Muhammad Habib ur Rehman, Ahmed Mukhtar Dirir, Khaled Salah, Ernesto Damiani · 5 authors
Cross-device federated learning (CDFL) systems enable fully decentralized training networks whereby each participating device can act as a model-owner and a model-producer. CDFL systems need to ensure fairness, trustworthiness, and high-quality model availability across all the participants in the underlying training networks. This article presents a blockchain-based framework, TrustFed, for CDFL systems to detect the model poisoning attacks, enable fair training settings, and maintain the participating devices' reputation. TrustFed provides fairness by detecting and removing the attackers from the training distributions. It uses blockchain smart contracts to maintain participating devices' reputations to compel the participants in bringing active and honest model contributions. We implemented the TrustFed using a Python-simulated federated learning framework, blockchain smart contracts, and statistical outlier detection techniques. We tested it over the large-scale industrial Internet of things dataset and multiple attack models. We found that TrustFed produces better results regarding multiple aspects compared with the conventional baseline approaches.
Digital evidence, such as evidence from CCTV and event data recorders, is highly valuable in criminal investigations, and is used as definitive evidence in trials. However, there are risks when digital evidence obtained during the investigation of a case is managed through a physical hard disk drive until it is submitted to the court. Previous studies have focused on the integrated management of digital evidence in a centralized system, but if a centralized system server is attacked, major operations and investigation information may be leaked. Therefore, there is a need to reliably manage digital evidence and investigation information using blockchain technology in a distributed system environment. However, when large amounts of data-such as evidence videos-are stored in a blockchain, the data that must be processed only within one block before being created increase, causing performance degradation. Therefore, we propose a two-level blockchain system that separates digital evidence into hot and cold blockchains. In the criminal investigation process, information that frequently changes is stored in the hot blockchain, and unchanging data such as videos are stored in the cold blockchain. To evaluate the system, we measured the storage and inquiry processing performance of digital crime evidence videos according to the different capacities in the two-level blockchain system.
Safa Otoum, Ismaeel Al Ridhawi, Hussein T. Mouftah
The COVID-19 pandemic, which spread rapidly in late 2019, has revealed that the use of computing and communication technologies provides significant aid in preventing, controlling, and combating infectious diseases. With the ongoing research in next-generation networking (NGN), the use of secure and reliable communication and networking is of utmost importance when dealing with users' health records and other sensitive information. Through the adaptation of Artificial Intelligence (AI)-enabled NGN, the shape of healthcare systems can be altered to achieve smart and secure healthcare capable of coping with epidemics that may emerge at any given moment. In this article, we envision a cooperative and distributed healthcare framework that relies on state-of-the-art computing, communication, and intelligence capabilities, namely, Federated Learning (FL), mobile edge computing (MEC), and Blockchain, to enable epidemic (or suspicious infectious disease) discovery, remote monitoring, and fast health-authority response. The introduced framework can also enable secure medical data exchange at the edge and between different health entities. Such a technique, coupled with the low latency and high bandwidth functionality of 5G and beyond networks, would enable mass surveillance, monitoring and analysis to occur at the edge. Challenges, issues, and design guidelines are also discussed in this article with highlights on some trending solutions.
