The public key infrastructure (PKI) based authentication protocol provides the basic security services for vehicular ad-hoc networks (VANETs). However, trust and privacy are still open issues due to the unique characteristics of vehicles. It is crucial for VANETs to prevent internal vehicles from broadcasting forged messages while simultaneously protecting the privacy of each vehicle against tracking attacks. In this paper, we propose a blockchain-based anonymous reputation system (BARS) to break the linkability between real identities and public keys to preserve privacy. The certificate and revocation transparency is implemented efficiently using two blockchains. We design a trust model to improve the trustworthiness of messages relying on the reputation of the sender based on both direct historical interactions and indirect opinions about the sender. Experiments are conducted to evaluate BARS in terms of security and performance and the results show that BARS is able to establish distributed trust management, while protecting the privacy of vehicles.
Gihan J. Mendis, Moein Sabounchi, Wei Jin, Rigoberto Roche
Deep learning algorithms have recently gained attention due to their inherent capabilities and the application opportunities that they provide. Two of the main reasons for the success of deep learning methods are the availability of processing power and big data. Both of these two are expensive and rare commodities that present limitations to the usage and implementation of deep learning. Decentralization of the processing and data is one of the most prevalent solutions for these issues. This paper proposes a cooperative decentralized deep learning architecture. The contributors can train deep learning models with private data and share them to the cooperative data-driven applications initiated elsewhere. Shared models are fused together to obtain a better model. In this work, the contributors can both design their own models or train the models provided by the initiator. In order to utilize an efficient decentralized learning algorithm, blockchain technology is incorporated as a method of creating an incentive-compatible market. In the proposed method, Ethereum blockchain's scripting capabilities are employed to devise a decentralized deep learning mechanism, which provides much higher, collective processing power and grants access to large amounts of data, which would be otherwise inaccessible. The technical description of the mechanism is described and the simulation results are presented.
Personal data are often collected and processed in a decentralized fashion, within different contexts. For instance, with the emergence of distributed applications, several providers are used to correlate their records, to provide personalized services to their clients. As such, to protect users' privacy, different pseudonyms are generally used for different contexts. These pseudonyms have to be unlinkable to prevent identifying records to be associated to the same user. Although unlinkable, these pseudonyms have to be processed and exchanged according to their owners' consent and in a privacy-preserving fashion. In this paper, we propose BDUA, a new Blockchain-based Data Usage Auditing system, that ensures a controlled yet privacy preserving exchange of distributed data, such that a set of authorized auditing entities are able to conduct an accurate auditing relying on registered blockchains' transactions.
Juan Carlos Farah, Andrii Vozniuk, María Jesús Rodríguez‐Triana, Denis Gillet
The need to ensure privacy and data protection in educational contexts is driving a shift towards new ways of securing and managing learning records. Although there are platforms available to store educational activity traces outside of a central repository, no solution currently guarantees that these traces are authentic when they are retrieved for review. This paper presents a blueprint for an architecture that employs blockchain technology to sign and validate learning traces, allowing them to be stored in a distributed network of repositories without diminishing their authenticity. Our proposal puts participants in online learning activities at the center of the design process, granting them the option to store learning traces in a location of their choice. Using smart contracts, stakeholders can retrieve the data, securely share it with third parties and ensure it has not been tampered with, providing a more transparent and reliable source for learning analytics. Nonetheless, a preliminary evaluation found that only 56% of teachers surveyed considered tamper-evident storage a useful feature of a learning trace repository. These results motivate further examination with other end users, such as learning analytics researchers, who may have stricter expectations of authenticity for data used in their practice.
Γεώργιος Σπαθούλας, Anastasija Collen, Pankaj Pandey, Niels Alexander Nijdam · 10 authors
The European research project GHOST challenges the traditional cyber security solutions for the Internet of Things (IoT) sector by exploiting novel technologies, such as blockchain, to provide resilience and integrity of decision making on the communication exchange in a smart home context. When it comes to novel cyber security solutions for extremely heterogeneous environments like IoT and smart homes, the key focus is typically given to the understanding of network activities and elimination of suspicious traffic. The GHOST project adds an extra dimension to this approach by integrating blockchain technology at its core decision mechanism. On a daily basis, each GHOST installation is encountering malicious behaviour and suspicious IoT communications, where easy information sharing with other installations, as well as decentralised decision making, are mandatory features for the efficient protection of the end-user. GHOST's Smart Contracts (SC) are designed to tackle in an easy, yet productive way, the reporting on suspicious IP addresses which the IoT devices in a smart home are trying to communicate with. Two variations of blacklisting smart contracts are presented in this paper, covering a diverse spectrum of possible attack vectors while closely following the Privacy by Design (PbD) principles. A reputation scoring scheme for malicious IPs reporting is integrated in the SC, uncovering the implementation details on the penalisation of existing entries in case of malicious behaviour of reporting devices.
