Blockchain Papers

Luxiu Yin, Pengfei Li, Juan Luo

No abstract is available for this record.

Yulei Wu, Zehua Wang, Yuxiang Ma, Victor C. M. Leung

No abstract is available for this record.

Osamah Ibrahim Khalaf, Ghaida Muttashar Abdulsahib

No abstract is available for this record.

Mahadev A. Gawas, Hemprasad Yashwant Patil, Sweta Govekar

No abstract is available for this record.

Bowen Hu, Yingwen Chen, Hujie Yu, Linghang Meng · 5 authors

A staggering number of consumer Internet-of-Things devices are being deployed in various application scenarios, and massive data will be generated per day. How to achieve a secure and efficient data-sharing scheme for the consumer IoT applications is a huge challenge for us. The traditional cloud-based IoT has the dilemma of prolonged communication delay and privacy leakage. With the application of 5G technology, edge computing can effectively alleviate these problems. However, it cannot meet the higher security requirements for the data sources’ authenticity and information reliability. By combining the blockchain and smart contracts technology, this article proposes a distributed, efficient, and secure data-sharing scheme centered on consumer IoT devices. This architecture consists of four layers: 1) IoT devices layer, 2) edge storage layer, 3) blockchain network layer, and 4) application services layer. We design smart contracts based on the attributed based access control and the searchable encryption algorithm, including device retrieval contract, policy management contract, and authorization verification contract. Through the implementation of simulated experiments, we prove that our proposed architecture can satisfy the large-scale data access requests and bring a tolerable level of communication overhead. The proposed framework is one of the few attempts to leverage the edge computing and blockchain technologies to support IoT data sharing.

Moritz Platt, Anton Hasselgren, Juan M. Román-Belmonte, Marcela Tuler de Oliveira · 8 authors

The enormous pressure of the increasing case numbers experienced during the COVID-19 pandemic has given rise to a variety of novel digital systems designed to provide solutions to unprecedented challenges in public health. The field of algorithmic contact tracing, in particular, an area of research that had previously received limited attention, has moved into the spotlight as a crucial factor in containing the pandemic. The use of digital tools to enable more robust and expedited contact tracing and notification, while maintaining privacy and trust in the data generated, is viewed as key to identifying chains of transmission and close contacts, and, consequently, to enabling effective case investigations. Scaling these tools has never been more critical, as global case numbers have exceeded 100 million, as many asymptomatic patients remain undetected, and as COVID-19 variants begin to emerge around the world. In this context, there is increasing attention on blockchain technology as a part of systems for enhanced digital algorithmic contact tracing and reporting. By analyzing the literature that has emerged from this trend, the common characteristics of the designs proposed become apparent. An archetypal system architecture can be derived, taking these characteristics into consideration. However, assessing the utility of this architecture using a recognized evaluation framework shows that the added benefits and features of blockchain technology do not provide significant advantages over conventional centralized systems for algorithmic contact tracing and reporting. From our study, it, therefore, seems that blockchain technology may provide a more significant benefit in other areas of public health beyond contact tracing.

Bhawna Chaudhary, Karan Singh

No abstract is available for this record.

Yilong Hui, Nan Cheng, Zhou Su, Yuanhao Huang · 7 authors

The customization of edge computing services is one of the key research fields in sixth-generation (6G) heterogeneous vehicular networks (HetVNETs). With various personalized requirements of vehicles on computation-intensive applications, how to explore the heterogeneous computing resources in the 6G HetVNETs to guarantee vehicles with the customized Quality of Experience (QoE), therefore, becomes a challenge. In this article, we develop a novel secure scheme to provide personalized edge computing services for moving vehicles (MVs) in 6G HetVNETs. In the scheme, a smart-contract-based secure edge computing architecture is designed by jointly considering the attack models and the characteristics of the 6G network infrastructures (e.g., satellites, drones, base stations, and roadside units), where each network infrastructure manages a number of parking vehicles to complete computing services collaboratively. With this architecture, based on the available computing resources owned by different network infrastructures, the collaborative computing resource allocation algorithm is designed to help each network infrastructure decide a customized service strategy (CSS) to satisfy the QoE of MVs. After deciding the CSSs, a model based on the second price-sealed auction is formulated to describe the competition among the network infrastructures, where the Nash equilibrium of the game is obtained to guide their optimal bidding strategies to obtain the chance for completing the services. The security analysis and the simulation results show that the proposed scheme can defend against the attacks and lead to a lower cost for completing the services than the conventional schemes.