Alexandre Siqueira, Arlindo Flavio Da Conceição, Vladimir Rocha
Self-Sovereign Identity (SSI), a Blockchain-based technology for digital\nidentity management, is a promising concept for handling health data. It could\nrepresent a step forward in empowering users, granting them control over their\ndata. This work conducts a systematic literature review to investigate\nstate-of-the-art measures based on SSI and Blockchain technologies for dealing\nwith electronic health records (EHRs), identifying gaps, and determining the\nkey questions for future research. As a result, this review shows a growing\ninterest in Blockchain methods to handle EHRs, but few works consider using the\nself-sovereign identity approaches. The results obtained in this work also\nsuggest that: Blockchain technologies provide a viable alternative to deliver\nEHR solutions such as patient monitoring, healthcare data trading, and\nprescription control; consolidated Blockchain technologies are the preferred\ncore components of most effective strategies; keeping raw health data off-chain\nhelps to create scalable solutions; health data standards make searching\nmedical records in Blockchain structures feasible; Smart Contracts are\nessential components of Blockchain-based EHR solutions; the concepts of data\nownership and Self-Sovereign Identity have been neither adequately defined nor\nemployed in the health context.\n
With the deployment of fifth-generation (5G) wireless networks worldwide, research on sixth-generation (6G) wireless communications has commenced. It is expected that 6G networks can accommodate numerous heterogeneous devices and infrastructures with enhanced efficiency and security over diverse, e.g. spectrum, computing and storage, resources. However, this goal is impeded by a number of trust-related issues that are often neglected in network designs. Blockchain, as an innovative and revolutionary technology that has arisen in the recent decade, provides a promising solution. Building on its nature of decentralization, transparency, anonymity, immutability, traceability and resiliency, blockchain can establish cooperative trust among separate network entities and facilitate, e.g. efficient resource sharing, trusted data interaction, secure access control, privacy protection, and tracing, certification and supervision functionalities for wireless networks, thus presenting a new paradigm towards 6G. This paper is dedicated to blockchain-enabled wireless communication technologies. We first provide a brief introduction to the fundamentals of blockchain, and then we conduct a comprehensive investigation of the most recent efforts in incorporating blockchain into wireless communications from several aspects. Importantly, we further propose a unified framework of the blockchain radio access network (B-RAN) as a trustworthy and secure paradigm for 6G networking by utilizing blockchain technologies with enhanced efficiency and security. The critical elements of B-RAN, such as consensus mechanisms, smart contract, trustworthy access, mathematical modeling, cross-network sharing, data tracking and auditing and intelligent networking, are elaborated. We also provide the prototype design of B-RAN along with the latest experimental results.
Xianjia Yu, Jorge Peña Queralta, Jukka Heikkonen, Tomi Westerlund
Autonomous systems are becoming inherently ubiquitous with the advancements of computing and communication solutions enabling low-latency offloading and real-time collaboration of distributed devices. Decentralized technologies with blockchain and distributed ledger technologies (DLTs) are playing a key role. At the same time, advances in deep learning (DL) have significantly raised the degree of autonomy and level of intelligence of robotic and autonomous systems. While these technological revolutions were taking place, raising concerns in terms of data security and end-user privacy has become an inescapable research consideration. Federated learning (FL) is a promising solution to privacy-preserving DL at the edge, with an inherently distributed nature by learning on isolated data islands and communicating only model updates. However, FL by itself does not provide the levels of security and robustness required by today's standards in distributed autonomous systems. This survey covers applications of FL to autonomous robots, analyzes the role of DLT and FL for these systems, and introduces the key background concepts and considerations in current research.
Cryptocurrencies have received a lot of research attention in recent years following the release of the first cryp-tocurrency Bitcoin. With the rise in cryptocurrency transactions, the need for smart contracts has also increased. Smart contracts, in a nutshell, are digitally executed contracts wherein some parties execute a common goal. The main problem with most of the current smart contracts is that there is no privacy for a party's input to the contract from either the blockchain or the other parties. Our research builds on the Hawk project that provides transaction privacy along with support for smart contracts. However, Hawk relies on a special trusted party known as a manager, which must be trusted not to leak each party's input to the smart contract. In this paper, we present a practical private smart contract protocol that replaces the manager with an MPC protocol such that the function to be executed by the MPC protocol is relatively lightweight, involving little overhead added to the smart contract function, and uses practical sigma protocols and homomorphic commitments to prove to the blockchain that the sum of the incoming balances to the smart contract matches the sum of the outgoing balances. An extended version of the paper is available at [1].
