Multi-party authorization (MPA) typically involves multiple parties to control and grant access to shared data. MPA is used to solve the insider’s attack problem by ensuring that a single authority or party is not acting alone. Currently, almost all existing implementations of MPA are centralized and fall short in providing logs and events related to provenance of granting permissions in a trusted, secure, immutable, auditable, and decentralized manner. Moreover, for sharing data, proxy re-encryption algorithms are often used to give secure access to encrypted shared data. These schemes and algorithms are also centralized and cannot be trusted. In this paper, we propose a fully decentralized blockchain-based solution in which MPA is implemented using Ethereum smart contracts, and proxy re-encryption algorithms (which are computationally expensive) are implemented using multiple oracles to give access to encrypted shared data stored on a public and decentralized storage platform, such as the Interplanetary File Systems (IPFS). The smart contracts help to validate results based on the majority of encrypted results determined by the oracles. For this, we incorporate reputation mechanisms in the proposed smart contracts to rate the oracles based on their malicious and non-malicious behaviors. We present algorithms along with their full implementation, testing, and validation details. We evaluate the proposed system in terms of security, cost, and generalization to show its reliability and practicality. We make the smart contract source code publicly available on Github.
Marc Eisenstadt, Manoharan Ramachandran, Niaz Chowdhury, Allan Third · 5 authors
Goal: As the Coronavirus Pandemic of 2019/2020 unfolds, a COVID-19 ‘Immunity Passport’ has been mooted as a way to enable individuals to return back to work. While the quality of antibody testing, the avail- the ability of vaccines, and the likelihood of even attaining COVID-19 immunity continue to be researched, we address the issues involved in providing tamper-proof and privacy-preserving certification for test results and vaccinations. Methods: We developed a prototype mobile phone app and requisite decentralized server architecture that facilitates instant verification of tamper-proof test results. Personally identifiable information is only stored at the user’s discretion, and the app allows the end-user selectively to present only the specific test result with no other personal information revealed. The architecture, designed for scalability, relies upon (a) the 2019 World Wide Web Consortium standard called ‘Verifiable Credentials’, (b) Tim Berners-Lee’s decentralized personal data platform ‘Solid’, and (c) a Consortium Ethereum-based blockchain. Results: Our mobile phone app and decentralized server architecture enable the mixture of verifiability and privacy in a manner derived from public/private key pairs and digital signatures, generalized to avoid restrictive ownership of sensitive digital keys and/or data. Benchmark performance tests show it to scale linearly in the worst case, as significant processing is done locally on each app. For the test certificate Holder, Issuer (e.g. healthcare staff, pharmacy) and Verifier (e.g. employer), it is ‘just another app’ which takes only minutes to use. Conclusions: The app and decentralized server architecture offer a prototype proof of concept that is readily scalable, applicable generically, and in effect ‘waiting in the wings’ for the biological issues, plus key ethical issues raised in the discussion section, to be resolved.
Accountability is a fundamental after-the-fact approach to detect and punish illegal actions during the execution of a warrant for accessing users’ sensitive data. To achieve accountability in a security protocol, a trusted authority is required, denoted as judge, to faithfully cooperate with the rest of the entities in the system. However, malicious judges or uncooperative protocol participants may void the accountability mechanism in practice, for example by fabricating fake evidence or by refusing to provide any evidence at all. To provide remediation to these issues, in this paper we propose Fialka, a novel accountable decryption system based on privacy-preserving smart contracts (PPSC). The neutrality that is inherent to a secure blockchain platform is inherited by PPSC which are then used in our approach as an accountable key manager as well as a transparent judge. To the best of our knowledge, we present the first PPSC-based accountable decryption system to increase the transparency of warrant execution with formal definitions and proofs. Furthermore, we provide and evaluate a prototype implementation using the PPSC-enabled platform Oasis Devnet, which additionally demonstrates the feasibility of Fialka.
