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3,460 results ¡ page 93 of 145
Xianxian Li, Junhao Yang, Shiqi Gao, Zhenkui Shi ¡ 6 authors
No abstract is available for this record.
Julia Hesse, Dennis Hofheinz, Lisa Kohl, Roman Langrehr
We investigate the quality of security reductions for non-interactive key exchange (NIKE) schemes. Unlike for many other cryptographic building blocks (like public-key encryption, signatures, or zero-knowledge proofs), all known NIKE security reductions to date are non-tight, i.e., lose a factor of at least the number of users in the system. In that sense, NIKE forms a particularly elusive target for tight security reductions. The main technical obstacle in achieving tightly secure NIKE schemes are adaptive corruptions. Hence, in this work, we explore security notions and schemes that lie between selective security and fully adaptive security. Concretely: We exhibit a tradeoff between key size and reduction loss. We show that a tighter reduction can be bought by larger public and secret NIKE keys. Concretely, we present a simple NIKE scheme with a reduction loss of O(N2log (ν) / ν2), and public and secret keys of O(ν) group elements, where N denotes the overall number of users in the system, and ν is a freely adjustable scheme parameter. Our scheme achieves full adaptive security even against multiple âtest queriesâ (i.e., adversarial challenges), but requires keys of size O(N) to achieve (almost) tight security under the matrix Diffie-Hellman assumption. Still, already this simple scheme circumvents existing lower bounds. We show that this tradeoff is inherent. We contrast the security of our simple scheme with a lower bound for all NIKE schemes in which shared keys can be expressed as an âinner product in the exponentâ. This result covers the original Diffie-Hellman NIKE scheme, as well as a large class of its variants, and in particular our simple scheme. Our lower bound gives a tradeoff between the âdimensionâ of any such scheme (which directly corresponds to key sizes in existing schemes), and the reduction quality. For ν= O(N), this shows our simple scheme and reduction optimal (up to a logarithmic factor). We exhibit a tradeoff between security and key size for tight reductions. We show that it is possible to circumvent the inherent tradeoff above by relaxing the desired security notion. Concretely, we consider the natural notion of semi-adaptive security, where the adversary has to commit to a single test query after seeing all public keys. As a feasibility result, we bring forward the first scheme that enjoys compact public keys and tight semi-adaptive security under the conjunction of the matrix Diffie-Hellman and learning with errors assumptions. We believe that our results shed a new light on the role of adaptivity in NIKE security, and also illustrate the special role of NIKE when it comes to tight security reductions.
Shaun Azzopardi, Joshua Ellul, Gordon J. Pace
No abstract is available for this record.
Gang Wang
No abstract is available for this record.
Francisco Ribeiro de Sousa
Blockchain, a distributed ledger technology (DLT) that sustained the creation of the first digital currency, Bitcoin, crosses many business areas, including healthcare, to promise better economic solutions. Blockchain generalized implementation is already a reality in Estonia, perhaps the most digitally advanced country globally, with proven healthcare results for its citizens. From a pharmaceutical industry perspective, blockchain offers solutions as diverse as the structuring of clinical trial protocols, the traceability of medicines along the supply chain, and intellectual property rights. Additionally, the DLT's cryptographic protocol, whose main characteristics are immutability, consensus, security, and transparency, may support both the web's decentralization and the transition to a Semantic Web, which is recognized by many as highly recommended.
Gi-Wan Hong, Jeong-Wook Kim, Hangbae Chang
Hyper-connectivity in Industry 4.0 has resulted in not only a rapid increase in the amount of information, but also the expansion of areas and assets to be protected. In terms of information security, it has led to an enormous economic cost due to the various and numerous security solutions used in protecting the increased assets. Also, it has caused difficulties in managing those issues due to reasons such as mutual interference, countless security events and logsâ data, etc. Within this security environment, an organization should identify and classify assets based on the value of data and their security perspective, and then apply appropriate protection measures according to the assetsâ security classification for effective security management. But there are still difficulties stemming from the need to manage numerous security solutions in order to protect the classified assets. In this paper, we propose an information classification management service based on blockchain, which presents and uses a model of the value of data and the security perspective. It records transactions of classifying assets and managing assets by each class in a distributed ledger of blockchain. The proposed service reduces assets to be protected and security solutions to be applied, and provides security measures at the platform level rather than individual security solutions, by using blockchain. In the rapidly changing security environment of Industry 4.0, this proposed service enables economic security, provides a new integrated security platform, and demonstrates service value.
Bingsheng Zhang, Yuan Chen, Jiaqi Li, Yajin Zhou ¡ 7 authors
No abstract is available for this record.
