Federated learning has been widely studied and applied to various scenarios, such as financial credit, medical identification, and so on. Under these settings, federated learning protects users from exposing their private data, while cooperatively training a shared machine learning algorithm model (i.e., the global model) for a variety of realworld applications. The only data exchanged is the gradient of the model or the updated model (i.e., the local model update). However, the security of federated learning is increasingly being questioned, due to the malicious clients or central servers' constant attack on the global model or user privacy data. To address these security issues, we propose a decentralized federated learning framework based on blockchain, that is, a Block-chain-based Federated Learning framework with Committee consensus (BFLC). Without a centralized server, the framework uses blockchain for the global model storage and the local model update exchange. To enable the proposed BFLC, we also devise an innovative committee consensus mechanism, which can effectively reduce the amount of consensus computing and reduce malicious attacks. We then discuss the scalability of BFLC, including theoretical security, storage optimization, and incentives. Finally, based on a FISCO blockchain system, we perform experiments using an AlexNet model on several frameworks with a real-world dataset FEMNIST. The experimental results demonstrate the effectiveness and security of the BFLC framework.
Xun Yi, Russell Paulet, Elisa Bertino, Fang-Yu Rao
In this paper we consider the problem where a client wishes to subscribe to some product or service provided by a server, but maintain their anonymity. At the same time, the server must be able to authenticate the client as a genuine user and be able to discontinue (or revoke) the client's access if the subscription fees are not paid. Current solutions for this problem are typically constructed using some combination of blind signature or zero-knowledge proof techniques, which do not directly support client revocation (that is, revoking a user before expiry of their secret value). In this paper, we present a solution for this problem on the basis of the broadcast encryption scheme, suggested by Boneh et al., by which the server can broadcast a secret to a group of legitimate clients. Our solution allows the registered client to log into the server anonymously and also supports client revocation by the server. Our solution can be used in many applications, such as location-based queries. We formally define a model for our anonymous subscription protocol and prove the security of our solution under this model. In addition, we present experimental results from an implementation of our protocol. These experimental results demonstrate that our protocol is practical.
With the development of precise positioning technology, a growing number of location-based services (LBS) emerge. For example, visit a specific place to get the corresponding reward. This also leads to location fraud by illegal users in order to gain benefits. Thus, it is necessary to verify location certificates provided by users. However, present proof of location systems are deficient in verifying users’ location certificates while protecting users’ privacy. Users do not flexibly control their location certificates either. Based on blockchain, a kind of distributed proof of location system architecture was proposed and based on the proposed system architecture, a kind of proof of location protocol with zero-knowledge proof was proposed further. With the proposed architecture and the protocol, the proposed proof of location system allows users to freely select disclosed certificate parameters and positional accuracy according to their needs so that hierarchical location privacy protection was achieved.
Christian Killer, Bruno Rodrigues, Raphael Matile, Eder J. Scheid · 5 authors
Digitization of electoral processes depends on confident systems that produce verifiable evidence. The design and implementation of voting systems has been widely studied in prior research, bringing together expertise in many fields. Switzerland is organized in a federal, decentralized structure of independent governmental entities. Thus, its decentralized structure is a real-world example for implementing an electronic voting system, where trust is distributed among multiple authorities.
Lei Xu, Lin Chen, Zhimin Gao, Keshav Kasichainula · 7 authors
Bitcoin introduces a new type of cryptocurrency that does not rely on a central system to maintain transactions. Inspired by the success of Bitcoin, all types of alt cryptocurrencies were invented in recent years. Some of the new cryptocurrencies focus on privacy enhancement, where transaction information such as value and sender/receiver identity can be hidden, such as Zcash and Monero. However, there are few schemes to support multiple types of cryptocurrencies/assets and offer privacy enhancement at the same time. The major challenge for a multiple asset system is that it needs to support two-way assets exchange between participants besides one-way asset transfer. Thus, we propose a privacy-preserving exchange scheme, PrivateEx, which preserves the privacy of the exchange of different assets. PrivateEx utilizes zero-knowledge proof and a novel way to "lock" assets involved in the exchange to guarantee the correctness, fairness, and privacy of exchange of assets in the system. We also implement a prototype of PrivateEx and evaluate its performance to show that it is practical with modern computers.
