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8,603 results · page 141 of 359
Zichao Yang, Chenzhe Yang, Fengdong Wang, Yunfan Bao · 5 authors
No abstract is available for this record.
Li-Ying Wang, Hongyu Gui, Xiao Zhang, Song Shang · 5 authors
No abstract is available for this record.
Zhiqi Zhao, Hao Song, Bin He, Xiaofeng Ma
No abstract is available for this record.
Zhihao Hou, Ruilin Lai, Yale He, Chengchuang Lin · 6 authors
No abstract is available for this record.
Junlang Zhang, Zeyu Yu, Tianrong Chen, Jiawen Fang · 6 authors
No abstract is available for this record.
Qianyi Zhan, Yuanyuan Liu, Zhenping Xie, Yuan Liu
No abstract is available for this record.
Yue Li, Xueying Ren, Chang Yin, Chaocen Tang · 6 authors
No abstract is available for this record.
Nikola Samardzic, Simon Langowski, Srinivas Devadas, Daniel Sánchez
Zero-Knowledge Proofs (ZKPs) are a cryptographic tool that enables one party (a prover) to prove to another (a verifier) that a statement is true, without requiring the prover to disclose any data to the verifier. ZKPs have many use cases, such as letting clients delegate computation to servers with cryptographic correctness guarantees, while enabling the server to use secret data in these computations. ZKP applications span verifiable machine learning (ML) and databases, online auctions, electronic voting, and blockchains. While ZKPs are already widely used in blockchains, the prohibitive costs of proof generation limit them to proving very simple computations. We present a novel accelerator, NoCap, that leverages hardware-algorithm co-design to achieve transformative speedups. NoCap generates proofs 586× faster than a 32-core CPU, and 41× faster than PipeZK, a state-of-the-art ZKP accelerator. We leverage recent algorithmic developments to achieve these speedups: we identify and combine two recent hash-based ZKP algorithms, Orion and Spartan, which have similar performance on CPUs to the ZKPs targeted by prior accelerators, but are much more amenable to hardware acceleration. Though these algorithms result in larger proofs, we show that the end-to-end speedups (including prover time, proof transmission, and verification time) more than justify this size increase. We contribute a novel hardware organization to exploit these acceleration opportunities: NoCap is a programmable vector processor with functional units tailored to the needs of hash-based ZKPs. We also contribute a co-designed implementation of the Spartan+Orion ZKP tailored to accelerators, with optimizations that improve parallelism and reduce memory traffic. As a result, NoCap achieves speedups that enable new use cases for ZKP.
Sarah O'Donovan, Aisling Moran, Maria McDonagh, Lisa Ryan
The food industry is intertwined in every continent and culture, shaping dietary habits and economies worldwide (1) . Sustainability has become an increasingly important and widely discussed topic in the food industry influencing the decisions and actions of food industry companies and stakeholders worldwide. In an effort to become environmentally conscious and protect the earth for future generations, sustainability practices have been developed and integrated into food industry actions and policies which aim to meet present needs without compromising the ability of future generations to meet their own needs (2) . This study was part of a joint Erasmus KA2 European-funded project (2022-1-IE01-KA220-VET-000087508 Digitalisation of Sustainable Health Education) and aimed to explore current food sustainability priorities across the food industry in Europe and how initiatives are developed, implemented and evaluated to achieve food sustainability targets. In-depth semi-structured, audio-recorded interviews were conducted with 21 employees in the Food Industry sector across Ireland, Poland, Lithuania and Cyprus. These participants were selected based on their knowledge and oversight of their company’s sustainability practices. Interviews were transcribed and thematically analysed (3,4) , whereby the data were coded, themes identified and discussed by all authors. Three themes were identified in the data: 1. sustainable practice challenges, 2. factors for consideration, and 3. thinking to the future. Sustainable practices were already implemented in all but one of the 21 participating companies. The main drivers reported behind development of sustainable initiatives included complying to the Science-Based Targets initiative (SBTi) and setting emissions targets such as being net zero by 2050 and minimising waste generation. Participants reported cost, time required for monitoring and evaluation, retaining quality of products, and employee engagement as the main challenges for initiative development and implementation. When developing a sustainability initiative, participants felt that employee and stakeholder understanding and acceptance were important to consider for the success of the initiative. Future goals and initiatives were positively discussed as expanding on current priorities to reduce emissions and implement sustainable procurement and production practices, and gaps in research were identified as the proliferation of environmental labels and exploration of greater inter-collaboration between companies to share sustainability data. A focus on becoming more sustainable was at the centre of innovation development and future proofing for all participating companies, with plans to develop new or further enhance current policies to continue producing quality food in an environmentally sustainable way. Educating employees and stakeholders, including nutrition educators and graduates, on future initiatives and potential impacts is essential for raising awareness, strengthening implementation and ensuring long-term maintenance and success of food sustainability practices within industry. Future research into a policy for sharing of sustainability data, such as raw sustainability metrics between companies could strengthen initiative outcomes and inform nutrition education and research to meet market needs.