In recent years we have witnessed a dramatic increase in the applications of blockchain and smart contracts in a variety of contexts, including supply-chain, decentralized finance, and international money transfers. However, a critical stumbling block to their further adoption is smart contract security (or more precisely, the lack thereof). Smart contracts, once deployed on a blockchain, are immutable. Hence, unlike traditional software systems, smart contracts are particularly vulnerable to latent security issues. It is therefore imperative that security analysis tools be developed that help improve smart contract security if they are to have continued adoption and impact. A particularly widespread class of security vulnerabilities that afflicts Ethereum smart contracts is the gas-based denial of service (DoS). Briefly, these vulnerabilities generally present in contracts containing unbounded loops. \n \nTo address the described problem, we present Gas Gauge, a tool aimed at detecting gas-based DoS vulnerabilities in Ethereum smart contracts. Gas Gauge consists of three major components: the Detection Phase, Identification Phase, and Correction Phase. First, we describe a highly accurate static analysis approach that finds all the loops in a smart contract (the Detection Phase). Then, a set of inputs that causes the contract to run out of gas is generated using a fuzzing approach. The last component uses static analysis and run-time verification to predict the maximum loop bounds consistent with allowable gas usage automatically. This component uses a binary search approach and an independent parallel processing design to speed up the process. Each part of the tool can be used separately for different purposes or all together to detect, identify and help repair the contracts vulnerable to out-of-gas behaviors. \n \nGas Gauge was tested on 2,000 real-world solidity smart contracts. The results were compared to seven state-of-the-art tools, and it was empirically demonstrated that Gas Gauge is highly effective and useful.
Edge computing (EC) has recently emerged as a novel computing paradigm that offers users low-latency services. Suffering from constrained computing resources due to their limited physical sizes, edge servers cannot always handle all the incoming computation tasks timely when they operate independently. They often need to cooperate through peer-offloading. Deployed and managed by different stakeholders, edge servers operate in a distrusted environment. Trust and incentive are the two main issues that challenge cooperative computing between them. Another unique challenge in the EC environment is to facilitate trust and incentive in a decentralized manner. To tackle these challenges systematically, this paper proposes CoopEdge, a novel blockchain-based decentralized platform, to drive and support cooperative edge computing. On CoopEdge, an edge server can publish a computation task for other edge servers to contend for. A winner is selected from candidate edge servers based on their reputations. After that, a consensus is reached among edge servers to record the performance in task execution on blockchain. We implement CoopEdge based on Hyperledger Sawtooth and evaluate it experimentally against a baseline and two state-of-the-art implementations in a simulated EC environment. The results validate the usefulness of CoopEdge and demonstrate its performance.
Matthew Tsao, Kaidi Yang, Stephen Zoepf, Marco Pavone
The era of big data has brought with it a richer understanding of user behavior through massive datasets, which can help organizations optimize the quality of their services. In the context of transportation research, mobility data can provide municipal authorities (MAs) with insights on how to operate, regulate, or improve the transportation network. Mobility data, however, may contain sensitive information about end users and trade secrets of mobility providers (MPs). Due to this data privacy concern, MPs may be reluctant to contribute their datasets to MA. Using ideas from cryptography, we propose an interactive protocol between an MA and an MP, in which MA obtains insights from mobility data without MP having to reveal its trade secrets or sensitive data of its users. This is accomplished in two steps: 1) a commitment step and 2) a computation step. In the first step, Merkle commitments and aggregated traffic measurements are used to generate a cryptographic commitment. In the second step, MP extracts insights from the data and sends them to MA. Using the commitment and zero-knowledge proofs, MA can certify that the information received from MP is accurate, without needing to directly inspect the mobility data. We also present a differentially private version of the protocol that is suitable for the large query regime. The protocol is verifiable for both MA and MP in the sense that dishonesty from one party can be detected by the other. The protocol can be readily extended to the more general setting with multiple MPs via secure multiparty computation.