Sara Rouhani, Luke Butterworth, Adam D. Simmons, Darryl G. Humphery · 5 authors
The set of distributed ledger architectures known as blockchain is best known for cryptocurrency applications such as Bitcoin and Ethereum. These permissionless block chains are showing the potential to be disruptive to the financial services industry. Their broader adoption is likely to be limited by the maximum block size, the cost of the Proof of Work consensus mechanism, and the increasing size of any given chain overwhelming most of the participating nodes. These factors have led to many cryptocurrency blockchains to become centralized in the nodes with enough computing power and storage to be a dominant miner and validator. Permissioned chains operate in trusted environments and can, therefore, avoid the computationally expensive consensus mechanisms. Permissioned chains are still susceptible to asset storage demands and non-standard user interfaces that will impede their adoption. This paper describes an approach to addressing these limitations: permissioned blockchain that uses off-chain storage of the data assets and this is accessed through a standard browser and mobile app. The implementation in the Hyperledger framework is described as is an example use of patient-centered health data management.
Although the blockchain is widely acknowledged as one of the most disruptive technologies emerged in the last decades, many implementation hurdles at the technical, regulatory and governance level still prevent a widespread adoption of services based on open networks. This research discusses the role Trust Service Providers may play in permissioned blockchains, providing a reliable ecosystem in which services can be safely developed and preserved in the long run. As case study, the paper outlines the main features of TrustedChain®, the first blockchain network of European Trust Service Providers specifically designed for highly sensitive sectors, with cutting-edge applications for public administration, e-government, banking, e-health and industry. Emphasis is thus placed on systemic trust, law compliance, adequate technical performance, confidentiality of transactions and long term preservation of data as essential conditions for blockchain networks to thrive and accomplish complex tasks in an effective and reliable way.
Intelligence is one of the most important aspects in the development of our future communities. Ranging from smart home to smart building to smart city, all these smart infrastructures must be supported by intelligent power supply. Smart grid is proposed to solve all challenges of future electricity supply. In smart grid, in order to realize optimal scheduling, an SM is installed at each home to collect the near-real-time electricity consumption data, which can be used by the utilities to offer better smart home services. However, the near-real-time data may disclose a user's private information. An adversary may track the application usage patterns by analyzing the user's electricity consumption profile. In this article, we propose a privacy-preserving and efficient data aggregation scheme. We divide users into different groups, and each group has a private blockchain to record its members' data. To preserve the inner privacy within a group, we use pseudonyms to hide users' identities, and each user may create multiple pseudonyms and associate his/ her data with different pseudonyms. In addition, the bloom filter is adopted for fast authentication. The analysis shows that the proposed scheme can meet the security requirements and achieve better performance than other popular methods.
Blockchain technologies, such as smart contracts, present a unique interface for machine-to-machine communication that provides a secure, append-only record that can be shared without trust and without a central administrator. We study the possibilities and limitations of using smart contracts for machine-to-machine communication by designing, implementing, and evaluating AGasP, an application for automated gasoline purchases. We find that using smart contracts allows us to directly address the challenges of transparency, longevity, and trust in IoT applications. However, real-world applications using smart contracts must address their important trade-offs, such as performance, privacy, and the challenge of ensuring they are written correctly.
The use of distributed ledger technologies introduces new security and privacy challenges. These challenges are dependent on properties of the ledgers, such as transaction latency and throughput. Some use cases may be outright impossible to implement securely, or in a privacy-retaining manner. Consequently, it is important that these concerns are taken into account when distributed ledger technologies are evaluated and selected as building blocks for higher-level systems. In this paper, we illustrate these concerns through use case examples. We discuss the implications these concerns on the use of distributed ledgers within higher-level systems, such as in SOFIE, a DLT-based approach to securely and openly federate IoT systems.
