Phillipe Austria, Chol Hyun Park, Alex Hoffman, Yoohwan Kim
Cloud storage has become a prevalent choice for data storage for both business and personal use due to increasing data use. While cloud storage services, such as Google Drive, provide customers with high levels of data integrity and security, customers however lose privacy and require trust in the service provider to not act maliciously with their data. We explore an alternative to centralized, traditional cloud storage (TCS) using blockchain technology. In this paper, we tested and evaluated the performance and cost of Sia, a decentralized blockchain-based storage platform (BBS) that ensures users' privacy. The platform allows users to rent storage space from other users in exchange for Siacoin, Sia's native currency. Metrics were evaluated through various storage tests and results were compared to Google Drive. Performance tests showed Sia's available time, how long it takes for a file to upload and be download ready, to be 8–12 times slower than Google Drive. In contrast, Sia downloads were 2–3 times faster. Cost test revealed Sia's overall storage spending to be comparable to Google Drive and other popular TCS; however, results raised questions about spending details. Further testing is needed to fully understand the complexities of a BBS platform like Sia.
Zero-Knowledge proofs (ZKPs) enable proving of mathematical statements, revealing nothing but their validity. We design an authentication sys-tem with a ZKP as a password verification mech-anism within the Extensible Authentication Pro-tocol (EAP) framework. Designing a secure pass-word authentication system requires us to adopt security practices for protecting ourselves against the vulnerabilities of passwords. Integrating said practices is not trivial because of the tight cou-pling with the password verification method.
Digital identity is the key to the evolving digital society and economy. Since the inception of digital identity, numerous Identity Management (IDM) systems have been developed to manage digital identity depending on the requirements of the individual and that of organisations. This evolution of IDM systems has provided an incremental process leading to the granting of control of identity ownership and personal data to its user, thus producing an IDM which is more user-centric with enhanced security and privacy. A recently promising IDM known as Self-Sovereign Identity (SSI) has the potential to provide this sovereignty to the identity owner. The Sovrin Network is an emerging SSI service utility enabling self-sovereign identity for all, therefore, its assessment has to be carefully considered with reference to its architecture, working, functionality, strengths and limitations. This paper presents an analysis of the Sovrin Network based on aforementioned features. Firstly, it presents the architecture and components of the Sovrin Network. Secondly, it illustrates the working of the Sovrin Network and performs a detailed analysis of its various functionalities and metrics. Finally, based on the detailed analysis, it presents the strengths and limitations of the Sovrin Network.
Vincent Schlatt, Johannes Sedlmeir, Janina Traue, Fabiane Völter
The digital transformation of the medical sector requires solutions that are convenient and efficient for all stakeholders while protecting patients' sensitive data. One example that has already attracted design-oriented research are medical prescriptions. However, current implementations of electronic prescription management systems typically create centralized data silos, leaving user data vulnerable to cybersecurity incidents and impeding interoperability. Research has also proposed decentralized solutions based on blockchain technology, but privacy-related challenges have often been ignored. We conduct design science research to develop and implement a system for the exchange of electronic prescriptions that builds on two blockchains and a digital wallet app. Our solution combines the bilateral, verifiable, and privacy-focused exchange of information between doctors, patients, and pharmacies through verifiable credentials with a token-based, anonymized double-spending check. Our qualitative and quantitative evaluations as well as a security analysis suggest that this architecture can improve existing approaches to electronic prescription management by offering patients control over their data by design, a high level of security, sufficient performance and scalability, and interoperability with emerging digital identity management solutions for users, businesses, and institutions. We also derive principles on how to design decentralized, privacy-oriented information systems that require both the exchange of sensitive information and double-usage protection.
The application of technology in various aspects of life has made it easy for many people. However, there are also shortcomings in the use of technology, one of which is security issues, both transactions and data. Given these issues in this paper, we propose blockchain technology for an authentication system that will protect data rights and interests and be safe from interference to store information in the form of confidential text, especially in the application of technology in education. From this writing, there are 2 benefits, the first is that all data stored in the education system is guaranteed and there will be increased trust from both parents, teachers and other parties due to the decentralized nature of blockchain.