Blockchain-Based Healthcare System (HS-BC) is an electronic medical record (EMR) data-sharing system, which significantly facilitates the storage, access, and sharing of EMR data, and provides patients with timely and effective medical diagnosis and treatment. However, due to the high openness of the blockchain, security and privacy still are major concerns in HS-BC. In this paper, we propose an attribute-based signature scheme with attribute revocation to protect the privacy of the user's identity in HS-BC. Under the premise of using attributes to identify users and protect their identity, the user combines the attribute master-key and the attribute update-key to calculate the attribute signing key, where the attribute master-key is related to the user identity and attribute set, and the attribute update-key is related to the attribute revocation. Through making use of the KUNodes algorithm, attribute revocation can effectively achieve. The designed attribute-based signature scheme requires relatively few pairing operations and does not rely on a central authority. Besides, we formally conducted a security analysis and proved that the proposed scheme is unforgeable, collusion resistant and privacy-preserving. Finally, we evaluate the proposed attribute-based signature scheme in terms of storage and efficiency. Comparison and experimental results show that it is feasible.
Automated digital contact tracing is effective and efficient, and one of the non-pharmaceutical complementary approaches to mitigate and manage epidemics like Coronavirus disease 2019 (COVID-19). Despite the advantages of digital contact tracing, it is not widely used in the western world, including the US and Europe, due to strict privacy regulations and patient rights. We categorized the current approaches for contact tracing, namely: mobile service-provider-application, mobile network operators' call detail, citizen-application, and IoT-based. Current measures for infection control and tracing do not include animals and moving objects like cars despite evidence that these moving objects can be infection carriers. In this article, we designed and presented a novel privacy anonymous IoT model. We presented an RFID proof-of-concept for this model. Our model leverages blockchain's trust-oriented decentralization for on-chain data logging and retrieval. Our model solution will allow moving objects to receive or send notifications when they are close to a flagged, probable, or confirmed diseased case, or flagged place or object. We implemented and presented three prototype blockchain smart contracts for our model. We then simulated contract deployments and execution of functions. We presented the cost differentials. Our simulation results show less than one-second deployment and call time for smart contracts, though, in real life, it can be up to 25 seconds on Ethereum public blockchain. Our simulation results also show that it costs an average of $1.95 to deploy our prototype smart contracts, and an average of $0.34 to call our functions. Our model will make it easy to identify clusters of infection contacts and help deliver a notification for mass isolation while preserving individual privacy. Furthermore, it can be used to understand better human connectivity, model similar other infection spread network, and develop public policies to control the spread of COVID-19 while preparing for future epidemics.
Fog computing (FC) is the extension of Cloud Computing (CC), from the core of the internet architecture to the edge of the network, with the aim to perform processes closer to end-users. This extension is proven to enhance security, and to reduce latency and energy consumption. Blockchain (BC), on the other hand, is the base technology behind crypto-currencies, yet is implemented in wide range of different applications. The security and reliability, along with the distributed trust management criteria proposed in BC, excited the research community to integrate it with FC, in a step towards reaching a distributed and trusted, Data, Payment, Reputation, and Identity management systems. In this survey we present the up-to-date state-of-the-art of FC-BC integration with a detailed literature review and classification. We discuss and categorize the related papers according to the year of publication, domain, used algorithms, BC roles, and the placement of the BC in the FC architecture. Our research presents detailed observations, analysis, and open challenges for the BC-FC integration. We believe such conclusions may clarify the vision of the BC-FC integration, and calibrate the compass towards open issues and future research directions.