Electronic medical records (EMRs) are extremely important for patients’ treatment, doctors’ diagnoses, and medical technology development. In recent years, the distributed healthcare blockchain system has been researched for solving the information isolated island problem in centralized healthcare service systems. However, there still exists a series of important problems such as the patients’ sensitive information security, cross-institutional data sharing, medical quality, and efficiency. In this paper, we establish a lightweight privacy-preserving mechanism for a healthcare blockchain system. First, we apply an interleaving encoder to encrypt the original EMRs. This can hide the sensitive information of EMRs to protect the patient’s privacy security. Second, a ( t , n )-threshold lightweight message sharing scheme is presented. The EMRs are mapped to n different short shares, and it can be reconstructed by at least t shares. The EMR shares rather than the original EMRs are stored in the blockchain nodes. This can guarantee high security for EMR sharing and improve the data reconstruction efficiency. Third, the indexes of the stored EMR shares are employed to generate blocks that are chained together and finally form a blockchain. The authorized data users or institutions can recover an EMR by requesting at least t shares of the EMR from the blockchain nodes. In this way, the healthcare blockchain system can not only facilitate the cross-institution sharing process, but also provide proper protections for the EMRs. The security proof and analysis indicate that the proposed scheme can protect the privacy and security of patients’ medical information. The simulation results show that our proposed scheme is more efficient than similar literature in terms of energy consumption and storage space, and the healthcare blockchain system is more stable with the proposed message sharing scheme.
Yuta Nakamura, Yuanyu Zhang, Masahiro Sasabe, Shoji Kasahara
Due to the rapid penetration of the Internet of Things (IoT) into human life, illegal access to IoT resources (e.g., data and actuators) has greatly threatened our safety. Access control, which specifies who (i.e., subjects) can access what resources (i.e., objects) under what conditions, has been recognized as an effective solution to address this issue. To cope with the distributed and trust-less nature of IoT systems, we propose a decentralized and trustworthy Capability-Based Access Control (CapBAC) scheme by using the Ethereum smart contract technology. In this scheme, a smart contract is created for each object to store and manage the capability tokens (i.e., data structures recording granted access rights) assigned to the related subjects, and also to verify the ownership and validity of the tokens for access control. Different from previous schemes which manage the tokens in units of subjects, i.e., one token per subject, our scheme manages the tokens in units of access rights or actions, i.e., one token per action. Such novel management achieves more fine-grained and flexible capability delegation and also ensures the consistency between the delegation information and the information stored in the tokens. We implemented the proposed CapBAC scheme in a locally constructed Ethereum blockchain network to demonstrate its feasibility. In addition, we measured the monetary cost of our scheme in terms of gas consumption to compare our scheme with the existing Blockchain-Enabled Decentralized Capability-Based Access Control (BlendCAC) scheme proposed by other researchers. The experimental results show that the proposed scheme outperforms the BlendCAC scheme in terms of the flexibility, granularity, and consistency of capability delegation at almost the same monetary cost.
With the rapid popularity of blockchain, decentralized human intelligence tasks (HITs) are proposed to crowdsource human knowledge without relying on vulnerable third-party platforms. However, the inherent limits of blockchain cause decentralized HITs to face a few "new" challenges. For example, the confidentiality of solicited data turns out to be the sine qua non, though it was an arguably dispensable property in the centralized setting. To ensure the "new" requirement of data privacy, existing decentralized HITs use generic zero-knowledge proof frameworks (e.g. SNARK), but scarcely perform well in practice, due to the inherently expensive cost of generality. We present a practical decentralized protocol for HITs, which also achieves the fairness between requesters and workers. At the core of our contributions, we avoid the powerful yet highly-costly generic zk-proof tools and propose a special-purpose scheme to prove the quality of encrypted data. By various non-trivial statement reformations, proving the quality of encrypted data is reduced to efficient verifiable decryption, thus making decentralized HITs practical. Along the way, we rigorously define the ideal functionality of decentralized HITs and then prove the security due to the ideal-real paradigm. We further instantiate our protocol to implement a system called Dragoon, an instance of which is deployed atop Ethereum to facilitate an image annotation task used by ImageNet. Our evaluations demonstrate its practicality: the on-chain handling cost of Dragoon is even less than the handling fee of Amazon's Mechanical Turk for the same ImageNet HIT.