Ashok Singh Gaur, Hari Om Sharan, Chetan Dudhagara
No abstract is available for this record.
R. Kousalya, Gulshan Kumar
With the advancement of cutting-edge technologies, the Internet of Medical Things (IoMT) has assisted the healthcare sector by facilitating interaction between healthcare service providers and patients in remote areas. In IoMT, wearable or implantable sensors collect the patient’s record and share the information through a public network. Health-related information about the patient must be protected from a variety of attacks by the adversary since it is sensitive and extremely vulnerable to attacks. The sensor equipment that is implanted in the patient is also resource-constrained and has a low power capacity. The entities involved in the communication must be authenticated with one another in order to protect patients’ health information, anonymity, and reliability. While several authenticated key agreement protocols have been proposed, many suffer from high computational costs and storage cost, making them unsuitable for lightweight applications. This paper proposes a secure three-factor robust Elliptic Curve Cryptography (ECC) based mutually authenticated and key agreement protocol known as RELAKA for the IoMT environment, utilizing the benefits of one-way hash function. In proposed scheme, all entities, including the healthcare service providers and wearable sensors, are authenticated by the medical server. Subsequently, a secret key is established for each communication session and shared between all the entities. Additionally, mechanism for appropriate user revocation and re-registration is integrated to provide additional security in cases where a user’s QR code is tampered with by the attacker. The privacy of the proposed protocol is investigated by the potential use of zero knowledge proof. Furthermore, the efficacy of the authentication is examined by challenge and response mechanism. The informal security analysis demonstrates its resistance to threats such as DoS, impersonation, message modification, password guessing, and so on. The performance evaluation of RELAKA protocol indicates that the execution, communication, and storage costs is reduced by 87.59%, 43% and 60.71% respectively. Moreover, the outcomes of the AVISPA simulation illustrate that the RELAKA successfully evades both active and passive attacks. In addition, real-world testbed environment is developed with Raspberry pi 4 model B and the experimental results verifies the robustness of the proposed protocol. According to theoretical analysis and experimental evaluation, the RELAKA scheme is more secure and efficient than the existing protocols.
Zhiwei Wang, Qiuchi Zhu, Zhenqi Zhang
The WiFi fingerprint-based localization method is considered one of the most popular techniques for indoor localization. In INFOCOM'14, Li et al. proposed a wireless fidelity (WiFi) fingerprint localization system based on Paillier encryption, which is claimed to protect both client$C{{}^{\prime}\mathrm{s}}$location privacy and service provider$S{{}^{\prime}\mathrm{s}}$database privacy. However, Yang et al. presented a practical data privacy attack in INFOCOM'18, which allows a polynomial time attacker to obtain$S{{}^{\prime}\mathrm{s}}$database. We propose a novel WiFi fingerprint localization system based on Castagnos-Laguillaumie (CL) encryption, which has a trustless setup and is efficient due to the excellent properties of CL encryption. To prevent Yang et al.'s attack, the system requires that$S$selects only the locations from its database that can receive the nonzero signals from all the available access points in$C{{}^{\prime}\mathrm{s}}$nonzero fingerprint in order to determine$C{{}^{\prime}\mathrm{s}}$location. Security analysis shows that our scheme is secure under Li et al.'s threat model. Furthermore, to enhance the security level of privacy-preserving WiFi fingerprint localization scheme based on CL encryption, we propose a secure and efficient zero-knowledge proof protocol for the discrete logarithm relations in$C{{}^{\prime}\mathrm{s}}$encrypted localization queries.
Ningyuan Chen, Chiew Foong Kwong, David Chieng, Pushpendu Kar
The advent of Cellular Vehicle-to-Everything (C-V2X) technology has revolutionized intelligent transportation systems (ITS), but poses challenges for secure and efficient data sharing due to its dynamic nature. Traditional centralised systems are inadequate, prompting the need for decentralised solutions like blockchain. However, applying blockchain technologies in C-V2X always faces scalability issues. This paper proposes a scalable C-V2X blockchain network integrating dynamic attribute-based sharding and zero-knowledge proofs (ZKPs). Our system ensures scalability in the C-V2X environment through sharding while utilising ZKPs to enhance cross-shard validation efficiency, reducing its complexity to O(1). Additionally, our approach reduces bandwidth consumption by 90.8% compared to Merkle tree-based solutions.