Simon Mangel, Lars Gleim, Jan Pennekamp, Klaus Wehrle ¡ 5 authors
No abstract is available for this record.
Charla GriffyâBrown, Mark Chun, Howard Miller, Demetrios Lazarikos
No abstract is available for this record.
Janko HriberĹĄek
Transformation of BPMN business process model will be a very important topic in the future of the Hyperledger Fabric blockchain environment. Machine transformation can increase the quality of transformation and thus reduce errors. The research paper first describes BPMN and the Hyperledger Fabric environment, what smart contracts are and why they are so important. In the second part, the raw transformation model is described, where the inputs for the transformations are BPMN and the metadata file, and the result is a smart contract written in Java that can be imported into the Hyperledger Fabric environment.
Ruba Awadallah, Azman Samsudin
Cloud computing has now become a very standardised concept in our society. However, many modern applications need a better level of security that includes saving data from internal breaches. Thus, cloud databases need effective security mechanisms to keep track of data modifications. This paper will introduce the enhanced structure of cloud relational database (RDB) based on blockchain technology (BC) named BC over cloud-RDB. To provide the client with an effective self-verification process to detect and prevent erroneous manipulation of RDBs. We proposed two systems to improve cloud-RDB: agile BC-based RDB and secure BC-based RDB. Both are distributed among several cloud service providers based on the Byzantine Fault Tolerance consensus. Additionally, both rely on linking records to each other using the SHA-256. At the same time, secure BC-based RDB uses a proof-of-work consensus to make data offensive operation impossible. Based on both systemsâ performance and security analysis, the agile BC-based RDB is highly suggested for the high throughput database. On the other hand, the secure BC-based RDB is recommended for RDB that contains sensitive data and low throughput performance. The improved RDB is flexible and can be operated based on the data ownerâs specifications.
Taimur Bakhshi, Bogdan Ghita
No abstract is available for this record.
Oyinomomo-emi Emmanuel Akpe, Denis Kisina, Samuel Owoade, Abel Chukwuemeke Uzoka ¡ 6 authors
The increasing complexity of digital platforms, driven by cloud-native architectures, distributed applications, and user-centric services, necessitates robust, scalable, and secure identity management frameworks. This paper explores recent advances in federated authentication and identity management, emphasizing their role in enabling seamless and secure access across interconnected digital ecosystems. Beginning with a foundational overview of identity managementâs evolutionâfrom traditional siloed systems to federated and decentralized modelsâthe study outlines key technologies such as SAML, OAuth, OpenID Connect, and emerging paradigms like decentralized identity and blockchain-based verification. It further investigates the integration of artificial intelligence and machine learning for adaptive authentication, anomaly detection, and risk-based decision-making, alongside privacy-enhancing technologies ensuring compliance with data protection regulations such as GDPR. Through the examination of scalability, interoperability, and security challenges, the paper identifies best practices and architectural strategies critical for real-world implementations. The discussion culminates in practical implications for industry adoption across sectors such as healthcare, finance, and e-commerce, and highlights future research directions including the development of standardized identity frameworks, AI integration, and decentralized identity systems in multi-cloud and edge computing environments. This study offers a comprehensive synthesis of current trends and technologies that are shaping the next generation of identity management in scalable digital platforms.
Weiqi Dai, Yan Lv, KimâKwang Raymond Choo, Zhongze Liu ¡ 6 authors
As cryptocurrency and blockchain-related assets become more common in our digital society, there is a corresponding need to secure our digital assets, including the private keys used to secure access to such assets (e.g., due to loss or corruption of the data storage medium). However, there are limitations in existing blockchain-related asset management and recovery methods. Therefore, we use zero-knowledge proof to design a cryptocurrency recovery scheme based on hidden assisting relationships (hereafter referred to as the CRSA scheme) to facilitate the recovery of blockchain assets. Specifically, when the user's private key is lost, and access to the assets cannot be obtained, the user leverages information such as the pre-defined list of assistants to authenticate himself/herself on the blockchain. Once the assistants have confirmed the legitimacy of the user's authentication request, the asset will be transferred from the old address to the new address. During the (identity) proof process, the zero-knowledge proof is used to ensure that the identification of assistants is not leaked to other nodes, assistants, and the adversary. We provide the formal definition of the above scheme and the security proof of the construction. We also implement a prototype of the system and evaluate its performance. Evaluations indicate that the time required for the zero-knowledge proof is less than 10s, and the block verification time is less than 100ms.