Tianrui Chen, Amjad Saeed Khan, Gan Zheng, Sangarapillai Lambotharan
This letter presents a secure user offloading mechanism in heterogeneous wireless networks (HWNs), where a macrocell base station (MBS) offloads its users to small cell access points (SCAs) using Vickrey auction. Additionally, a user-in-the-loop (UIL) strategy is exploited to encourage the unserved users to move to desired locations for connections. As the participants in the conventional auction-based trading may collude or take selfish actions, we employ Ethereum framework for trustless, secure and distributed auctioning. Simulation results are presented to demonstrate the advantages of the proposed user offloading methodology. The security aspects of the blockchain framework are also discussed.
Younghun Lee, Shailendra Rathore, Jin Ho Park, Jong Hyuk Park · 6 authors
Abstract With the advancement of Information and Communication Technology (ICT) and the proliferation of sensor technologies, the Internet of Things (IoT) is now being widely used in smart home for the purposes of efficient resource management and pervasive sensing. In smart homes, various IoT devices are connected to each other, and these connections are centered on gateways. The role of gateways in the smart homes is significant, however, its centralized structure presents multiple security vulnerabilities such as integrity, certification, and availability. To address these security vulnerabilities, in this paper, we propose a blockchain-based smart home gateway network that counters possible attacks on the gateway of smart homes. The network consists of three layers including device, gateway, and cloud layers. The blockchain technology is employed at the gateway layer wherein data is stored and exchanged in the form blocks of blockchain to support decentralization and overcome the problem from traditional centralized architecture. The blockchain ensures the integrity of the data inside and outside of the smart home and provides availability through authentication and efficient communication between network members. We implemented the proposed network on the Ethereum blockchain technology and evaluated in terms of standard security measures including security response time and accuracy. The evaluation results demonstrate that the proposed security solutions outperforms over the existing solutions.
Security-related data collection is an essential part for attack detection and security measurement in Mobile Ad Hoc Networks (MANETs). Due to no fixed infrastructure of MANETs, a detection node playing as a collector should discover available routes to a collection node for data collection. Notably, route discovery suffers from many attacks (e.g., wormhole attack), thus the detection node should also collect securityrelated data during route discovery and analyze these data for determining reliable routes. However, few literatures provide incentives for security-related data collection in MANETs, and thus the detection node might not collect sufficient data, which greatly impacts the accuracy of attack detection and security measurement. In this paper, we propose B4SDC, a blockchain system for security-related data collection in MANETs. Through controlling the scale of RREQ forwarding in route discovery, the collector can constrain its payment and simultaneously make each forwarder of control information (namely RREQs and RREPs) obtain rewards as much as possible to ensure fairness. At the same time, B4SDC avoids collusion attacks with cooperative receipt reporting, and spoofing attacks by adopting a secure digital signature. Based on a novel Proof-of-Stake consensus mechanism by accumulating stakes through message forwarding, B4SDC not only provides incentives for all participating nodes, but also avoids forking and ensures high efficiency and real decentralization at the same time. We analyze B4SDC in terms of incentives and security, and evaluate its performance through simulations. The thorough analysis and experimental results show the efficacy and effectiveness of B4SDC.
Muhammad Umar Javed, Mubariz Rehman, Nadeem Javaid, Abdulaziz Aldegheishem · 6 authors
In this paper, a blockchain-based secure data sharing mechanism is proposed for Vehicular Networks (VNs). Edge service providers are introduced along with ordinary nodes to efficiently manage service provisioning. The edge service providers are placed in the neighborhood of the ordinary nodes to ensure smooth communication between them. The huge amount of data generated by smart vehicles is stored in a distributed file storage system, known as Interplanetary File System (IPFS). It is used to tackle the issues related to data storage in centralized architectures, such as data tampering, lack of privacy, vulnerability to hackers, etc. Monetary incentives are given to edge vehicle nodes to motivate them for accurate and timely service provisioning to ordinary nodes. In response, ordinary nodes give reviews to the edge nodes against the services provided by them, which are further stored in a blockchain to ensure integrity, security and transparency. Smart contracts are used to automate the system processes without the inclusion of an intermediate party and to check the reviews given to the edge nodes. To optimize gas consumption and to enhance the system performance, a Proof of Authority (PoA) consensus mechanism is used to validate the transactions. Moreover, a caching system is introduced at the edge nodes to store frequently used services. Furthermore, both security and privacy are enhanced in the proposed system by incorporating a symmetric key cryptographic mechanism. A trust management mechanism is also proposed in this work to calculate the nodes’ reputation values based upon their trust values. These values determine the authenticity of the nodes involved in the network. Eventually, it is concluded from the simulation results that the proposed system is efficient for VNs.