Due to the long train marshaling and complex line conditions, the operating modes in heavy haul rail systems frequently change when trains travel. Improper traction or braking operation made by drivers will increase the longitudinal impact force to trains and causes the train decoupling, severely affecting the safe operations of trains. It is quite desirable to replace the manual control with intelligent control in heavy haul rail systems. Traditional machine learning-based intelligent control methods suffer from insufficient data. Due to lacking effective incentives and trust, data from different rail lines or operators cannot be shared directly. In this paper, we propose an approach on blockchain-based federated learning to implement asynchronous collaborative machine learning between distributed agents that own data. This method performs distributed machine learning without a trusted central server. The blockchain smart contract is used to realize the management of the entire federated learning. Using the historical driving data collected from real heavy haul rail systems, the learning agent in the federated learning method adopts a support vector machine (SVM) based intelligent control model. To deal with the imbalanced traction and braking data, we optimize the classic SVM model via assigning different penalty factors to the majority and minority classes. The data set are mapped to a high dimension using kernel functions to make it linearly separable. We construct a mixing kernel function composed of polynomial and radial basis function (RBF) kernel functions, which uses a dynamic weight factor changing with train speeds to improve the model accuracy. The simulation results demonstrate the efficiency and accuracy of our proposed intelligent control method.
In a recent seminal work, Bitansky and Shmueli (STOC '20) gave the first construction of a constant round zero-knowledge argument for NP secure against quantum attacks. However, their construction has several drawbacks compared to the classical counterparts. Specifically, their construction only achieves computational soundness, requires strong assumptions of quantum hardness of learning with errors (QLWE assumption) and the existence of quantum fully homomorphic encryption (QFHE), and relies on non-black-box simulation. In this paper, we resolve these issues at the cost of weakening the notion of zero-knowledge to what is called $\epsilon$-zero-knowledge. Concretely, we construct the following protocols:
- We construct a constant round interactive proof for NP that satisfies statistical soundness and black-box $\epsilon$-zero-knowledge against quantum attacks assuming the existence of collapsing hash functions, which is a quantum counterpart of collision-resistant hash functions. Interestingly, this construction is just an adapted version of the classical protocol by Goldreich and Kahan (JoC '96) though the proof of $\epsilon$-zero-knowledge property against quantum adversaries requires novel ideas.
- We construct a constant round interactive argument for NP that satisfies computational soundness and black-box $\epsilon$-zero-knowledge against quantum attacks only assuming the existence of post-quantum one-way functions.
At the heart of our results is a new quantum rewinding technique that enables a simulator to extract a committed message of a malicious verifier while simulating verifier's internal state in an appropriate sense.
We put forth a new framework for building pairing-based non-interactive zero-knowledge (\(\mathsf {NIZK}\)) arguments for a wide class of algebraic languages, which are an extension of linear languages, containing disjunctions of linear languages and more. Our approach differs from the Groth-Sahai methodology, in that we rely on pairings to compile a \(\varSigma \)-protocol into a \(\mathsf {NIZK}\). Our framework enjoys a number of interesting features:
conceptual simplicity, parameters derive from the \(\varSigma \)-protocol;
proofs as short as resulting from the Fiat-Shamir heuristic applied to the underlying \(\varSigma \)-protocol;
fully adaptive soundness and perfect zero-knowledge in the common random string model with a single random group element as CRS;
yields simple and efficient two-round, public coin, publicly-verifiable perfect witness-indistinguishable (WI) arguments(ZAPs) in the plain model. To our knowledge, this is the first construction of two-rounds statistical witness-indistinguishable arguments from pairing assumptions.
Security and privacy issues have become a rapidly growing problem with the fast development of big data in public health. However, big data faces many ongoing serious challenges in the process of collection, storage, and use. Among them, data security and privacy problems have attracted extensive interest. In an effort to overcome this challenge, this article aims to present a distributed privacy preservation approach based on smart contracts and Intel Software Guard Extensions (SGX). First of all, we define SGX as a trusted edge computing node, design data access module, data protection module, and data integrity check module, to achieve hardware-enhanced data privacy protection. Then, we design a smart contract framework to realize distributed data access control management in a big data environment. The crucial role of the smart contract was revealed by designing multiple access control contracts, register contracts, and history contracts. Access control contracts provide access control methods for different users and enable static access verification and dynamic access verification by checking the user’s properties and history behavior. Register contract contains user property information, edge computing node information, the access control and history smart contract information, and provides functions such as registration, update, and deletion. History contract records the historical behavior information of malicious users, receives the report information of malicious requestors from the access control contract, implements a misbehavior check method to determines whether the requestor has misbehavior, and returns the corresponding result. Finally, we design decentralized system architecture, prove the security properties, and analysis to verify the feasibility of the system. Results demonstrate that our method can effectively improve the timeliness of data, reduce network latency, and ensure the security, reliability, and traceability of data.
