Edge intelligence is a key enabler for IIoT as it offers smart cloud services in close proximity to the production environment with low latency and less cost. The need for ubiquitous communication, computing, and caching resources in 5G beyond will lead to a growing demand to integrate heterogeneous resources into the edge network. Furthermore, distributed edge services can make resource transactions vulnerable to malicious nodes. Ensuring secure edge services under complex industrial networks is a big challenge. In this article, we present an edge intelligence and blockchain empowered IIoT framework, which achieves flexible and secure edge service management. Then we propose a cross-domain sharing inspired edge resource scheduling scheme and design a credit-differentiated edge transaction approval mechanism. Numerical results indicate that the proposed schemes bring significant improvement in both edge service cost and service capacities.
In recent years, multi-party computation (MPC) frameworks based on replicated secret sharing schemes (RSSS) have attracted the attention as a method to achieve high efficiency among known MPCs. However, the RSSS-based MPCs are still inefficient for several heavy computations like algebraic operations, as they require a large amount and number of communication proportional to the number of multiplications in the operations (which is not the case with other secret sharing-based MPCs). In this paper, we propose RSSS-based three-party computation protocols for modular exponentiation, which is one of the most popular algebraic operations, on the case where the base is public and the exponent is private. Our proposed schemes are simple and efficient in both of the asymptotic and practical sense. On the asymptotic efficiency, the proposed schemes require O(n)-bit communication and O(1) rounds,where n is the secret-value size, in the best setting, whereas the previous scheme requires O(n2)-bit communication and O(n) rounds. On the practical efficiency, we show the performance of our protocol by experiments on the scenario for distributed signatures, which is useful for secure key management on the distributed environment (e.g., distributed ledgers). As one of the cases, our implementation performs a modular exponentiation on a 3,072-bit discrete-log group and 256-bit exponent with roughly 300ms, which is an acceptable parameter for 128-bit security, even in the WAN setting.
The emerging blockchain technology has enabled various decentralised applications in a trustless environment without relying on a trusted intermediary. It is expected as a promising solution to tackle sophisticated challenges on personal data management, thanks to its advanced features such as immutability, decentralisation and transparency. Although certain approaches have been proposed to address technical difficulties in personal data management; most of them only provided preliminary methodological exploration. Alarmingly, when utilising Blockchain for developing a personal data management system, fictions have occurred in existing approaches and been promulgated in the literature. Such fictions are theoretically doable; however, by thoroughly breaking down consensus protocols and transaction validation processes, we clarify that such existing approaches are either impractical or highly inefficient due to the natural limitations of the blockchain and Smart Contracts technologies. This encourages us to propose a feasible solution in which such fictions are reduced by designing a novel system architecture with a blockchain-based "proof of permission" protocol. We demonstrate the feasibility and efficiency of the proposed models by implementing a clinical data sharing service built on top of a public blockchain platform. We believe that our research resolves existing ambiguity and take a step further on providing a practically feasible solution for decentralised personal data management.
As the great prevalence of various Internet of Things (IoT) terminals, how to solve the problem of isolated information among different IoT platforms attracts attention from both academia and industry. It is necessary to establish a trusted access system to achieve secure authentication and collaborative sharing. Therefore, this article proposes a distributed and trusted authentication system based on blockchain and edge computing, aiming to improve authentication efficiency. This system consists of physical network layer, blockchain edge layer and blockchain network layer. Through the blockchain network, an optimized practical Byzantine fault tolerance consensus algorithm is designed to construct a consortium blockchain for storing authentication data and logs. It guarantees trusted authentication and achieves activity traceability of terminals. Furthermore, edge computing is applied in blockchain edge nodes, to provide name resolution and edge authentication service based on smart contracts. Meanwhile, an asymmetric cryptography is designed, to prevent connection between nodes and terminals from being attacked. And a caching strategy based on edge computing is proposed to improve hit ratio. Our proposed authentication mechanism is evaluated with respect to communication and computation costs. Simulation results show that the caching strategy outperforms existing edge computing strategies by 6%-12% in terms of average delay, and 8%-14% in hit ratio.
Democratic principles demand that every voter should be able to individually verify that their vote is recorded as intended and counted as recorded, without having to trust any authorities. However, most end-to-end (E2E) verifiable voting protocols that provide universal verifiability and voter secrecy implicitly require to trust some authorities or auditors for the correctness guarantees that they provide.