Mohammed El Baraka, Siham Ezzouak
This paper introduces a novel Distributed Key Generation (DKG) protocol based on the Commutative Supersingular Isogeny Diffie-Hellman (CSIDH) framework for secure multi-party cryptography. Our proposed protocol is designed to address scalability and security concerns, particularly in post-quantum cryptographic systems. The main contributions include the introduction of Piecewise Verifiable Proofs (PVPs) for non-interactive zero-knowledge verification of secret shares, and the provision of rigorous security analysis, including resistance to quantum adversaries via Shor’s and Grover’s algorithms. We analyze the protocol’s efficiency, ensuring low computational overhead even in large-scale systems, and compare it with other distributed cryptographic protocols such as RSA-based and lattice-based schemes. Through mathematical proofs and complexity analysis, we demonstrate that our protocol offers enhanced security, efficiency, and scalability in a post-quantum environment. The results presented in this paper provide a strong foundation for implementing secure multi-party computations in quantum-resistant systems.
François Le Gall, Yupan Liu, Harumichi Nishimura, Qisheng Wang
We introduce two models of space-bounded quantum interactive proof systems, QIPL and QIP_{U}L. The QIP_{U}L model, a space-bounded variant of quantum interactive proofs (QIP) introduced by Watrous (CC 2003) and Kitaev and Watrous (STOC 2000), restricts verifier actions to unitary circuits. In contrast, QIPL allows logarithmically many pinching intermediate measurements per verifier action, making it the weakest model that encompasses the classical model of Condon and Ladner (JCSS 1995). We characterize the computational power of QIPL and QIP_{U}L. When the message number m is polynomially bounded, QIP_{U}L ⊊ QIPL unless P = NP: - QIPL^HC, a subclass of QIPL defined by a high-concentration condition on yes instances, exactly characterizes NP. - QIP_{U}L is contained in P and contains SAC¹ ∪ BQL, where SAC¹ denotes problems solvable by classical logarithmic-depth, semi-unbounded fan-in circuits. However, this distinction vanishes when m is constant. Our results further indicate that (pinching) intermediate measurements uniquely impact space-bounded quantum interactive proofs, unlike in space-bounded quantum computation, where BQL = BQ_{U}L. We also introduce space-bounded unitary quantum statistical zero-knowledge (QSZK_{U}L), a specific form of QIP_{U}L proof systems with statistical zero-knowledge against any verifier. This class is a space-bounded variant of quantum statistical zero-knowledge (QSZK) defined by Watrous (SICOMP 2009). We prove that QSZK_{U}L = BQL, implying that the statistical zero-knowledge property negates the computational advantage typically gained from the interaction.
Marek Kirejczyk, Maciej Kalka, Leonid Logvinov
This paper presents a comprehensive analysis of storage proofs in the Ethereum ecosystem, examining their role in addressing historical and cross-chain state access challenges. We systematically review existing approaches to historical state verification, comparing Merkle Mountain Range (MMR) and Merkle-Patricia trie (MPT) architectures. An analysis involves their respective performance characteristics within zero-knowledge contexts, where performance challenges related to Keccak-256 are explored. The paper also examines the cross-chain verification, particularly focusing on the interactions between Ethereum and Layer 2 networks. Through careful analysis of storage proof patterns across different network configurations, we identify and formalize three architectures for cross-chain verification. By organizing this complex technical landscape, this analysis provides a structured framework for understanding storage proof implementations in the Ethereum ecosystem, offering insights into their practical applications and limitations.
Dr. Emily R. Thompson
Blockchain technology has revolutionized decentralized systems by enabling secure, transparent, and tamper-resistant data management. Central to blockchain functionality is the consensus mechanism, which ensures agreement among distributed nodes. This paper presents a comprehensive review of cryptographic solutions underpinning various blockchain consensus protocols. We analyze the role of cryptographic primitives such as hash functions, digital signatures, zero-knowledge proofs, and threshold cryptography in enhancing security and efficiency of consensus algorithms like Proof of Work (PoW), Proof of Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT). The review highlights strengths, limitations, and emerging trends in cryptographic techniques addressing scalability, privacy, and resistance to adversarial attacks. Finally, we discuss future research directions toward integrating advanced cryptography with blockchain consensus to improve trustworthiness and performance.