Sara Rouhani, Ralph Deters
Trust is the main barrier preventing widespread data sharing. The lack of transparent infrastructures for implementing data trust prevents many data owners from sharing their data and concerns data users regarding the quality of the shared data. Data trust is a paradigm that facilitates data sharing by forcing data users to be transparent about the process of sharing and reusing data. Blockchain technology proposes a distributed and transparent administration by employing multiple parties to maintain consensus on an immutable ledger. This paper presents an end-to-end framework for data trust to enhance trustworthy data sharing utilizing blockchain technology. The framework promotes data quality by assessing input data sets, effectively manages access control, and presents data provenance and activity monitoring. We introduce an assessment model that includes reputation, endorsement, and confidence factors to evaluate data quality. We also suggest an adaptive solution to determine the number of transaction validators based on the computed trust value. The proposed data trust framework addresses both data owners' and data users' concerns by ensuring the trustworthiness and quality of the data at origin and ethical and secure usage of the data at the end. A comprehensive experimental study indicates the presented system effectively handles a large number of transactions with low latency.
Chloe C. Tartan, Craig Wright, Michaella Pettit, Wei Zhang
No abstract is available for this record.
Yihan Liu, Ke Li, Zihao Huang, Bowen Li ¡ 6 authors
The predominant centralized paradigm in educational data management currently suffers from several critical issues such as vulnerability to malicious tampering, a high prevalence of diploma counterfeiting, and the onerous cost of certificate authentication. Decentralized blockchain technology, with its cutting-edge capabilities, presents a viable solution to these pervasive problems. In this paper, we illuminate the inherent limitations of existing centralized systems and introduce EduChain, a novel heterogeneous blockchain-based system for managing educational data. EduChain uniquely harnesses the strengths of both private and consortium blockchains, offering an unprecedented level of security and efficiency. In addition, we propose a robust mechanism for performing database consistency checks and error tracing. This is achieved through the implementation of a secondary consensus, employing the pt-table-checksum tool. This approach effectively addresses the prevalent issue of database mismatches. Our system demonstrates superior performance in key areas such as information verification, error traceback, and data security, thereby significantly improving the integrity and trustworthiness of educational data management. Through EduChain, we offer a powerful solution for future advancements in secure and efficient educational data management.
Benjamin KÜrbel, Marten Sigwart, Philip Frauenthaler, Michael Sober ¡ 5 authors
Offloading of computation, e.g., to the cloud, is today a major task in distributed systems. Usually, consumers which apply offloading have to trust that a particular functionality offered by a service provider is delivering correct results. While redundancy (i.e., offloading a task to more than one service provider) or (partial) reprocessing help to identify correct results, they also lead to significantly higher cost. Hence, within this paper, we present an approach to verify the results of offchain computations via the blockchain. For this, we apply zero-knowledge proofs to provide evidence that results are correct. Using our approach, it is possible to establish trust between a service consumer and arbitrary service providers. We evaluate our approach using a very well-known example task, i.e., the Traveling Salesman Problem.
Lorenzo Andolfo, Luigi Coppolino, Salvatore DâAntonio, Giovanni Mazzeo ¡ 8 authors
The majority of financial organizations managing confidential data are aware of security threats and leverage widely accepted solutions (e.g., storage encryption, transport-level encryption, intrusion detection systems) to prevent or detect attacks. Yet these hardening measures do little to face even worse threats posed on data-in-use. Solutions such as Homomorphic Encryption (HE) and hardware-assisted Trusted Execution Environment (TEE) are nowadays among the preferred approaches for mitigating this type of threat. However, given the high-performance overhead of HE, financial institutions -- whose processing rate requirements are stringent -- are more oriented towards TEE-based solutions. The X-Margin Inc. company, for example, offers secure financial computations by combining the Intel SGX TEE technology and HE-based Zero-Knowledge Proofs, which shield customers' data-in-use even against malicious insiders, i.e., users having privileged access to the system. Despite such a solution offers strong security guarantees, it is constrained by having to trust Intel and by the SGX hardware extension availability. In this paper, we evaluate a new frontier for X-Margin, i.e., performing privacy-preserving credit risk scoring via an emerging cryptographic scheme: Functional Encryption (FE), which allows a user to only learn a function of the encrypted data. We describe how the X-Margin application can benefit from this innovative approach and -- most importantly -- evaluate its performance impact.