In this paper, we explore the notion of individual verifiability. We evaluate the existing E2E voting protocols and propose a new protocol that guarantees such verifiability without any trust requirements. Our construction depends on a novel vote commitment scheme to capture voter intent that allows voters to obtain a direct zero-knowledge proof of their vote being recorded as intended. We also ensure protection against spurious vote injection or deletion post eligibility verification, and polling-booth level community profiling.
Providing a 360° view of a given data item especially for sensitive data is essential toward not only protecting the data and associated privacy but also assuring trust, compliance, and ethics of the systems that use or manage such data. With the advent of General Data Protection Regulation, California Data Privacy Law, and other such regulatory requirements, it is essential to support data transparency in all such dimensions. Moreover, data transparency should not violate privacy and security requirements. In this article, we put forward a vision for how data transparency would be achieved in a de-centralized fashion using blockchain technology.
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
\n\t\t\t\t\tBlockchain technology with its secure, transparent and decentralized nature has been recently employed in many mobile applications. However, the process of executing extensive tasks such as computation-intensive data applications and blockchain mining requires high computational and storage capability of mobile devices, which would hinder blockchain applications in mobile systems. To meet this challenge, we propose a mobile edge computing (MEC) based blockchain network where multi-mobile users (MUs) act as miners to offload their data processing tasks and mining tasks to a nearby MEC server via wireless channels. Specially, we formulate task offloading, user privacy preservation and mining profit as a joint optimization problem which is modelled as a Markov decision process, where our objective is to minimize the long-term system offloading utility and maximize the privacy levels for all blockchain users. We first propose a reinforcement learning (RL)-based offloading scheme which enables MUs to make optimal offloading decisions based on blockchain transaction states, wireless channel qualities between MUs and MEC server and user’s power hash states. To further improve the offloading performances for larger-scale blockchain scenarios, we then develop a deep RL algorithm by using deep Q-network which can efficiently solve large state space without any prior knowledge of the system dynamics. Experiment and simulation results show that the proposed RL-based offloading schemes significantly enhance user privacy, and reduce the energy consumption as well as computation latency with minimum offloading costs in comparison with the benchmark offloading schemes.\n\t\t\t\t
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
For current and future Internet of Things (IoT) networks, mobile edge-cloud computation offloading (MECCO) has been regarded as a promising means to support delay-sensitive IoT applications. However, offloading mobile tasks to the cloud gives rise to new security issues due to malicious mobile devices (MDs). How to implement offloading to alleviate computation burdens at MDs while guaranteeing high security in mobile edge cloud is a challenging problem. In this paper, we investigate simultaneously the security and computation offloading problems in a multi-user MECCO system with blockchain. First, to improve the offloading security, we propose a trustworthy access control mechanism using blockchain, which can protect cloud resources against illegal offloading behaviours. Then, to tackle the computation management of the authorized MDs, we formulate a computation offloading problem by jointly optimizing the offloading decisions, the allocation of computing resource and radio bandwidth, and smart contract usage. This optimization problem aims to minimize the long-term system costs of latency, energy consumption and smart contract fee among all MDs. To solve the proposed offloading problem, we develop an advanced deep reinforcement learning algorithm using a double-dueling Q-network. Evaluation results from real experiments and numerical simulations demonstrate the significant advantages of our scheme over the existing approaches.
Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne
For current and future Internet of Things (IoT) networks, mobile edge-cloud\ncomputation offloading (MECCO) has been regarded as a promising means to\nsupport delay-sensitive IoT applications. However, offloading mobile tasks to\nthe cloud is vulnerable to security issues due to malicious mobile devices\n(MDs). How to implement offloading to alleviate computation burdens at MDs\nwhile guaranteeing high security in mobile edge cloud is a challenging problem.\nIn this paper, we investigate simultaneously the security and computation\noffloading problems in a multi-user MECCO system with blockchain. First, to\nimprove the offloading security, we propose a trustworthy access control using\nblockchain, which can protect cloud resources against illegal offloading\nbehaviours. Then, to tackle the computation management of authorized MDs, we\nformulate a computation offloading problem by jointly optimizing the offloading\ndecisions, the allocation of computing resource and radio bandwidth, and smart\ncontract usage. This optimization problem aims to minimize the long-term system\ncosts of latency, energy consumption and smart contract fee among all MDs. To\nsolve the proposed offloading problem, we develop an advanced deep\nreinforcement learning algorithm using a double-dueling Q-network. Evaluation\nresults from real experiments and numerical simulations demonstrate the\nsignificant advantages of our scheme over existing approaches.\n
Domenico Rotondi, Marco Saltarella, Gaetano Giordano, Francesco Pellecchia
Abstract Compliance of distributed ledger technology (DLT) based solutions with the European Union General Data Protection Regulation (EU GDPR) is currently a hot topic both from a technical point of view, as well as from a legal and normative one. Flexible working is a new working model where employees can perform their work activity without specific time and space constraints. In this context privacy and information trustworthiness are relevant and, therefore, on the one hand it can gain benefit from using DLT based solutions, on the other hand it must comply with the GDPR. This paper describes a solution that combines DLTs and the new Ciphertext‐Policy Attribute Based Encryption cryptographic techniques to support compliance with the EU GDPR in the context of flexible working. The devised solution is being concretely experimented, in the context of the EU H2020 CITADEL project, by the Municipality of Bari (Italy).