This PhD thesis focuses on lattice-based cryptography and how to apply it to build post-quantum online voting systems. It is the result of the research done by the author at Scytl in close collaboration with Dr. Paz Morillo, from the Department of Applied Mathematics at UPC and Ramiro Martínez, PhD student. As part of her work at the electronic voting company Scytl, the author has participated in the design of several electronic voting systems as well as in their implementation, by providing support to the development team. Nevertheless, all these systems use standard and well-known cryptographic primitives, i.e., not lattice-based primitives, to ensure that the security requirements are fulfilled. Due to this, one of the main challenges of this PhD has been to start researching on a field which was not familiar to the author and contribute to its state of the art. This has allowed the company to enter the post-quantum world by participating in a project which aims to implement a lattice-based online voting system. The thesis has the following contents: an introduction to the lattice theory by describing some of its basic concepts and the computational problems in which the security of lattice-based cryptosystems relies. In this first part it is also described in detail those cryptosystems that are used as building blocks of three new protocols proposed in the thesis: a lattice-based coercion-resistant cast-as-intended protocol, a post-quantum mix-net and a fully post-quantum proof of a shuffle. The former is the lattice version of an existing protocol and allows the voter to check that the vote cast contains the selected voting options. The second and third protocols are the result of the research on lattice-based mix-nets. Two constructions are proposed: the first one allows to demonstrate that a mix-node has permuted and re-encrypted a list of RLWE ciphertexts without modifying them, but it cannot be considered fully post-quantum since the binding property of the commitment scheme relies on classical computational problems. The second one is fully post-quantum since all the cryptographic schemes used for building it, i.e., commitment scheme and zero-knowledge proofs, are based on lattices. Last but not least, for this second proposal a security definition and a proof of security are also provided. Finally, the last part of the thesis consists of building a post-quantum online voting system using as building blocks the protocols already presented and existing lattice-based constructions. This system is considered secure under quantum attacks and provides long-term privacy. It also guarantees vote anonymity, vote authenticity, vote integrity, individual verifiability and receipt-freeness. The algorithms involved in each phase are described in detail as well as the interaction among the participants. An implementation of this system is not given as part of this thesis although a lattice-based online voting system based on that is already being implemented at the company. Aquest tesi es centra en la criptografia basada en reticles i com aplicar-la a la construcció de sistemes de votació electrònica post-quàntics. És el fruit de la recerca feta per l'autora de la tesi a Scytl en estreta col·laboració amb la Dra. Paz Morillo, del Departament de Matemàtica Aplicada de la UPC i en Ramiro Martínez, estudiant de doctorat. Com a part de la seva feina a l'empresa de vot electrònic Scytl, l'autora ha participat tant en el disseny de sistemes de votació electrònica com en la seva implementació, donant suport a l'equip de desenvolupament. No obstant, tots aquests sistemes utilitzen primitives criptogràfiques estàndard (primitives no basades en reticles) per assegurar que els requisits de seguretat es compleixen, i és per aquest motiu que un dels principals reptes d'aquest doctorat ha estat fer en recerca en un camp que no era familiar per l'autora, i contribuir-hi. Per altra banda, això ha permès a l'empresa endinsar-se en el món post-quàntic i participar en un projecte que té per objectiu implementar un sistema de vot electrònic basat en reticles. Aquest tesi consta dels següents continguts: una introducció a la teoria dels reticles on es descriuen alguns dels seus conceptes bàsics i els problemes computacionals dels quals depèn la seguretat dels criptosistemes basats en reticles. En aquesta primera part també es descriuen en detall aquells criptosistemes utilitzats en la construcció dels tres nous protocols presentats en aquesta tesi: un protocol basat en reticles resistent a la coacció i que ofereix verificabilitat “cast-as-intended”; una “mix-net post-quàntica” i una prova de coneixement nul totalment post-quàntica que permet demostrar que la barreja de vots s'ha realitzat correctament. El primer protocol és la versió basada en reticles d'un protocol ja existent i permet que el votant comprovi que el vot emès conté les opcions que havia seleccionat. El segon i el tercer protocol són el resultat de la recerca feta en el camp de les mix-nets basades en reticles. Es proposen dues construccions: la primera d'elles permet demostrar que un node de la mix-net ha barrejat i rexifrat una llista de xifrats RLWE sense modificar-los, però no es pot considerar totalment post-quàntica ja que la propietat de lligar de l'esquema de compromís utilitzat per construir la prova es basa en problemes computacionals clàssics. La segona construcció és totalment post-quàntica ja que tots els esquemes criptogràfics utilitzats en el seu disseny, és a dir, esquema de compromís i proves de coneixement nul, estan basats en reticles. Finalment, però no per això menys important, per aquesta segona proposta també es dóna una definició de seguretat i una prova de seguretat. L'última part de la tesi consisteix en construir un sistema de vot online post-quàntic, utilitzant com a components els protocols prèviament presentats i construccions ja existents basades en reticles. El sistema es considera segur en front atacs quàntics i ofereix privadesa a llarg plaç. També garanteix l'anonimat del vot, la seva autenticitat i integritat, verificabilitat individual i resistència a la coacció. Es descriuen en detall tant els algoritmes executats a cada fase com la interacció entre els seus participants. Com a part de la tesi no s'inclou cap implementació del sistema tot i que l'empresa està implementant un sistema de vot online basat en el que es presenta en aquesta tesi.