Die Möglichkeit, Computerberechnungen mit einem Beweis für deren korrekte Ausführung zu hinterlegen, scheint in Zeiten der oft genannten ‘Digitalisierung’ ein vielversprechendes Mittel zu sein, um es Parteien, die einander nicht trauen, zu ermöglichen sich auszutauschen. Diese Korrektheitsbeweise sind gerade im Themengebiet der Blockchain interessante und vielversprechende Kandidaten, um dortige Probleme zu adressieren. In dieser Arbeit untersuchen wir formal, was eine Blockchain im Sinne Nakamotos auszeichnet, und inwiefern sogenannte ‘Privacy Enhancing Technolgies’ in diesen dezentralen Systemen Anwendung finden. Das Hauptaugenmerk legen wir dabei auf ‘pairing-based preprocessed zero knowledge succinct non interactive arguments of knowledge’ (zkSNARKs). Wir untersuchen deren mathematische Grundlage und entwickeln unsere eigene zkSNARK Konstruktion. Diese basiert auf einer Erweiterung der gängigen F-arithmetischen Schaltung, die neben arithmetischen Operationen auch die der skalare Gruppenexponentiation auf elliptischen Kurven unterstützt. Die Implementierung ist in der Sprache Golang verfasst und unter einer GPL3.0 Lizenz auf Github zugänglich gemacht. Das Programm übersetzt eine eigens dafür entwickelte Programmiersprache in die Form eines ‘QuadraticArithmetic Programs’ und kann daher über unsere Arbeit hinaus in Beweissystemen basierend auf F-arithmetischen Schaltungen eingesetzt werden.
The healthcare industry electronically maintains medical data which includes patients' information such as patients' personal information, diagnostic reports, and doctor prescriptions. However, the centralized storage model is currently used for storing such sensitive information. One main disadvantage of the centralized model is the difficulty in preserving user privacy. Threats relating to user (patient) privacy include unauthorized access of critical information such as identity details and diseases from which a patient is suffering, and misuse of patients' data and their medical reports. To address this issue, we propose a distributed off-chain storage of medical data using IPFS (Interplanetary File System) and blockchain technology. The proposed framework while preserving patient privacy facilitates easy access of medical data by authorized entities such as healthcare providers (e.g., doctors and nurses). Moreover, it achieves consistency, integrity, and availability.
Bao Nguyen, E. Laxmi Lydia, Mohamed Elhoseny, Irina V. Pustokhina · 8 authors
In present digital era, an exponential increase in Internet of Things (IoT) devices poses several design issues for business concerning security and privacy. Earlier studies indicate that the blockchain technology is found to be a significant solution to resolve the challenges of data security exist in IoT. In this view, this paper presents a new privacy-preserving Secure Ant Colony optimization with Multi Kernel Support Vector Machine (ACOMKSVM) with Elliptical Curve cryptosystem (ECC) for secure and reliable IoT data sharing. This program uses blockchain to ensure protection and integrity of some data while it has the technology to create secure ACOMKSVM training algorithms in partial views of IoT data, collected from various data providers. Then, ECC is used to create effective and accurate privacy that protects ACOMKSVM secure learning process. In this study, the authors deployed blockchain technique to create a secure and reliable data exchange platform across multiple data providers, where IoT data is encrypted and recorded in a distributed ledger. The security analysis showed that the specific data ensures confidentiality of critical data from each data provider and protects the parameters of the ACOMKSVM model for data analysts. To examine the performance of the proposed method, it is tested against two benchmark dataset such as Breast Cancer Wisconsin Data Set (BCWD) and Heart Disease Data Set (HDD) from UCI AI repository. The simulation outcome indicated that the ACOMKSVM model has outperformed all the compared methods under several aspects.