Sidra Aslam, Aleksandar Tošić, Michaël Mrissa

During the last decade, distributed ledger solutions such as blockchain have gained significant attention due to their decentralized, immutable, and verifiable features. However, the public availability of data stored on the blockchain and its link to users may raise privacy and security issues. In some cases, addressing these issues requires blockchain data to be secured with mechanisms that allow on-demand (as opposed to full) disclosure. In this paper, we give a comprehensive overview of blockchain privacy and security requirements, and detail how existing mechanisms answer them. We provide a taxonomy of current attacks together with related countermeasures. We present a thorough comparative analysis based on various parameters of state-of the-art privacy and security mechanisms, we provide recommendations to design secure and privacy-aware blockchain, and we suggest guidelines for future research.

Eranga Bandara, Xueping Liang, Peter Foytik, Sachin Shetty · 8 authors

No abstract is available for this record.

Prasanjit Dey, S.K. Chaulya, Sanjay Kumar

Summary A secure decision tree twin support vector machine (DT‐TSVM) multi‐classification algorithm has been proposed in this paper for improving the reliability and security of the collected IoT data from multiple data providers. The multiclass secure DT‐TSVM algorithm has been employed to train a machine learning model using the encrypted training dataset. The training dataset is collected via a blockchain platform. A blockchain method has been adopted to construct a secure and reliable distributed platform among dataset providers. The Paillier homomorphic cryptosystem has been applied for encrypting the IoT dataset. Then, the dataset has been recorded on the distributed ledger. The secure DT‐TSVM algorithm's‐based train model effectiveness has been compared with the other two available algorithms, namely the multiclass binary support vector machine (MBSVM) and one‐to‐one SVM algorithms. The experiment results showed that the privacy‐preserving multiclass secure DT‐TSVM‐based model did not reduce the accuracy, but it increased the average precision and recall by 0.53% and 0.44% than MBSVM and 0.82% and 0.71% than one‐to‐one SVM, respectively. Further, the time consumption of data providers and data analysts did not change significantly with the increase of number of data provider.

Sowmya Kudva, Shahriar Badsha, Shamik Sengupta, Hung Manh La · 6 authors

No abstract is available for this record.

Guiyu Kou, Liquan Chen

The development of blockchain has put forward higher requirements for authentication technology. In order to solve the current blockchain authentication problem and enhance the supervision and anonymity, we propose an authentication scheme based on master-slave certificate and zero-knowledge proof. Users can hide their real identity information through the anonymity of the slave certificate. When necessary, regulators can track the malicious users through smart contracts. Through security analysis, it is verified that there is no linkability between the master and slave certificates of this scheme, which can efficiently achieve supervisable anonymous authentication. The simulation experiment results show that the scheme is stable and scalable. The results also show that, compared with the traditional authentication, this scheme reduces the computational overhead of certificate issuers and is suitable for adoption in blockchain systems.

Lihua Song, Zongke Zhu, Mengchen Li, Li Ma · 5 authors

Since more and more devices join the Internet of Things(IoT) network, a large amount of user sensitive data is generated. The leakage of these data will cause very serious consequences. Traditional access control is prone to single point of failure. The existing researches on the combination of blockchain and access control have some disadvantages, such as the difficulty of managing access rights, inefficient access efficiency, and the difficulty of supporting lightweight IOT devices. This paper proposes an IoT access control model based on blockchain smart contract, called SCBAC. Firstly, by adopting the idea of IoT Attributes Based Access Control(ABAC), the model supports a dynamic, fine-grained access control. Secondly, by deploying the access control strategy on the blockchain in the form of smart contracts, the computing pressure of IoT devices is reduced, so that the model can be applied to lightweight IoT devices and has tamper resistance and traceability characteristics. The idea of tokens is adopted into the strategy, and subjects obtain access rights by applying for tokens in advance, which improves access efficiency. In addition, Trust recommendation algorithm is adopted in the model, which effectively solves the problem of identity fraud in access control. Finally, we build a prototype system to verify this proposed model, through case analysis and security analysis, it shows that this access control model is effective and versatile. Furthermore, the model can be used as a reference for other IoT applications with access control security requirements.