The Internet of Things (IoT) is experiencing explosive growth and has gained extensive attention from academia and industry in recent years. However, most of the existing IoT infrastructures are centralized, which may cause the issues of unscalability and single-point-of-failure. Consequently, decentralized IoT has been proposed by taking advantage of the emerging technology called blockchain. Voting systems are widely adopted in IoT, for example a leader election in wireless sensor networks. Self-tallying voting systems are alternatives to unsuitable, traditional centralized voting systems in decentralized IoT. Unfortunately, self-tallying voting systems inherently suffer from fairness issues, such as adaptive and abortive issues caused by malicious voters. To address these issues, in this article, we introduce a framework of the self-tallying voting system in decentralized IoT based on blockchain. We propose a concrete construction and prove that the proposed system satisfies all the security requirements, including fairness, dispute-freeness, and maximal ballot secrecy. We simulate the algorithms on a laptop, an Android phone, and a Raspberry Pi to test the time consumption and evaluate the gas cost of each algorithm in a private blockchain as well. The implementation results demonstrate the practicability of our system.
With the popularization of intelligent terminals, especially current trends, such as “Industrie 4.0” and the Internet of Things, mobile crowdsensing is becoming one of the promising applications built on smart devices in mobile networks. However, the existing mobile crowdsensing models are mostly based on a centralized platform, which is not fully trusted in reality and results in the existence of fraud and other security problems. Furthermore, the data quality collected through crowdsensing is varied, and the location privacy is difficult to guarantee, especially at the worker selection stage. To solve these two problems, an effective blockchain-based location-privacy-preserving crowdsensing model, CrowdBLPS, is proposed in this article. First, the idea of a blockchain is introduced into this model. The decentralized structure and the consensus approach are applied to realize the nonrepudiation and nontampering of information. Second, to improve the data sensing quality and protect worker privacy, a two-stage approach, including the preregistration stage and the final selection stage, is proposed. Finally, we further implement a prototype on the Ethereum public testing network, and the experimental results show the feasibility, availability, and reliability of CrowdBLPS.
A blockchain, such as Bitcoin, is an append-only, secure, transparent, distributed ledger. A fair blockchain is expected to have healthy metrics; high honest mining power, low processing latency, i.e., low wait times for transactions and stable price of consumption, i.e., the minimum transaction fee required to have a transaction processed. As Bitcoin matures, the influx of transactions increases and the block rewards become insignificant. We show that under these conditions, it becomes hard to maintain the health of the blockchain. In Bitcoin, under these mature operating conditions (MOC), the miners would find it challenging to cover their mining costs as there would be no more revenue from merely mining a block. It may cause miners not to continue mining, threatening the blockchain's security. Further, as we show in this paper using simulations, the cost of acting in favor of the health of the blockchain, under MOC, is very high in Bitcoin, causing all miners to process transactions greedily. It leads to stranded transactions, i.e., transactions offering low transaction fees, experiencing unreasonably high processing latency. To make matters worse, a compounding effect of these stranded transactions is the rising price of consumption. Such phenomena not only induce unfairness as experienced by the miners and the users but also deteriorate the health of the blockchain. We propose BitcoinF transaction processing protocol, a simple, yet highly effective modification to the existing Bitcoin protocol to fix these issues of unfairness. BitcoinF resolves these issues of unfairness while preserving the ability of the users to express urgency and have their transactions prioritized.