Francesco Buccafurri, Vincenzo De Angelis, Gianluca Lax, Lorenzo Musarella · 5 authors
The main benefit of smart contracts over Ethereum is that different parties with conflicting interests can exchange value without trusting each other. As a matter of fact, solutions in which service delivery is regulated by smart contracts are proliferating. Sometimes, services can be negotiated and delivered only on the basis of some attributes, without disclosing the identity of the customer to the service supplier. However, accountability is still required, so that, in case of need, the identity of the customer should be linked to the service delivered and communicated to the appropriate parties. In this paper, we propose a practical solution to the above problem that integrates the features of Ethereum with a (Ciphertext-Policy) Attribute-Based Encryption scheme. To show the effectiveness of our proposal, we instantiate the general model to a significant use case.
Loïc Lesavre, Priam Varin, Peter Mell, Michael L. Davidson · 5 authors
Identity management systems (IDMSs) are widely used to provision user identities while managing authentication, authorization, and data sharing within organizations and on the web. Traditional identity systems typically suffer from single points of failure, lack of interoperability, and privacy issues, such as enabling mass data collection and user tracking. Blockchain technology has the potential to alleviate these concerns: it can support the ability for users to control the custody of their own identifiers and credentials, enabling novel data ownership and governance models with built-in control and consent mechanisms. Hence, blockchain-based IDMSs, which could benefit both users and businesses, are beginning to proliferate. This work categorizes these systems into a taxonomy based on differences in blockchain architectures, governance models, and other salient features. Context is provided for the taxonomy through the description of related terms, emerging standards, and use cases while highlighting relevant security and privacy considerations.
An exemplary paradigm of how an AI can be a disruptive technological paragon via the utilization of blockchain comes straight from the world of deep learning. Data scientists have long struggled to maintain the quality of a dataset for machine learning by an AI entity. Datasets can be very expensive to purchase, as, depending on both the proper selection of the elements and the homogeneity of the data contained within, constructing and maintaining the integrity of a dataset is difficult. Blockchain as a highly secure storage medium presents a technological quantum leap in maintaining data integrity. Furthermore, blockchain’s immutability constructs a fruitful environment for creating high quality, permanent and growing datasets for deep learning. The combination of AI and blockchain could impact fields like Internet of things (IoT), identity, financial markets, civil governance, smart cities, small communities, supply chains, personalized medicine and other fields, and thereby deliver benefits to many people.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
In this paper, we propose an anonymous English auction scheme that utilizes trusted hardware and blockchain for the enhancement of the privacy of the bidders and the correctness of the auction. We use group signature to provide anonymity to the bidders. The hardware-based trusted execution environment (TEE) is utilized to ensure that the group manager de-anonymizes a group member only once for identifying the winner. To incorporate this idea, the blockchain transactions are signed using a group signature scheme instead of an ordinary signature scheme.
Data trading has become a promising way to bridge numerous data islands and benefit a wide range of data driven applications. However, due to the high risk of data privacy, the easy-to-copy feature of data, and potential malicious behaviors of users, there still lacks data trading solutions to provide privacy protection, copyright/ownership protection and auditability of user behaviors. In this work, we propose a blockchain and smart contract based framework to keep tamper-proof records of data trading transactions, which also preserves users' identity, behavior and data privacy. Data fingerprint is introduced to track data and protect data ownership. A set of protocols are also designed to prevent dishonest behaviors and ensure the security of data trading.
Blockchain technology provides a distributed solution, but not privacy of data used. Data privacy is included with the help of secure multiparty computation protocols and which in turn increases the complexity of application. This paper provides an efficient solution for blockchain technology with privacy by including a novel optimization for secure computation protocols.