Abstract The persevering pursuit of security has proved historically limiting the implementation of significant design improvements for Electronic Health Records (EHR). Such a vital requirement for these kinds of technical development is revamped now. This is because the patients are motivated by personalization and data science to participate in the health information sharing. The implementation of cloud computing has already shown substantial benefits for both clinical organizations and patients in managing electronic health records. The prime security issue of cloud-based electronic health records is that the patient is physically unable to own a medical record whereas a clinical organization can maintain one for them. The latter may collude with centralized cloud servers. So, there is a vulnerability of such records being tampered with in order to hide the medical malpractices. So, maintaining data integrity and data privacy becomes a significant challenge when deploying cloud computing. Therefore, in this paper, a consortium blockchain-based cloud-stored electronic health record is proposed which provides data integrity, data privacy, storage scalability, and fine-grained access control. Each process in outsourcing electronic health records to the cloud is incorporated as a transaction in a consortium ethereum blockchain through smart contracts. Through smart contracts, an attribute-based contract key is generated for the users that can decrypt the encrypted data stored in the cloud. The attribute-based contract key allows only users who are authorized to access the information ensuring data privacy and fine-grained access control. Moreover, the proposed scheme is proved to provide tamper-proof although the medical records are controlled by a group of clinical organizations.
Data marketplaces (DMs) promote the benefits of the Internet of Things (IoT) in smart cities. To facilitate the easy exchanges of real-time IoT data streams between device owners and third-party applications, it is required to provide scalable, interoperable, and secured services for large numbers of distributed IoT devices operated by different application vendors. Thanks to decentralization, immutability, and auditability, Blockchain is promising to enable a tamper-proof and trust-free framework to enhance performance and security issues in centralized DMs. However, directly integrating blockchains into large-scale IoT-based DMs still faces many limitations, such as high resource and energy demands, low transaction throughput, poor scalability, and challenges in privacy preservation. This paper introduces a novel Federated Ledgers-based Framework for Hierarchical Decentralized Data Marketplaces (Fed-DDM). In Fed-DDM, participants are divided into multiple permissioned domains given their registrations. Each domain leverages an efficient Byzantine Fault Tolerance (BFT) consensus protocol to commit transactions of a domain on a private intra-ledger. A public inter-ledger network adopts a scalable Proof-of-Work (PoW) consensus protocol to federate multiple private intra-ledger networks. We design a smart contract-enabled inter-ledger protocol to guarantee the security of the cross-domain operations on a public federated ledger without exposing sensitive privacy information from private ledgers. A proof-of-concept prototype is implemented, and the experimental results verify the feasibility of the proposed Fed-DDM solution with performance and security guarantees.