Youyang Qu, Longxiang Gao, Tom H. Luan, Yong Xiang · 7 authors
As the extension of cloud computing and a foundation of IoT, fog computing is experiencing fast prosperity because of its potential to mitigate some troublesome issues, such as network congestion, latency, and local autonomy. However, privacy issues and the subsequent inefficiency are dragging down the performances of fog computing. The majority of existing works hardly consider a reasonable balance between them while suffering from poisoning attacks. To address the aforementioned issues, we propose a novel blockchain-enabled federated learning (FL-Block) scheme to close the gap. FL-Block allows local learning updates of end devices exchanges with a blockchain-based global learning model, which is verified by miners. Built upon this, FL-Block enables the autonomous machine learning without any centralized authority to maintain the global model and coordinates by using a Proof-of-Work consensus mechanism of the blockchain. Furthermore, we analyze the latency performance of FL-Block and further derive the optimal block generation rate by taking communication, consensus delays, and computation cost into consideration. Extensive evaluation results show the superior performances of FL-Block from the aspects of privacy protection, efficiency, and resistance to the poisoning attack.
The global Electronic Health Record (EHR) market is growing dramatically and has already hit $31.5 billion in 2018. To safeguard the security of EHR data and privacy of patients, fine-grained information access and sharing mechanisms are essential for EHR management. This paper proposes a hybrid architecture of blockchain and edge nodes to facilitate EHR management. In this architecture, we utilize attribute-based multi-signature (ABMS) scheme to authenticate user's signatures without revealing the sensitive information and multi-authority attribute-based encryption (ABE) scheme to encrypt EHR data which is stored on the edge node. We develop the blockchain module on Hyperledger Fabric platform and the ABMS module on Hyperledger Ursa library. We measure the signing and verifying time of the ABMS scheme under different settings, and experiment with the authentication events and access activities which are logged as transactions in blockchain.
Tsung-Ting Kuo, Rodney A. Gabriel, Krishna R. Cidambi, Lucila Ohno‐Machado
OBJECTIVE: Predicting patient outcomes using healthcare/genomics data is an increasingly popular/important area. However, some diseases are rare and require data from multiple institutions to construct generalizable models. To address institutional data protection policies, many distributed methods keep the data locally but rely on a central server for coordination, which introduces risks such as a single point of failure. We focus on providing an alternative based on a decentralized approach. We introduce the idea using blockchain technology for this purpose, with a brief description of its own potential advantages/disadvantages. MATERIALS AND METHODS: We explain how our proposed EXpectation Propagation LOgistic REgRession on Permissioned blockCHAIN (ExplorerChain) can achieve the same results when compared to a distributed model that uses a central server on 3 healthcare/genomic datasets, and what trade-offs need to be considered when using centralized/decentralized methods. We explain how the use of blockchain technology can help decrease some of the problems encountered in decentralized methods. RESULTS: We showed that the discrimination power of ExplorerChain can be statistically similar to its counterpart central server-based algorithm. While ExplorerChain inherited some benefits of blockchain, it had a small increased running time. DISCUSSION: ExplorerChain has the same prerequisites as a distributed model with a centralized server for coordination. In a manner similar to secure multi-party computation strategies, it assumes that participating institutions are honest, but "curious." CONCLUSION: When evaluated on relatively small datasets, results suggest that ExplorerChain, which combines artificial intelligence and blockchain technologies, performs as well as a central server-based method, and may avoid some risks at the cost of efficiency.
High availability of data is responsible for the current trends in Artificial\nIntelligence (AI) and Machine Learning (ML). However, high-grade datasets are\nreluctantly shared between actors because of lacking trust and fear of losing\ncontrol. Provenance tracing systems are a possible measure to build trust by\nimproving transparency. Especially the tracing of AI assets along complete AI\nvalue chains bears various challenges such as trust, privacy, confidentiality,\ntraceability, and fair remuneration. In this paper we design a graph-based\nprovenance model for AI assets and their relations within an AI value chain.\nMoreover, we propose a protocol to exchange AI assets securely to selected\nparties. The provenance model and exchange protocol are then combined and\nimplemented as a smart contract on a permission-less blockchain. We show how\nthe smart contract enables the tracing of AI assets in an existing industry use\ncase while solving all challenges. Consequently, our smart contract helps to\nincrease traceability and transparency, encourages trust between actors and\nthus fosters collaboration between them.\n
Proof-of-vote is a third generation of the Nakamoto consensus. With proof-of-vote, validators compete for people-votes, using proof-of-suffrage given by proof-of-person, and authorize transactions based on authority delegated by the consensus mechanism, just like proof-of-work or proof-of-stake. This logical conclusion of the Nakamoto consensus allows a “nation” of people to secure their own ledger, the equivalent of representative democracy for distributed ledger technology.