Open access
Blockchain Technology Applications and Security
Privacy-Preserving Technologies in Data
Advanced Steganography and Watermarking Techniques
With the rise in popularity of cryptocurrencies, distributed ledger technology is a term that has gained traction. The aim of this study is to review and comparethe distributed ledger technologies blockchain and directed acyclic graph, examining their internal structures as well as some platforms and existing areas of application. An implementation, the goal of which is to illustrate the components of a possible distributed ledger solution and how they might interact, has been made in the form of a smart contract deployed on a simulated distributed ledger network. To give some explanation to the foundations of distributed ledger technology, a brief overview is given on the topics of cryptography, underlying data structures, and the frameworks used in this study. The literature study has been conducted by collecting and reviewing primarily scientific articles on the topic of distributed ledger technologies and consensus algorithms, as well as white papers on selected distributed ledger platforms. The construction has been done using the framework Hyperledger Fabric. The result chapter reviews how the implemented smart contract fulfills the concrete goals. The study is concluded with a discussion regarding how distributed ledgers might possibly be used in thef uture, what might be done to further develop the implemented smart contract and some of the ethical concerns surrounding distributed ledger technology.
As a kind of point-to-point distributed public ledger technology, blockchain has been widely concerned in recent years. The privacy protection of blockchain technology has always been the core issue of people's attention. In this paper, some existing solutions to the current problems of user identity and transaction privacy protection are surveyed, including coin mixing mechanism, zero knowledge proof, ring signature and other technologies. Secondly, five typical applications of privacy protection technology based on blockchain are proposed and analyzed, which are mainly divided into technology applications based on coin mixing protocol, encryption protocol, secure channel protocol and so on. Finally, in view of the shortages of the existing blockchain privacy protection technology, we explore future research challenges that need to be studied in order to preserve privacy in blockchain system, and looks forward to the future development direction.
The distributed ledger technology has been widely hailed as the break-through technology. It has realised a great number of application scenarios, and improved workflow of many domains. Nonetheless, there remain a few major concerns in adopting and deploying the distributed ledger technology at scale. In this white paper, we tackle two of them, namely the throughput scalability and confidentiality protection for transactions. We learn from the existing body of research, and build a scale-out blockchain platform that champions privacy called RVChain. RVChain takes advantage of trusted execution environment to offer confidentiality protection for transactions, and scales the throughput of the network in proportion with the number of network participants by supporting parallel shadow chains.
Many recent social media posts and news may create a perception of big success in the use of blockchain for the real estate industry, land registration and protection of titles and property rights. A sobering outlook is crucial because misleading concepts may bury the whole idea of blockchain use. The paper aims to research the possibilities of blockchain and other distributed ledger technologies (DLT) and applicability of these technologies for different purposes in real estate, property rights and public registries. Blockchain, which is distinguished from permissioned systems as the technology of the immutable ledger that does not require authorities, is a new word in governance. However, this technology has some principal features that can restrain its implementation at the state level, and thus require further research and development. The application of blockchain requires a proper architecture of overlaid technologies to support changes of outdated and mistaken data, address issues of digital identity and privacy, legal compliance and enforceability of smart contracts and scalability of the ledger. This paper shows the constraints of the technology's properties which were not explained before in the context of title rights and land registration even though technological limits are known in more specific technical sources. Along with the known benefits this meant to help to avoid misinterpretation of some DLT features by non-technical people. A multidisciplinary approach in analysing the technology and laws helped to better understand what can and cannot be beneficial for public registries and the protection of property rights. The presented outcomes can be laid down as requirements for the technical protocols aimed at addressing the issues of DLT and public policies to put blockchain at the service of society.