Aug 1, 2019·2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
Shihan Bao, Ao Lei, Haitham Cruickshank, Zhili Sun · 6 authors
Research into the established area of ITS is evolving into the Internet of Vehicles (IoV), itself a fast-moving research area, fuelled in part by rapid changes in computing and communication technologies. Using pseudonym certificate is a popular way to address privacy issues in IoV. Therefore, the certificate management scheme is considered as a feasible technique to manage system and maintain the lifecycle of certificate. In this paper, we propose an efficient pseudonym certificate management scheme in IoV. The Blockchain concept is introduced to simplify the network structure and distributed maintenance of the Certificate Revocation List (CRL). The proposed scheme embeds part of the certificate revocation functions within the security and privacy applications, aiming to reduce the communication overhead and shorten the processing time cost. Extensive simulations and analysis show the effectiveness and efficiency of the proposed scheme, in which the Blockchain structure costs fewer network resources and gives a more economic solution to against further cybercrime attacks.
Blockchain and the European General Data Protection Regulation (GDPR) are two topics that are currently highly discussed in academia and amongst professionals. The Blockchain technology is claimed to revolutionize how business is being conducted by its way of storing data and sharing it with others. The recently introduced GDPR has a huge impact on processing personal data because it brought major changes to privacy regulation. This might also affect the processing of personal data in Blockchain-based application scenarios. Based on literature analysis, the paper at hand provides an overview of the Blockchain technology, presents a decision model, and introduces two possible Blockchain application scenarios. It analyses relevant requirements of the GDPR in view of processing personal data and compares these with the fundamental principles of the Blockchain technology. The paper concludes that processing personal data in the Blockchain is violating the GDPR because it conflicts with fundamental specification of this regulation. This finding reveals the need for further research to propose concepts and frameworks for a GDPR-compliant processing of personal data using Blockchain technology.
Participants can complete tasks on crowdsensing platform with smart mobile devices. They go to specific locations to collect data and upload them. Then, the platform pays them some rewards. However, most of the existing crowdsensing platforms are deployed on centralized servers, which are vulnerable to attack, intrusion, and manipulation. In addition, the location information in task records increases the potential risk of privacy leakage. To reach a balance between privacy protection and functional availability of the system. We design and implement Crowdchain, which is a location preserve anonymous payment system based on a permissioned blockchain. In order to disassociate participants identity information from task records, Crowdchain contains a novel protocol that makes participants transfer wallet address to payment system bypass the crowdsensing platform and receive task rewards correctly. We prove the security of our anonymous payment system by zero-knowledge proof and give the analysis result of system stability.
Through decentralized ledger, Bitcoin rebuilds trust and achieves payment verification. However, the verification of Bitcoin transactions requires nodes to download the whole blockchain, which is infeasible for resource-constraint devices. Traditional schemes tried to transfer most of the storage and computation tasks from a lightweight client to a full node. Nevertheless, these schemes would severely violate users' privacy since they would leak transaction ID and public-key address when a lightweight client queries the full node. To address this, we propose a privacy-preserving approach to secure queries of simplified payment verification (SPV) clients. Specifically, we design a d-differentially private mechanism based on trusted hardware such that semi-honest adversaries cannot acquire the real access pattern during shards retrieval phase. Data-oblivious primitives are adopted to prevent the internal search pattern leakage owing to side-channel attacks. Our scheme is more secure than traditional SPV schemes, and it is proved to satisfy d-differential privacy definition. Our prototype implementation with the Bitcoin blockchain dataset shows its practicality.
Hasan Al-Aswad, Hesham Hasan, Wael Elmedany, Mazen Ali · 5 authors
Blockchain-based applications cover numerous fields from financial services to the Internet of Things (IoT). The smart contracts which are the programmable blocks that execute predefined command are executed on participating nodes. Such execution leads to privacy and confidentiality issues as nodes process data to execute the smart contracts. A zero-knowledge proof is used in cryptocurrencies for allowing spending digital money without revealing the identity of persons. In this paper, we aim to introduce a zero-knowledge proof model using blockchain to enable sharing data securely between services and devices without affecting the confidentiality or privacy of data. The security model fuses digital assets within a blockchain and serves as a trustless layer for protecting the data, which results in enhancing the security of data sharing. We apply the model to two recently introduced concepts in Bahrain: The National Healthcare Insurance Scheme and government-collected VAT. Applying the model for exchanging medical data and sharing medical records between the private sector and public sector will enable maintaining the privacy of patients and increasing efficiency of operations. For VAT, the model helps secure the overall process of VAT reporting and B2B transactional processes in general.