Praveena Bolly Joshi, Arivazhagan Natesan
In recent years, the healthcare sector has encountered significant challenges in authenticating identities for online medical services. A predominant reliance on centralized identity management systems (IDMs) has presented obstacles to the seamless exchange of patient identities among various healthcare institutions, often resulting in data isolation within individual silos. Of paramount concern are the potential privacy breaches associated with centralized IDMs, which may compromise patient confidentiality. In response to these challenges, we propose a novel approach to securely sharing patient details across multiple hospitals utilizing the zero-knowledge access protocol (MediCrypt-ZKAP) within the Hyperledger Fabric blockchain framework. By adopting MediCrypt-ZKAP, hospitals can effectively verify the identities of requesting entities without disclosing sensitive patient information, thereby ensuring the highest levels of confidentiality and privacy protection. The proposed system represents a proactive step towards addressing the critical need for secure and interoperable patient data exchange within the healthcare sector. Through the integration of MediCrypt-ZKAP into existing blockchain infrastructure, our solution aims to enhance data security and privacy while promoting seamless collaboration among healthcare institutions.
Obaida Firas Osama, Abeer Salim Jamil, Amal Faisal Jaffar Al-Madhhachi, Rana Khudhair Abbas Ahmed · 7 authors
This article presents a real-time environment aware blockchain framework for the Industrial Internet of Things (IIoT) to optimize contextually blockchain processing and execution. In contrast to current blockchain technologies, which are very static systems, this proposal adapts based on shuttering amounts such as temperature and pressure. The flexibility provided by blockchain promotes data authentication, and its adaptability makes sure that the needs of IIoT environments are met concerning security, integrity, and scalability. The system better accommodates the expanding data loads from IoT sensors and does so more resourcefully by leveraging dynamic block generation, smart contracts, as well as adaptive resource allocation to exploit the available resources serving it at peak performance.The study here also examines how IoT's cybersecurity benefits, in the form of contextual blockchain with cryptographic hashing and zero-knowledge proofs, allow developers to securely embed protection against Distributed Denial of Service (DDoS) attacks alongside data tampering or unauthorized access on an anytime basis. Operational use-cases such as supply chain management, smart cities and edge computing demonstrate the system solution accelerates real-time decision-making, reduces any resource wastage or delays if at all occurring in systemic responses, thereby enhances operational efficiency.In conclusion, contextual blockchain makes scalable and secure as well as flexible solution for IIoT application in which it pertains static nature of other blockchain systems to pragmatic real world situations. This work paves the way for possible future developments such as AI and edge computing integrations, which could make blockchain suitable to run on high-performance environments.
Carmit Hazay, Muthuramakrishnan Venkitasubramaniam, Mor Weiss
Abstract Leakage-resilient cryptography aims to protect cryptographic primitives from so-called “side channel attacks” that exploit their physical implementation to learn their input or secret state. Starting from the works of Ishai, Sahai and Wagner (CRYPTO‘03) and Micali and Reyzin (TCC‘04), most works on leakage-resilient cryptography either focus on protecting general computations, such as circuits or multiparty computation protocols, or on specific non-interactive primitives such as storage, encryption, and signatures. This work focuses on leakage resilience for the middle ground, namely for distributed and interactive cryptographic primitives. Our main technical contribution is designing the first secret sharing scheme that is equivocal , resists adaptive probing of a constant fraction of bits from each share, while incurs only a constant blowup in share size. Equivocation is a strong leakage-resilience guarantee, recently introduced by Hazay et al. (ITC, 2021). Our construction is obtained via a general compiler which we introduce, that transforms any secret sharing scheme into an equivocal scheme against adaptive leakage. An attractive feature of our compiler is that it respects additive reconstruction; namely, if the original scheme has additive reconstruction, then the transformed scheme has linear reconstruction. We extend our compiler to a general paradigm for protecting distributed primitives against leakage and show its applicability to various primitives, including secret sharing, verifiable secret sharing, function secret sharing, distributed encryption and signatures, and distributed zero-knowledge proofs. For each of these primitives, our paradigm transforms any construction of the primitive into a scheme that resists adaptive party corruptions, as well as adaptive probing leakage of a constant fraction of bits in each share when the share is stored in memory (but not when it is used in computations). Moreover, the transformation incurs only a constant blowup in the share size and respects additive reconstruction—an important feature for several of these primitives, such as function secret sharing and distributed encryption.