The application of blockchain to Vehicular Edge Computing (VEC) has attracted significant interests. As the Internet of Things plays an essential and fundamental role for data collecting, data analyzing, and data management in VEC, it is vital to guarantee the security of the data. However, the resource-constraint nature of edge node makes it challenging to meet the needs to maintain long life-cycle IoT data since vast volumes of IoT data quickly increase. In this paper, we propose Acce-chain, a storage-elastic blockchain based on different storage capacities at the edge. Acce-chain supports re-write operation to re-write the historical block with a newly generated block without breaking the hash links between the blocks. As a result, Acce-chain ensures that the hot data can be efficiently accessed at the edge without incurring much communication costs or increasing the total size of the chain. To guarantee the security of the re-write process, we propose a new cryptographic primitive named Dynamic Threshold Trapdoor Chameleon Hash (DTTCH). To guarantee the verifiability of query operation, we design a novel storage structure namedHybridStoreto ensure the verifiable query for on-chain/off-chain IoT data. As a result, Acce-chain achieves both authorized re-write and verifiable query simultaneously. We provide security analysis for the DTTCH scheme and the IoT data query algorithms. We evaluate Acce-chain through experiments and the results show that the performance of the re-write operation is feasible in real-world VEC settings, and the query efficiency can achieve up to several magnitudes better than which of the baseline. The results also demonstrate that Acce-chain can provide high service quality for the latency-sensitive VEC systems.
Most of the existing identity management is the centralized architecture that has to validate, certify, and manage identity in a centralized approach by trusted authorities. Decentralized identity is causing widespread public concern because it enables to give back control of identity to clients, and the client then has the ability to control when, where, and with whom they share their credentials. A decentralized solution atop on blockchain will bypass the centralized architecture and address the single point of the failure problem. To our knowledge, blockchain is an inherited pseudonym but it cannot achieve anonymity and auditability directly. In this paper, we approach the problem of decentralized identity management starting from the designated-verifier anonymous credential (DVAC in short). DVAC would assist to build a new practical decentralized identity management with anonymity and auditability. Apart from the advantages of the conventional anonymous credential, the main advantage of the proposed DVAC atop blockchain is that the issued cryptographic token will be divided into shares at the issue phase and will be combined at the showing credential phase. Further, the smooth projective hash function ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi mathvariant="sans-serif">SPHF</a:mi> </a:math> in short) is regarded as a designated-verifier zero-knowledge proof system. Thus, we introduce the <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" id="M2"> <d:mi mathvariant="sans-serif">SPHF</d:mi> </d:math> to achieve the designated verifiability without compromising the privacy of clients. Finally, the security of the proposed DVAC is proved along with theoretical and experimental evaluations.
Summary In order to ensure best health care experience for the user, the user should be able to access or grant access to his medical information as the requirement arises. Currently, when the data are residing in hospital proprietary Electronic Health Record (EHR), this is not possible. Hence there is a requirement for patient operated PHR where the details of the treatment of patient is with the patient. This paper proposes a blockchain‐based, secure interoperable patient‐centric data access management system—MediTrans. In the proposed model, the patient owns his/her treatment related data and stores it in a secure personal health record (PHR) cloud. The tool provides technique for secure transfer of patient related data from Hospital EHR to patient PHR Cloud. Patient can give controlled access of patient's medical data to Health Care Providers for a specific period of time. MediTrans proposes secure access management of data stored in PHR cloud to authorised person via Blockchain Technology and Ciphertext policy attribute‐based encryption technique. The proposed design was evaluated by developing a prototype on Ethereum Blockchain with OpenEMR as the healthcare system. Performance analysis was carried out by varying the size of the data and the number of users. The results obtained were promising, which gives clear insights on the feasibility of the approach taken.
Summary Today, the integrity and authenticity of digital documents and data are often hard to verify. Existing public key infrastructures (PKIs) are capable of certifying digital identities but do not provide solutions to store signatures immutably, and the process of certification is often not transparent. We propose Veritaa, a distributed public key infrastructure with an integrated signature store (DPKISS). The central part of Veritaa is the Graph of Trust that manages identity claims and singed declarations between identity claims and document identifiers. An application‐specific distributed ledger is used to store the transactions that form the Graph of Trust immutably. For the distributed certification of identity claims, a reputation system based on signed trust declarations and domain vetting is used. In this work, we have designed and implemented the proposed architecture of Veritaa, created a testbed, and performed several experiments. The experiments show the benefits and the high performance of Veritaa.