Preuves à divulgation nulle de connaissance efficaces à base de réseaux euclidiens et applications Le chiffrement à base de réseaux euclidiens a connu un grand essor durant les vingt dernières années. Autant grâce à l’apparition de nouvelles primitives telles que le chiffrement complètement homomorphe, que grâce à l’amélioration des primitives existantes, comme le chiffrement á clef publique ou les signatures digitales, qui commencent désormais à rivaliser avec leurs homologues fondés sur la théorie des nombres. Cela dit les preuves à divulgation nulle de connaissance, bien qu’elles représentent un des piliers des protocols de confidentialité, n’ont pas autant progressé, que ce soit au niveau de leur expressivité que de leur efficacité. Cette thèse s’attelle dans un premier temps à améliorer l’état de l’art en matière de preuves à divulgation nulle de connaissance. Nous construisons une preuve d’appartenance à un sous ensemble dont la taille est indépendante de l’ensemble en question. Nous construisons de même une preuve de connaissance amortie qui est plus efficace et plus simple que toutes les constructions qui la précèdent. Notre second propos est d’utiliser ces preuves à divulgation nulle de connaissance pour construire de nouvelles primitives cryptographiques. Nous concevons une signature de groupe dont la taille est indépendante du groupe en question, ainsi qu’un schéma de vote électronique hautement efficace, y compris pour des élections à grand échelle.
Joaõ Pedro Dias, Hugo Sereno Ferreira, Ângelo Martins
Access control is a crucial part of a system's security, restricting what actions users can perform on resources. Therefore, access control is a core component when dealing with e-Health data and resources, discriminating which is available for a certain party. We consider that current systems that attempt to assure the share of policies between facilities are prone to system's and network's faults and do not assure the integrity of policies lifecycle. By approaching this problem with the use of a distributed ledger, namely a consortium blockchain, where the operations are stored as transactions, we ensure that the different facilities have knowledge about all the parties that can act over the e-Health resources while maintaining integrity, auditability, authenticity, and scalability.
A problem facing healthcare record systems throughout the world is how to share the medical data with more stakeholders for various purposes without sacrificing data privacy and integrity. Blockchain, operating in a state of consensus, is the underpinning technology that maintains the Bitcoin transaction ledger. Blockchain as a promising technology to manage the transactions has been gaining popularity in the domain of healthcare. Blockchain technology has the potential of securely, privately, and comprehensively manage patient health records. In this work, we discuss the latest status of blockchain technology and how it could solve the current issues in healthcare systems. We evaluate the blockchain technology from the multiple perspectives around healthcare data, including privacy, security, control, and storage. We review the current projects and researches of blockchain in the domain of healthcare records and provide the insight into the design and construction of next generations of blockchain-based healthcare systems.
In this paper, we propose an architecture for Blockchain-based Electronic Medical Records (EMRs) called GAA-FQ (Granular Access Authorisation supporting Flexible Queries) that comprises an access model and an access authorisation scheme. Unlike existing Blockchain schemes, our access model can authorise different levels of granularity of authorisation, whilst maintaining compatibility with the underlying Blockchain data structure. Furthermore, the authorisation, encryption, and decryption algorithms proposed in the GAA-FQ scheme dispense with the need to use a public key infrastructure (PKI) and hence improve the computation performance needed to support more granular and distributed, yet authorised, EMR data queries. We validated the computation performance and transmission efficiency for GAA-FQ using a simulation of GAA-FQ against an access control scheme for EMRs called ESPAC as our baseline that was not designed using a Blockchain. To the best of our knowledge, GAA- FQ is the first Blockchain-oriented access authorisation scheme with granular access control, supporting flexible data queries, that has been proposed for secure EMR information management.
Motivated by the great success and adoption of Bitcoin, a number of cryptocurrencies such as Litecoin, Dogecoin, and Ethereum are becoming increasingly popular. Although existing blockchain-based cryptocurrency schemes can ensure reasonable security for transactions, they do not consider any notion of fairness. Fair exchange allows two players to exchange digital “items,” such as digital signatures, over insecure networks fairly, so that either each player gets the other's item, or neither player does. Given that blockchain participants typically do not trust each other, enabling fairness in existing cryptocurrencies is an essential but insufficiently explored problem. In this article, we explore the solution space for enabling the fair exchange of a cryptocurrency payment for a receipt. We identify the timeliness of an exchange as an important property especially when one of the parties involved in the exchange is resource-constrained. We introduce the notion of strong timeliness for a fair exchange protocol and propose two fair payment-for-receipt protocol instantiations that leverage functionality of the blockchain to achieve strong timeliness. We implement both and compare their security and efficiency.