Non-interactive zero-knowledge (NIZK) proofs for chosen-ciphertext security are generally considered to give an impractical construction. An interesting recent work by Seo, Abdalla, Lee, and Park (Information Sciences, July 2019) proposed an efficient semi-generic conversion method for achieving chosen-ciphertext security based on NIZK proofs in the random oracle model. The recent work by Seo et al. demonstrated that the semi-generic conversion method transforms a one-way (OW)-secure key encapsulation mechanism (KEM) into a chosen-ciphertext secure KEM while preserving tight security reduction. This paper shows that the security analysis of the semi-generic conversion method has a flaw, which comes from the OW security condition of the underlying KEM. Without changing the conversion method, this paper presents a revised security proof under the changed conditions that (1) the underlying KEM must be chosen-plaintext secure in terms of indistinguishability and (2) an NIZK proof derived from the underlying KEM via the Fiat–Shamir transform must have the properties of zero-knowledge and simulation soundness. This work extended the security proof strategy to the case of identity-based KEM (IBKEM) and also revise the security proof for IBKEM of previous method by Seo et al. Finally, this work gives a corrected security proof by applying the new proofs to several existing (IB)KEMs.
Chiara Spadafora, Riccardo Longo, Massimiliano Sala
We propose a decentralized e-voting protocol that is coercion-resistant and vote-selling resistant, while being also completely transparent and not receipt-free. We achieve decentralization using blockchain technology. Because of the properties such as transparency, decentralization, and non-repudiation, blockchain is a fundamental technology of great interest in its own right, and it also has large potential when integrated into many other areas. We prove the security of the protocol under the standard DDH assumption on the underlying prime-order cyclic group (e.g. the group of points of an elliptic curve), as well as under standard assumptions on blockchain robustness.
Seham A. Alansari, Mahmoud M. Badr, Mohamed Mahmoud, Waleed Alasmary · 6 authors
Contact tracing is a very effective way to control the COVID-19-like pandemics. It aims to identify individuals who closely contacted an infected person during the incubation period of the virus and notify them to quarantine. However, the existing systems suffer from privacy, security, and efficiency issues. To address these limitations, in this article, we propose an efficient and privacy-preserving Blockchain-based infection control system. Instead of depending on a single authority to run the system, a group of health authorities, that form a consortium Blockchain, run our system. Using Blockchain technology not only secures our system against single point of failure and denial of service attacks, but also brings transparency because all transactions can be validated by different parties. Although contact tracing is important, it is not enough to effectively control an infection. Thus, unlike most of the existing systems that focus only on contact tracing, our system consists of three integrated subsystems, including contact tracing, public places access control, and safe-places recommendation. The access control subsystem prevents infected people from visiting public places to prevent spreading the virus, and the recommendation subsystem categorizes zones based on the infection level so that people can avoid visiting contaminated zones. Our analysis demonstrates that our system is secure and preserves the privacy of the users against identification, social graph disclosure, and tracking attacks, while thwarting false reporting (or panic) attacks. Moreover, our extensive performance evaluations demonstrate the scalability of our system (which is desirable in pandemics) due to its low communication, computation, and storage overheads.
Recent increases in security breaches and digital surveillance highlight the need for improved privacy and security, particularly over users’ personal data. Advances in cybersecurity and new legislation promise to improve data protection. Blockchain and distributed ledger technologies provide novel opportunities for protecting user data through decentralized identity and other privacy mechanisms. These systems can allow users greater sovereignty through tools that enable them to own and control their own data. Artificial intelligence provides further possibilities for enhancing system and user security, enriching data sets, and supporting improved analytical models.
Dinh C. Nguyen, Ming Ding, Quoc‐Viet Pham, Pubudu N. Pathirana · 9 authors
Mobile edge computing (MEC) has been envisioned as a promising paradigm to handle the massive volume of data generated from ubiquitous mobile devices for enabling intelligent services with the help of artificial intelligence (AI). Traditionally, AI techniques often require centralized data collection and training in a single entity, e.g., an MEC server, which is now becoming a weak point due to data privacy concerns and high data communication overheads. In this context, federated learning (FL) has been proposed to provide collaborative data training solutions, by coordinating multiple mobile devices to train a shared AI model without exposing their data, which enjoys considerable privacy enhancement. To improve the security and scalability of FL implementation, blockchain as a ledger technology is attractive for realizing decentralized FL training without the need for any central server. Particularly, the integration of FL and blockchain leads to a new paradigm, called FLchain, which potentially transforms intelligent MEC networks into decentralized, secure, and privacy-enhancing systems. This article presents an overview of the fundamental concepts and explores the opportunities of FLchain in MEC networks. We identify several main topics in FLchain design, including communication cost, resource allocation, incentive mechanism, security and privacy protection. The key solutions for FLchain design are provided, and the lessons learned as well as the outlooks are also discussed. Then, we investigate the applications of FLchain in popular MEC domains, such as edge data sharing, edge content caching and edge crowdsensing. Finally, important research challenges and future directions are also highlighted.