A verifiable random function (VRF in short) is a powerful pseudo-random function that provides a non-interactively public verifiable proof for the correctness of its output. Recently, VRFs have found essential applications in blockchain design, such as random beacons and proof-of-stake consensus protocols. To our knowledge, the first generation of blockchain systems used inherently inefficient proof-of-work consensuses, and the research community tried to achieve the same properties by proposing proof-of-stake schemes where resource-intensive proof-of-work is emulated by cryptographic constructions. Unfortunately, those most discussed proof-of-stake consensuses (e.g., Algorand and Ouroborous family) are not future-proof because the building blocks are secure only under the classical hard assumptions; in particular, their designs ignore the advent of quantum computing and its implications. In this paper, we propose a generic compiler to obtain the post-quantum VRF from the simple VRF solution using symmetric-key primitives (e.g., non-interactive zero-knowledge system) with an intrinsic property of quantum-secure. Our novel solution is realized via two efficient zero-knowledge systems ZKBoo and ZKB++, respectively, to validate the compiler correctness. Our proof-of-concept implementation indicates that even today, the overheads introduced by our solution are acceptable in real-world deployments. We also demonstrate potential applications of a quantum-secure VRF, such as quantum-secure decentralized random beacon and lottery-based proof of stake consensus blockchain protocol.
Hanlin Zhang, Peng Gao, Jia Yu, Jie Lin · 5 authors
Linear Regression (LR) is a classical machine learning algorithm which has many applications in the cyber physical social systems (CPSS) to shape and simplify the way we live, work, and communicate. This paper focuses on the data analysis for CPSS when the Linear Regression is applied. The training process of LR is time-consuming since it involves complex matrix operations, especially when it gets a large scale training dataset In the CPSS. Thus, how to enable devices to efficiently perform the training process of the Linear Regression is of significant importance. To address this issue, in this paper, we present a secure, verifiable and fair approach to outsource LR to an untrustworthy cloud-server. In the proposed scheme, computation inputs/outputs are obscured so that the privacy of sensitive information is protected against cloud-server. Meanwhile, computation result from cloud-server is verifiable. Also, fairness is guaranteed by the blockchain, which ensures that the cloud gets paid only if he correctly performed the outsourced workload. Based on the presented approach, we exploited the fair, secure outsourcing system on the Ethereum blockchain. We analysed our presented scheme on theoretical and experimental, all of which indicate that the presented scheme is valid, secure and efficient.
Blockchain is a reliable and innovative technology that harnesses education and training through digital technologies. Nonetheless, it has been still an issue keeping track of student/graduate academic achievement and blockchain access rights management. Detailed information about academic performance within a certain period (semester) is not present in the official education documents. Furthermore, academic achievement documents issued by institutions are not secured against unauthorized changes due to the involvement of intermediaries. Therefore, verification of official educational documents has become a pressing issue owing to the recent development of digital technologies. However, effective tools to accelerate the verification are rare as the process takes time. This study provides a prototype of the UniverCert platform based on a consortium version of the decentralized, open-source Ethereum blockchain technology. The proposed platform is based on a globally distributed peer-to-peer network that allows educational institutions to partner with the blockchain network, track student data, verify academic performance, and share documents with other stakeholders. The UniverCert platform was developed on a consortium blockchain architecture to address the problems universities face in storing and securing student data. The system provides a solution to facilitate students’ registration, verification, and authenticity of educational documents.
Ashar Ahmad, Muhammad Saad, Mohammed A. Al Ghamdi, DaeHun Nyang · 5 authors
Audit trails are critical components in enterprise business applications, typically used for storing, tracking, and auditing data. Entities in the audit trail applications have weak trust boundaries, which expose them to various security risks and attacks. To harden the security and develop secure by design applications, blockchain technology has been recently introduced in the audit trails. Blockchains take a consensus-driven clean slate approach to equip audit trails with secure and transparent data processing, without a trusted intermediary. On a downside, blockchains significantly increase the space-time complexity of the audit trails, leading to high storage costs and low transaction throughput. In this article, we introduceBlockTrail, a novel blockchain architecture that fragments the legacy blockchain systems into layers of codependent hierarchies, thereby reducing the space-time complexity and increasing the throughput. BlockTrail is prototyped on the “practical Byzantine fault tolerance” protocol with a custom-built blockchain. Experiments with BlockTrail show that compared to the conventional schemes, BlockTrail is secure and efficient, with low storage footprint.