Lei Zhang, Yixin Jiang, Hongjian Yin, Yakun Niu · 6 authors
Under the rapid development of big data and cloud computing, emerging applications have seen significant improvements in efficiency and service quality. Nevertheless, the conflict between data sharing and privacy preservation remains a major obstacle to the advancement of big data technology. Addressing this issue, this study introduces a solution tailored to the big data environment, which achieves privacy protection and auditability in data sharing and processing. This approach separates data ownership, usage, and validation to mitigate privacy breaches and improper computing behaviors. Leveraging blockchain technology, a transparent governance platform is constructed to identify and track illegal data and computing activities. Furthermore, the solution integrates noninteractive zero-knowledge proofs for publicly verifying data consistency and computing validity on the blockchain. Experimental analysis on computational latency, communication costs, and encryption parameters confirms the feasibility and efficacy of this approach.
Bowei Zhang, Heng Pan, Kunyang Li, Ying Xing · 7 authors
In distributed computing, data trading mechanisms are essential for ensuring the sharing of data across multiple computing nodes. Nevertheless, they currently encounter considerable obstacles, including low accuracy in matching trading parties, ensuring fairness in transactions, and safeguarding data privacy throughout the trading process. In order to address these issues, we put forward a data trading security scheme based on zero-knowledge proofs and smart contracts. In the phase of preparing the security parameters, the objective is to reduce the complexity of generating non-interactive zero-knowledge proofs and to enhance the efficiency of data trading. In the pre-trading phase, we devise attribute atomic matching smart contracts based on precise data property alignment, with the objective of achieving fine-grained matching of data attributes between trading parties. In the trading execution phase, lightweight cryptographic algorithms based on elliptic curve cryptography (ECC) and non-interactive zero-knowledge proofs are employed for the dual encryption of trading data and the generation of attribute proof contracts, thus ensuring the security and privacy of the data. The results of experiments conducted on the Ethereum platform in an industrial IoT scenario demonstrate that our scheme maintains stable and low-cost consumption while ensuring accuracy in matching and privacy protection.
Philip Huff, Spencer Massengale, Tran Viet Xuan Phuong, Sri Nikhil Gupta Gourisetti
Cyber Threat Intelligence (CTI) is a key resource for developing defensive strategies against potential cyber adversaries. Entities typically access CTI through open-source platforms, national agencies, or specialized commercial services. However, the bi-directional exchange of CTI is hindered by organizational trust boundaries, which complicate the sharing processes between entities and CTI providers. Centralized CTI services benefit from receiving suspicious cyber observables such as IP addresses, domain names, and email addresses from various entities. The aggregation allows for the correlation of widespread adversarial activities to enhance the alert and response mechanisms across the network of involved parties. Despite these benefits, openly sharing such observables incurs potential legal, regulatory, and reputational risks for the disclosing entities.This paper introduces a system designed to facilitate the secure exchange of cyber observables across trust boundaries without compromising the anonymity of the sharing entities. We propose an architecture that leverages common web protocols alongside zero-knowledge proofs to authenticate members while maintaining anonymity. Additionally, we outline a privacy model tailored for STIX (Structured Threat Information eXpression) cyber observables to minimize the risk of inadvertently disclosing private information. Through our threat models, we assess the privacy implications of our proposed system and demonstrate its potential to enhance collaborative cyber defense efforts without exposing entities to undue risk.
Vinh Quach, Ram Dantu, Sirisha Talapuru, Shakila Zaman · 5 authors
As concerns over privacy and trust escalate among individuals and corporations, traditional memory-based trust systems are increasingly seen as inadequate and undesirable. The rise of microservice architecture complicates this by making data paths harder to track. Given these concerns, the critical question arises: How can we establish trust or verify an entity’s credibility without collecting private information or relying on comparisons with pre-existing data, while knowing the exact data path of each request? To address this challenge, we introduce a lightweight, scalable, ZCube platform that employs nested Zero Knowledge Proofs (ZKPs), eliminating reliance on memory or evaluations based on past actions. This platform verifies and maintains trust in real-time without centralizing trust in any specific part of the system. It anticipates intentions and rigorously monitors them, ensuring operational integrity while preserving privacy. Distinctive for its ZKP trustless setup incorporating blockchain, each request begins anew and is rigorously monitored bidirectionally during execution. Our tests on the realistic example of a microservice-based distributed system, OpenTelemetry Demo, confirm that our novel approach— combining proof segmentation with plan adherence— exhibits fast response times of less than 200ms on average for most test cases. This ZCube platform surpasses traditional methods in efficiency and security. Our analysis shows comprehensive security and enhanced performance while effectively maintaining bidirectional trustlessness.