. zkFi aims to preserve consumer privacy while achieving regulation compliance through zero-knowledge proofs. These ends are simultaneously achievable. zkFi protocol is designed to function as a plug-and-play solution, offering developers the flexibility to handle transactional assets while abstracting away the complexities associated with zero-knowledge proofs. Notably, specific expertise in zero-knowledge proofs (ZKP) is optional, attributed to zkFi's modular approach and software development kit (SDK) availability.
The objective of this memory is to give a purely algebraic proof of the Sauer- Shelah-Perles Lemma (inspired by the elegant proof in [FrPa,1983]), based only in duality in the Q−algebra Q[Vn] of polynomial functions de_ned on the zero-dimensional algebraic variety of subsets of the set [n] := {1, 2, . . . , n}. In fact, two di_erent proofs of this lemma will be given. Furthermore, we prove how several other classical results from Combinatorics are particular examples of a Trace (Inversion) Formula in _nite Q−algebras. For instance, one of this results is the general form of the Inclusion-Exclusion Principle (both with direct and reverse order associated to subsets inclusion). This approach also allows us to show a basis of the space of null t−designs, which di_ers from the one described in Theorem 4 of [DeFr,1982]. All results are still true if we replace Q[Vn] by K[Vn], where K is a perfect _eld of characteristic di_erent from 2. This memory has then the underlying purpose of connecting two _elds of mathematical knowledge that are not usually connected, at least not in this form.
Andreas Erwig, Sebastian Faust, Siavash Riahi, Tobias Stöcker
Permissionless blockchain systems such as Bitcoin or Ethereum are slow and expensive, since transactions are processed in a distributed network by a large set of parties. To improve on these shortcomings, a prominent approach is given by so-called 2nd-layer protocols. In these protocols parties process transactions off-chain directly between each other, thereby drastically reducing the costly and slow interaction with the blockchain. In particular, in the optimistic case, when parties behave honestly, no interaction with the blockchain is needed. One of the most popular off-chain solutions are Plasma protocols (often also called commit-chains). These protocols are orchestrated by a so-called operator that maintains the system and processes transactions between parties. Importantly, the operator is trustless, i.e., even if it is malicious users of the system are guaranteed to not lose funds. To achieve this guarantee, Plasma protocols are highly complex and rely on involved and expensive dispute resolution processes. This has significantly slowed down development and deployment of these systems.In this work we propose CommiTEE – a simple and efficient Plasma system leveraging the power of trusted execution environments (TEE). Besides its simplicity, our protocol requires minimal interaction with the blockchain, thereby drastically reducing costs and improving efficiency. An additional benefit of our solution is that it allows for switching between operators, in case the main operator goes offline due to system failure, or behaving maliciously. We implemented and evaluated our system over Ethereum and show that it is at least 2 times (and in some cases more than 16 times) cheaper in terms of communication complexity when compared to existing Plasma implementations. Moreover, for protocols using zero-knowledge proofs (like NOCUST-ZKP), CommiTEE decreases the on-chain gas cost by a factor ≈ 19 compared to prior solution.
Jul 1, 2023·2023 IEEE 10th International Conference on Cyber Security and Cloud Computing (CSCloud)/2023 IEEE 9th International Conference on Edge Computing and Scalable Cloud (EdgeCom)
Yang Yang, Kai Jin, Wei Liang, Yaqin Liu · 6 authors
Blockchain technology offers unique advantages in terms of decentralization, transparency, and de-anonymization. However, it also poses challenges to user anonymity and data privacy protection. Consequently, researchers have employed advanced cryptographic primitives to enhance the privacy and anonymity of blockchain-based privacy payments, as well as to extend privacy payment methods to more general forms of privacy computing. Nevertheless, relying on high-level cryptographic primitives and emerging technologies, these solutions have proven challenging for academic and industrial personnel to understand and apply. Therefore, we introduce the principle mechanisms of zero-knowledge proofs and homomorphic encryption and their typical algorithms, analyze and summarize recent research in blockchain privacy computing across several dimensions, and briefly present their potential applications.
The ability to compute on encrypted data is fast becoming a practical reality. We discuss the progress in four technologies which enable this: Trusted Execution Environments, Fully Homomorphic Encryption, Multi-Party Computation and Zero-Knowledge Proofs.