Alexander Djamali, Patrick Dossow, Michael Hinterstocker, Benjamin Schellinger · 7 authors
Abstract Due to a steeply growing number of energy assets, the increasingly decentralized and segmented energy sector fuels the potential for new digital use cases. In this paper, we focus our attention on the application field of asset logging, which addresses the collection, documentation, and usage of relevant asset data for direct or later verification. We identified a number of promising use cases that so far have not been implemented; supposedly due to the lack of a suitable technical infrastructure. Besides the high degree of complexity associated with various stakeholders and the diversity of assets involved, the main challenge we found in asset logging use cases is to guarantee the tamper-resistance and integrity of the stored data while meeting scalability, addressing cost requirements, and protecting sensitive data. Against this backdrop, we present a blockchain-based platform and argue that it can meet all identified requirements. Our proposed technical solution hierarchically aggregates data in Merkle trees and leverages Merkle proofs for the efficient and privacy-preserving verification of data integrity, thereby ensuring scalability even for highly frequent data logging. By connecting all stakeholders and assets involved on the platform through bilateral and authenticated communication channels and adding a blockchain as a shared foundation of trust, we implement a wide range of asset logging use cases and provide the basis for leveraging platform effects in future use cases that build on verifiable data. Along with the technical aspects of our solution, we discuss the challenges of its practical implementation in the energy sector and the next steps for testing in a regulatory sandbox approach.
Recent successful pilot studies on blockchains showed significant benefits of data provenance towards improved visibility and authenticity, as well as a reduction of administrative costs. Traditionally, all the parties reside in a single blockchain system, which leads to various single-chain provenance query schemes. However, for the sake of convenience, it has been a trend for different parties to deploy their own blockchain systems separately, which requires cross-chain provenance queries. Unfortunately, state-of-the-art blockchain query schemes suffered from inauthentic transactions and low efficiencies when expanding to adversarial cross-chain commercial deals. To be more specific, query results may be inconsistent and incomplete over multiple blockchains due to the lack of global knowledge on cross-chain dependencies. Moreover, these schemes perform cross-chain provenance queries in sequence, leading to high query latencies. In this paper, we present Vassago, the first multi-chain system that empowers efficient and authenticated provenance queries. Vassago incorporates three innovative designs: 1) it explores the dependencies of cross-chain transactions, 2) it validates the authenticity of cross-chain provenance by recording and querying the dependencies on a shared blockchain, and 3) it improves efficiency by parallelizing query processes. Our experimental results show that Vassago can shorten the query latency by 85.9% and reduce the storage consumption by up to 85.7%, with negligible overhead.
In inter-collaborative workflows, several role instances may coexist. Depending on which roles are applied to a specific task, trust issues can potentially occur. Blockchain has been proposed as a trusted execution system, ensuring the task’s execution integrity and transparency. Smart contracts can not only manage the task or workflow execution but also the allocation of tasks in a decentralized and reliable fashion. In this paper, we leverage smart contracts as resource binders to match dynamically the resource with the best quality of service to a service request. If a match occurs, the system generates a binding agreement autonomously. The latter can be mapped to a business process management system to manage the task status. We implement this algorithm in a real-world setting to demonstrate the approach’s feasibility, and we carry on with quantitative experiments to confirm the validity of the protocol.
Zero-knowledge proofs help to protect the privacy and security of blockchains by keeping the transaction information private. Bulletproofs are the state-of-the-art zero-knowledge technologies that perform confidential transactions without a trusted setup. However, Bulletproofs are still computationally inefficient to be applied in blockchain applications, and it is of great significance to parallelize Bulletproofs on GPUs. In this paper, we present a CPU-GPU collaborative framework to accelerate the inner-product arguments of Bulletproofs. To our best knowledge, it is the first time that Bulletproofs are implemented in a CPU-GPU hybrid system. The experiments show that our implementation achieves an average speedup ratio of 3.7x. The results also demonstrate that the CPU-GPU collaborative acceleration of Bulletproofs has properties of small size, high efficiency, and high scalability.