Blockchain is a decentralized transaction and data management technology. It was developed for the world's first cryptocurrency known as Bitcoin in 2008. The reason behind its popularity was its properties which provide pseudonymity, security, and data integrity without third-party intervention. Initially, most of the researches were focused on the Bitcoin system and its limitation, but later other applications of Blockchain e.g. smart contracts and licensing [1] also got famous. Blockchain technology has the potential to change the way how transactions are conducted in daily life. It is not limited to cryptocurrencies but could be possibly applied in various environments where any forms of transactions are done. This article presents a comprehensive overview of Blockchain technology, its development, applications, security issues, and their countermeasures. In particular, the security towards illegal data insertion and the countermeasures is focused. Our analysis of countermeasures of illegal data insertion can be combined for increased efficiency. After the introduction of the Blockchain and consensus algorithm, some famous Blockchain applications and expected future of Blockchain are deliberated. Then, the technical challenges of Blockchain are discussed, in which the main focus here is on the security and the data insertion in Blockchain. The review of the possible countermeasures to overcome the security issues related to data insertion are elaborated.
Yan Zhang, Bing Li, Ben Liu, Jiaxin Wu · 6 authors
The Internet of Things (IoT) benefits our lives by integrating physical devices to the real world and offers a crucial internet infrastructure for future civilization. Because IoT devices are widely distributed and restricted in resources, it is difficult for them to adopt traditional security methods to resist malicious attacks. Unauthorized access to IoT devices, which results in severe privacy and security problems, has become a major challenge that has impeded IoT technology from being widely adopted. Therefore, the access control for IoT devices urgently needs to be improved when dealing with authorization issues. In this paper, we propose an attribute-based access control scheme that provides decentralized, flexible, and fine-grained authorization for IoT devices. Blockchain is utilized to provide authentic and reliable credentials. More importantly, a verifiable collaboration mechanism is designed to meet the needs of controlled access authorization in emergencies. Authority nodes are constructed to execute major computation tasks and interact with the blockchain. The security analysis shows that our scheme can reliably guarantee the security of authorized access. More than security assurance, a proof-of-concept prototype has been implemented to prove that our scheme is scalable, efficient, and accommodates IoT devices well.
Blockchain shows great potential to be applied in wireless IoT ecosystems for establishing the trust and consensus mechanisms without central authority's involvement. Based on RAFT consensus mechanism, this letter investigates the security performance of wireless blockchain networks in the presence of malicious jamming. We first map and model the blockchain transaction as a wireless network composed of uplink and downlink transmissions by assuming the follower nodes' position as a Poisson Point Process (PPP) with selected leader location. The probability of achieving successful blockchain transactions is derived and verified by extensive simulations. The results provide analytical guidance for the practical deployment of wireless blockchain networks.
Yeṣem Kurt Peker, Xavier Rodríguez, James Ericsson, Suk Jin Lee · 5 authors
Blockchain is a developing technology that can be utilized for secure data storage and sharing. In this work, we examine the cost of Blockchain-based data storage for constrained Internet of Things (IoT) devices. We had two phases in the study. In the first phase, we stored data retrieved from a temperature/humidity sensor connected to an Ethereum testnet blockchain using smart contracts in two different ways: first, appending the new data to the existing data, storing all sensor data; and second, overwriting the new data onto the existing data, storing only a recent portion of the data. In the second phase, we stored simulated data from several sensors on the blockchain assuming sensor data is numeric. We proposed a method for encoding the data from the sensors in one variable and compared the costs of storing the data in an array versus storing the encoded data from all sensors in one variable. We also compared the costs of carrying out the encoding within the smart contract versus outside the smart contract. In the first phase, our results indicate that overwriting data points is more cost-efficient than appending them. In the second phase, using the proposed encoding method to store the data from several sensors costs significantly less than storing the data in an array, if the encoding is done outside the smart contract. If the encoding is carried out in the smart contract, the cost is still less than storing the data in an array, however, the difference is not significant. The study shows that even though expensive, for applications where the integrity and transparency of data are crucial, storing IoT sensor data on Ethereum could be a reliable solution.