Kevin Liu, Harsh Desai, Lalana Kagal, Murat Kantarcıoğlu
As more and more data is collected for various reasons, the sharing of such data becomes paramount to increasing its value. Many applications ranging from smart cities to personalized health care require individuals and organizations to share data at an unprecedented scale. Data sharing is crucial in today's world, but due to privacy reasons, security concerns and regulation issues, the conditions under which the sharing occurs needs to be carefully specified. Currently, this process is done by lawyers and requires the costly signing of legal agreements. In many cases, these data sharing agreements are hard to track, manage or enforce. In this work, we propose a novel alternative for tracking, managing and especially enforcing such data sharing agreements using smart contracts and blockchain technology. We design a framework that generates smart contracts from parameters based on legal data sharing agreements. The terms in these agreements are automatically enforced by the system. Monetary punishment can be employed using secure voting by external auditors to hold the violators accountable. Our experimental evaluation shows that our proposed framework is efficient and low-cost.
John Collomosse, Tu Bui, Alan Brown, John Sheridan · 9 authors
We present ARCHANGEL; a de-centralised platform for ensuring the long-term integrity of digital documents stored within public archives. Document integrity is fundamental to public trust in archives. Yet currently that trust is built upon institutional reputation --- trust at face value in a centralised authority, like a national government archive or University. ARCHANGEL proposes a shift to a technological underscoring of that trust, using distributed ledger technology (DLT) to cryptographically guarantee the provenance, immutability and so the integrity of archived documents. We describe the ARCHANGEL architecture, and report on a prototype of that architecture build over the Ethereum infrastructure. We report early evaluation and feedback of ARCHANGEL from stakeholders in the research data archives space.
A trusted electronic election system requires that all the involved information must go public, that is, it focuses not only on transparency but also privacy issues. In other words, each ballot should be counted anonymously, correctly, and efficiently. In this work, a lightweight E-voting system is proposed for voters to minimize their trust in the authority or government. We ensure the transparency of election by putting all message on the Ethereum blockchain, in the meantime, the privacy of individual voter is protected via an efficient and effective ring signature mechanism. Besides, the attractive self-tallying feature is also built in our system, which guarantees that everyone who can access the blockchain network is able to tally the result on his own, no third party is required after voting phase. More importantly, we ensure the correctness of voting results and keep the Ethereum gas cost of individual participant as low as possible, at the same time. Clearly, the pre-described characteristics make our system more suitable for large-scale election.
Clinical research and health information data sharing are but ripples in a growing wave of reimagined applications of distributed ledger technologies beyond the digital marketplace for which they were originally created. This paper explores the use of distributed ledger technologies to facilitate single institutional ethics review of multi-site, collaborative studies in the dataintensive sciences such as genetics and genomics. Immutable record-keeping, automatable protocol amendments and direct connectivity between stakeholders in the research enterprise (e.g., researchers, research ethics committees, institutions, funders and regulators) comprise several of the conceptual and technological advantages of distributed ledger technologies to research ethics review. This novel-use proposal dovetails recent policy reforms to research ethics review across North America that mandate a single ethics review for any study that takes place across more than one research site. Such reforms in the United States, Canada and Australia replace prior institution-by-institution approval mechanisms that contributed to significant research delays and duplicative procedures for collaborative research worldwide. While this paper centers on the Common Rule revision in the United States, the single ethics review mandate is a noteworthy example of regulation evolving in parallel with advances in the dataintensive sciences it governs. The informational exchange capacities of distributed ledger technologies align well with the procedural goals of streamlining the ethics review system under the new Common Rule ahead of its official implementation on January 19, 2020. The ethical, legal and social implications of applying such technologies to ethics review will be explored in this concept paper. Namely, the paper proposes how administrative data from research ethics committees (REC) could be protected and shared responsibly, as well as interinstitutional cooperation negotiated within a centralized network of research ethics committees using the blockchain. Keywords: Blockchain, Data Sharing, Ethics Review, Governance, IRB, Research, Single Mutual Recognition
Open access