Jonathan Heiss, Anselm Busse, Stefan Tai
Prior to provisioning sensor data to smart contracts, a pre-processing of the data on intermediate off-chain nodes is often necessary. When doing so, originally constructed cryptographic signatures cannot be verified on-chain anymore. This exposes an opportunity for undetected manipulation and presents a problem for applications in the Internet of Things where trustworthy sensor data is required on-chain. In this paper, we propose trustworthy pre-processing as enabler for end-to-end sensor data integrity in data on-chaining workflows. We define requirements for trustworthy pre-processing, present a model and common workflow for data on-chaining, select off-chain computation utilizing Zero-knowledge Proofs (ZKPs) and Trusted Execution Environments (TEEs) as promising solution approaches, and discuss both our proof-of-concept implementations and initial experimental, comparative evaluation results. The importance of trustworthy pre-processing and principle solution approaches are presented, addressing the major problem of end-to-end sensor data integrity in blockchain-based IoT applications.
Lelio Campanile, Pasquale Cantiello, Mauro Iacono, Fiammetta Marulli ¡ 5 authors
No abstract is available for this record.
Cyril Chimelie Anichukwueze, Vivian Chilee Osuji, Esther Ebunoluwa Oguntegbe
The exponential growth of digital transactions and regulatory requirements has necessitated the development of robust, transparent, and tamper-proof recordkeeping systems that can withstand the scrutiny of modern audit processes. This comprehensive study investigates the implementation and effectiveness of blockchain-based architectures for regulatory recordkeeping systems, with particular emphasis on achieving real-time audit readiness across multiple industry sectors. The research examines how distributed ledger technology can address the fundamental challenges of data integrity, transparency, and immutability that traditional centralized recordkeeping systems have struggled to resolve effectively. The investigation encompasses a thorough analysis of existing blockchain frameworks, consensus mechanisms, and smart contract implementations specifically designed for regulatory compliance applications. Through systematic evaluation of various blockchain architectures, including permissioned networks, hybrid systems, and consortium blockchains, this study identifies optimal configurations for different regulatory environments. The research methodology combines theoretical framework analysis with practical implementation case studies from financial services, healthcare, supply chain management, and energy sectors to provide comprehensive insights into the practical applications and limitations of blockchain-based regulatory systems. Key findings reveal that blockchain-based architectures demonstrate significant improvements in data integrity verification, audit trail transparency, and compliance monitoring capabilities compared to traditional systems. The study identifies critical success factors including proper node governance structures, appropriate consensus mechanisms, integration with existing enterprise systems, and compliance with data privacy regulations. However, the research also highlights substantial challenges including scalability limitations, energy consumption concerns, regulatory uncertainty, and the complexity of legacy system integration that must be addressed for successful implementation. The research contributes to the existing body of knowledge by proposing a comprehensive framework for evaluating blockchain suitability for specific regulatory environments, developing implementation guidelines for different industry contexts, and identifying best practices for maintaining audit readiness in distributed ledger systems. The study concludes that while blockchain technology offers transformative potential for regulatory recordkeeping, successful implementation requires careful consideration of technical, regulatory, and organizational factors to ensure both compliance and operational efficiency.
Yi Deng, Shunli Ma, Xinxuan Zhang, Hailong Wang ¡ 6 authors
No abstract is available for this record.
Rahul Ganpatrao Sonkamble, Shraddha Phansalkar, Vidyasagar Potdar, Anupkumar M. Bongale
Interoperability in Electronic Health Records (EHR) is significant for the seamless sharing of information amongst different healthcare stakeholders. Interoperability in EHR aims to devise agreements in its interpretation, access, and storage with security, privacy, and trust. A study and survey of state-of-the-art literature, prototypes, and projects in standardization of the EHR structure, privacy-preservation, and EHR sharing are very essential. The presented work conducts a systematic literature review to address four research questions. 1) What are the different standards for common interpretation, representation, and modeling of EHR to achieve semantic interoperability? 2) What are the different privacy-preservation techniques and security standards for EHR data storage? 3) How mature is blockchain technology for building interoperable, privacy-preserving solutions for EHR storage and sharing? 4) What is the state-of-the-art for cross-chain interoperability for EHR sharing? An exhaustive study of these questions establishes the potential of a blockchain-based EHR management framework in privacy preservation, access control and efficient storage. The study also unveils challenges in the adoption of blockchain in EHR management with the state-of-the-art maturity of cross-chain interoperable solutions for sharing EHR amongst stakeholders on different blockchain platforms. The research gaps culminate in proposing a blockchain-based EHR framework with privacy preservation and access control design. The proposed framework employs partitioning of EHR to on-chain and off-chain storages for performance guarantees with the retrieval of valid off-chain data. The framework is deployed on the Ethereum test network with Solidity smart contracts. It is observed that different test cases on the partitioning of the EHR data, yielded better read-write throughput and effective gas price than fully on-chain storage.