Guntur Dharma Putra, Volkan Dedeoglu, Salil S. Kanhere, Raja Jurdak · 5 authors
Authorization or access control limits the actions a user may perform on a computer system, based on predetermined access control policies, thus preventing access by illegitimate actors. Access control for the Internet of Things (IoT) should be tailored to take inherent IoT network scale and device resource constraints into consideration. However, common authorization systems in IoT employ conventional schemes, which suffer from overheads and centralization. Recent research trends suggest that blockchain has the potential to tackle the issues of access control in IoT. However, proposed solutions overlook the importance of building dynamic and flexible access control mechanisms. In this paper, we design a decentralized attribute-based access control mechanism with an auxiliary Trust and Reputation System (TRS) for IoT authorization. Our system progressively quantifies the trust and reputation scores of each node in the network and incorporates the scores into the access control mechanism to achieve dynamic and flexible access control. We design our system to run on a public blockchain, but we separate the storage of sensitive information, such as user's attributes, to private sidechains for privacy preservation. We implement our solution in a public Rinkeby Ethereum test-network interconnected with a lab-scale testbed. Our evaluations consider various performance metrics to highlight the applicability of our solution for IoT contexts.
Hassan Mansur Hussien, Sharifah Md Yasin, Nur Izura Udzir, Mohd Izuan Hafez Ninggal
Blockchain technology provides a tremendous opportunity to transform current personal health record (PHR) systems into a decentralised network infrastructure. However, such technology possesses some drawbacks, such as issues in privacy and storage capacity. Given its transparency and decentralised features, medical data are visible to everyone on the network and are inappropriate for certain medical applications. By contrast, storing vast medical data, such as patient medical history, laboratory tests, X-rays, and MRIs, significantly affect the repository storage of blockchain. This study bridges the gap between PHRs and blockchain technology by offloading the vast medical data into the InterPlanetary File System (IPFS) storage and establishing an enforced cryptographic authorisation and access control scheme for outsourced encrypted medical data. The access control scheme is constructed on the basis of the new lightweight cryptographic concept named smart contract-based attribute-based searchable encryption (SC-ABSE). This newly cryptographic primitive is developed by extending ciphertext-policy attribute-based encryption (CP-ABE) and searchable symmetric encryption (SSE) and by leveraging the technology of smart contracts to achieve the following: (1) efficient and secure fine-grained access control of outsourced encrypted data, (2) confidentiality of data by eliminating trusted private key generators, and (3) multikeyword searchable mechanism. Based on decisional bilinear Diffie-Hellman hardness assumptions (DBDH) and discrete logarithm (DL) problems, the rigorous security indistinguishability analysis indicates that SC-ABSE is secure against the chosen-keyword attack (CKA) and keyword secrecy (KS) in the standard model. In addition, user collusion attacks are prevented, and the tamper-proof resistance of data is ensured. Furthermore, security validation is verified by simulating a formal verification scenario using Automated Validation of Internet Security Protocols and Applications (AVISPA), thereby unveiling that SC-ABSE is resistant to man-in-the-middle (MIM) and replay attacks. The experimental analysis utilised real-world datasets to demonstrate the efficiency and utility of SC-ABSE in terms of computation overhead, storage cost and communication overhead. The proposed scheme is also designed and developed to evaluate throughput and latency transactions using a standard benchmark tool known as Caliper. Lastly, simulation results show that SC-ABSE has high throughput and low latency, with an ultimate increase in network life compared with traditional healthcare systems.