Access control is a major factor in enhancing data security in the cloud storage system. However, the existing data sharing and the access control method have privacy data leakage and key abuse, which is a major challenge in the research community. Therefore, an effective method named Blockchain-based access control and data sharing approach is developed in the cloud storage system to increase data security. The proposed Blockchain-based access control and data sharing approach effectively solve single-point failure in the cloud system. It provides more benefits by increasing the throughput and reducing the cost. The Data user (DU) makes the registration request using the ID and password and forwards it to the Data Owner (DO), which processes the request and authenticates the Data user. The information of the data owner is embedded in the transactional blockchain using the encrypted master key. The Data owner achieves the data encryption process, and encrypted files are uploaded to the Interplanetary File System (IPFS). Based on the encrypted file location and encrypted key, the Data owner generates the ciphertext metadata and is embedded in the transactional blockchain. The proposed Blockchain-based access control and data sharing approach achieved better performance using the metrics, like a better genuine user detection rate of 95% and lower responsiveness of 25sec with the blockchain of 100 sizes.
The integrity of data stored in cloud environments is a critical concern as organizations increasingly rely on distributed cloud services for their data storage and processing needs. Traditional methods of data integrity assurance, such as cryptographic hashing and third-party audits, often fail to provide the required levels of security due to their centralized nature and reliance on trust in third-party entities. This paper proposes an AI augmented blockchain framework designed to provide a robust, decentralized solution for data integrity assurance in distributed cloud environments. By integrating Artificial Intelligence (AI) with blockchain technology, the proposed framework offers real-time anomaly detection, improved decision-making, and enhanced scalability for cloud data systems. The architecture utilizes a lightweight consensus mechanism, such as Delegated Proof of Stake (DPoS), to reduce latency and computational costs, while AI models are employed to identify anomalies in data transactions before they are permanently recorded on the blockchain. Experimental results show that the proposed system achieves a data integrity assurance rate of 98.5%, significantly outperforming traditional blockchain methods. Moreover, the framework reduces average transaction latency by 35% and increases transaction throughput by 43%. This results in a more efficient and sustainable approach to data integrity management, making it suitable for large-scale cloud deployments. The findings suggest that the AI-augmented blockchain framework can serve as a foundational solution for building trustworthy, tamper-proof data systems, with applications ranging from enterprise cloud services to secure Internet of Things (IoT) deployments. These advancements contribute to a more secure and resilient cloud computing environment, addressing the evolving challenges of data integrity and security.
Desire Ngabo, Dong Wang, Celestine Iwendi, Joseph Henry Anajemba · 6 authors
The recent developments in fog computing architecture and cloud of things (CoT) technology includes data mining management and artificial intelligence operations. However, one of the major challenges of this model is vulnerability to security threats and cyber-attacks against the fog computing layers. In such a scenario, each of the layers are susceptible to different intimidations, including the sensed data (edge layer), computing and processing of data (fog (layer), and storage and management for public users (cloud). The conventional data storage and security mechanisms that are currently in use appear to not be suitable for such a huge amount of generated data in the fog computing architecture. Thus, the major focus of this research is to provide security countermeasures against medical data mining threats, which are generated from the sensing layer (a human wearable device) and storage of data in the cloud database of internet of things (IoT). Therefore, we propose a public-permissioned blockchain security mechanism using elliptic curve crypto (ECC) digital signature that that supports a distributed ledger database (server) to provide an immutable security solution, transaction transparency and prevent the patient records tampering at the IoTs fog layer. The blockchain technology approach also helps to mitigate these issues of latency, centralization, and scalability in the fog model.
Preserving privacy and integrity is one of the important needs of any internet based platform especially if it is based on cloud. Block chain has been a recent technology key player in securing cloud based platforms. In the proposed work, we have used Blockchain technologies to provide encryption for cloud IoT results. Blockchain has recently become a promising software for cloud cluster integration and enhancement of cloud transaction protection and access to data and application codes. The main objective is to use blockchain technology to encrypt heterogeneous and enormous data. Authorizing the data obtained from different sources. Furthermore, more stable and better hash functions, such as SHA-256, SHA-384, and MD5 are now available, a future attacker would require more time to produce all available SHA512 hashes to brute force a hashed password from your database from a security standpoint. As a result, we consider SHA512 to be more robust and reliable in terms of the time it takes to compute a single hash when opposed to all other hash functions. As a result, we have introduced modified SHA512 in the proposed work for added reliability