Ethics in Clinical Research
Artificial Intelligence in Healthcare and Education
Peng Jiang, Fuchun Guo, Willy Susilo, Man Ho Au · 6 authors
A procurement protocol is a protocol for a buyer to purchase digital goods at their prices from a vendor. A procurement protocol with privacy preservation can be achieved by priced oblivious transfer (POT). POT allows the buyer to obliviously procure items one by one. An adaptive POT protocol only consumes O(1) communication cost in each transaction, where all items are committed and encrypted before transactions. However, we found that the state-of-the-art adaptive POT protocol proposed by Rial et al. is less practical and does not meet real-world needs. It has to restrict to the one-buyer setting where all items are encrypted associated with one buyer's public key. For multiple buyers, the vendor must respectively encrypt all the same items for each buyer. Besides, it has to employ computationally expensive primitives such as zero-knowledge proof which imply inefficient computation operations. It is therefore unscalable and unsuitable in large-scale applications. In this paper, we propose an efficient adaptive priced oblivious transfer protocol to address the aforementioned problems. The proposed adaptive POT is built on top of a new cryptographic primitive, namely, adaptive set membership encryption (ASME). In our proposed protocol, all items are encrypted without the use of buyers' public keys and hence they can be used for universal buyers. Our protocol significantly reduces the transaction cost compared to existing schemes. For example, the communication in each transaction costs only 6 group elements compared to at least 141 group elements in Rial et al.'s protocol. The implementation shows that our protocol is efficient in terms of bandwidth and computational cost.
Olivia Choudhury, Hillol Sarker, Nolan Rudolph, Morgan A. Foreman · 9 authors
Recent changes to the Common Rule, which govern Institutional Review Boards (IRB), require implementing new policies to strengthen research protocols involving human subjects. A major challenge in implementing such policies is an inability to automatically and consistently meet these ethical rules while securing sensitive information collected during the study. In this paper, we propose a novel framework, based on blockchain technology, to enforce IRB regulations on data collection. We demonstrate how to design smart contracts and a ledger to meet the requirements of an IRB protocol, including subject recruitment, informed consent management, secondary data sharing, monitoring risks, and generating automated assessments for continuous review. Furthermore, we show how we can employ the immutable transaction log in the blockchain to embed security in research activities by detecting malicious activities and robustly tracking subject involvement. We evaluate our approach by assessing its ability to enforce IRB guidelines in different types of human subjects studies, including a genomic study, a drug trial, and a wearable sensor monitoring study. Keywords: Blockchain, Data Sharing, Data Exchange, EHR, electronic health record, Ethereum, interplanetary filesystem, IPFS
Jiayu Zhou, Fengyi Tang, He Zhu, Ning Nan · 5 authors
Recent advances in blockchain technologies have provided exciting opportunities for decentralized applications. Specifically, blockchain-based smart contracts enable credible transactions without authorized third parties. The attractive properties of smart contracts facilitate distributed data vending, allowing for proprietary data to be securely exchanged on a blockchain. Distributed data vending can transform domains such as healthcare by encouraging data distribution from owners and enabling large-scale data aggregation. However, one key challenge in distributed data vending is the trade-off dilemma between the effectiveness of data retrieval, and the leakage risk from indexing the data. In this paper, we propose a framework for distributed data vending through a combination of data embedding and similarity learning. We illustrate our framework through a practical scenario of distributing and aggregating electronic medical records on a blockchain. Extensive empirical results demonstrate the effectiveness of our framework.
Abstract A functional credential allows a user to anonymously prove possession of a set of attributes that fulfills a certain policy. The policies are arbitrary polynomially computable predicates that are evaluated over arbitrary attributes. The key feature of this primitive is the delegation of verification to third parties, called designated verifiers. The delegation protects the privacy of the policy : A designated verifier can verify that a user satisfies a certain policy without learning anything about the policy itself. We illustrate the usefulness of this property in different applications, including outsourced databases with access control. We present a new framework to construct functional credentials that does not require (non-interactive) zero-knowledge proofs. This is important in settings where the statements are complex and thus the resulting zero-knowledge proofs are not efficient. Our construction is based on any predicate encryption scheme and the security relies on standard assumptions. A complexity analysis and an experimental evaluation confirm the practicality of our approach.