Data analytics based on the produced data from the Internet of Things (IoT) devices is expected to improve the individuals' quality of life. However, ensuring security and privacy in the IoT data aggregation process is a non-trivial task. Generally, the IoT data aggregation process is based on centralized servers. Yet, in the case of distributed approaches, it is difficult to coordinate several untrustworthy parties. Fortunately, the blockchain may provide decentralization while overcoming the trust problem. Consequently, blockchain-based IoT data aggregation may become a reasonable choice for the design of a privacy-preserving system. To this end, we propose PrivDA, a Privacy-preserving IoT Data Aggregation scheme based on the blockchain and homomorphic encryption technologies. In the proposed system, each data consumer can create a smart contract and publish both terms of service and requested IoT data. Thus, the smart contract puts together into one group potential data producers that can answer the consumer's request and chooses one aggregator, the role of which is to compute the group requested result using homomorphic computations. Therefore, group-level aggregation obfuscates IoT data, which complicates sensitive information inference from a single IoT device. Finally, we deploy the proposal on a private Ethereum blockchain and give the performance evaluation.
Lodovico Giaretta, Ioannis Savvidis, Thomas Marchioro, Šarūnas Girdzijauskas · 7 authors
We envision PDS<sup>2</sup>, a decentralized data marketplace in which consumers submit their tasks to be run within the platform, on the data of willing providers. The goal of PDS2is to ensure that users maintain full control on their data and do not compromise their privacy, while being rewarded for the value that their data generates. In order to achieve this, our marketplace architecture employs blockchain technology, privacy-preserving computation and decentralized machine learning. We then compare different potential solutions and identify the Ethereum blockchain, trusted execution environments and gossip learning as the most suitable for the implementation of PDS<sup>2</sup>. We also discuss the main open challenges that are left to tackle and possible directions for future work.
5G and beyond (B5G) networks are leading a digital revolution in telecommunication in both academia and industry. It brings new paradigms in many aspects of people's daily lives due to its advantages. However, it still leaves some issues in terms of security and privacy as challenges. Blockchain, the public database, is an alternative to the traditional centralized systems, serving as the backbone technique in many systems, including manufacturing, economics, and industry. Blockchain is promising in solving the security issues in the sense that it provides desirable properties including decentralization, transparency, immutability, and so on. In this article, we investigate typical security and privacy issues in edge intelligence in B5G networks and devise a framework to integrate blockchain with such systems, which can provide guaranteed security as well as privacy. We also illustrate several possible solutions to these security and privacy issues in edge intelligence in B5G systems based on blockchain and Ethereum to show how blockchain contributes to the coming B5G networks.
Financial Regulation is a form of compliance system that subjects financial institutions to certain requirements and restrictions. Investment Compliance is an example that involves investment restrictions and monitoring on behalf of investors. Hedge Funds differ from other traditional funds such as mutual funds because of their ability to employ complex investment and hedging techniques. These are private entities with few public disclosure requirements. This is useful in a way as the strategies used are confidential which allows financial agents to participate in the financial markets without any fear of information leakage, hence promoting liquidity. However, this is often implied as a lack of transparency. Hedge Funds are expected to produce higher returns, but sometimes investors seek a risk guarantee in addition to higher returns. However, too much transparency rules out the incentives financial entities have by participating in the first place. On the other hand, too much secrecy may give rise to malicious entities that can break the rules due to a lack of compliance. We aim to solve this problem of protecting investors while ensuring the privacy of financial bodies using zero knowledge proofs. Proofs can be visualized as a way of providing enough information to investors while the zero-knowledge property of proofs maintains the privacy of the fund manager’s strategies. We propose a protocol to address this scenario using Zokrates, a framework for verifiable computation using Zk-SNARKs on Ethereum, to encode the constraints and export the verifier. Based on our implementation and analysis, it can be concluded that zero knowledge proofs provide us with a variety of ways to develop compliance systems.