Chenhao Xu, Jiaqi Ge, Yong Li, Yao Deng · 8 authors

Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy. FL is effective when dealing with independent and identically distributed (iid) datasets, but struggles with non-iid datasets. Various personalized approaches have been proposed, but such approaches fail to handle underlying shifts in data distribution, such as data distribution skew commonly observed in real-world scenarios (e.g., driver behavior in smart transportation systems changing across time and location). Additionally, trust concerns among unacquainted devices and security concerns with the centralized aggregator pose additional challenges. To address these challenges, this paper presents a dynamically optimized personal deep learning scheme based on blockchain and federated learning. Specifically, the innovative smart contract implemented in the blockchain allows distributed edge devices to reach a consensus on the optimal weights of personalized models. Experimental evaluations using multiple models and real-world datasets demonstrate that the proposed scheme achieves higher accuracy and faster convergence compared to traditional federated and personalized learning approaches.

Markus Lücking, Felix Kretzer, Niclas Kannengießer, Michael Beigl · 6 authors

Communication between vehicles and their environment (i.e., vehicle-to-everything or V2X communication) in vehicular ad hoc networks (VANETs) has become of particular importance for smart cities. However, economic challenges, such as the cost incurred by data sharing (e.g., due to power consumption), hinder the integration of data sharing in open systems into smart city applications, such as dynamic environmental zones. Moving from open data sharing to open data trading can address the economic challenges and incentivize vehicle drivers to share their data. In this context, integrating distributed ledger technology (DLT) into open systems for data trading is promising for reducing the transaction cost of payments in data trading, avoiding dependencies on third parties, and guaranteeing openness. However, because the integration of DLT conflicts with the short available communication time between fast moving objects in VANETs, it remains unclear how open data trading in VANETs using DLT should be designed to be viable. In this work, we present a system design for data trading in VANETs using DLT. We measure the required communication time for data trading between a vehicle and a roadside unit in a real scenario and estimate the associated cost. Our results show that the proposed system design is technically feasible and economically viable.

Wei Liu, Yang Li, Xiujun Wang, Yufei Peng · 6 authors

No abstract is available for this record.

Qinglei Kong, Rongxing Lu, Feng Yin, Shuguang Cui

Driving behaviors are highly relevant to automotive statuses and on-board safety, which offer compelling shreds of evidence for mobility as a service (MaaS) providers to develop personalized rental prices and insurance products. However, the direct dissemination of driving behaviors may lead to violations of identity and location privacy. In this paper, our proposed mechanism first achieves the verifiable aggregation and immutable dissemination of performance records by exploiting a blockchain with the proof-of-stake (PoS) consensus. Moreover, to acquire a driver's aggregated performance record from the blockchain, the proposed scheme first realizes quick identification with a Bloom filter and further approaches the target performance record through an oblivious transfer (OT) protocol. A performance evaluation shows that during the acquisition of the records, the computational complexity of our scheme is only related to the scale of the records contained in one transaction. However, the computational complexity of one traditional scheme without a Bloom filter depends on the scale of the records generated during each time slot. Furthermore, the computational complexity of another traditional scheme without aggregation relies on the scale of the records contained in one transaction, as well as the length of a driver's performance history. We also investigate the trade-off between the privacy level and computational complexity, and we determine the optimal number of data records in each transaction.

Lejun Zhang, Zhijie Zhang, Weizheng Wang, Zilong Jin · 6 authors

The traditional covert communication channel relying on a third-party node is vulnerable to attack. The data are easily tampered with and the identity information of the communication party is fragile. Blockchain has the characteristics of decentralization and tamper resistance, which can effectively solve the above problems. In addition, some confidential information needs to be transmitted covertly in the transparent blockchain. A smart contract deployed in the blockchain to automatically realize its function can replace a centralized node to provide credible guarantee for communication. The diversity of parameters, data redundancy, and code programmability of smart contract make it an excellent carrier for covert communication under blockchain. In this article, we propose a covert communication model combined with smart contracts to covertly transfer information in the blockchain environment. To implement this model, we use the parameters in the contract to map the secret information sequence, and call the contract to transfer message. Voting contract and secret bidding contract are combined to instantiate the proposed model, and optimized versions of the two contracts are also proposed to reduce costs. Moreover, we use encryption algorithms and two-round protocols to ensure data privacy and design corresponding information embedding and transmission methods for different scenarios. To improve the concealment of communication, redundant options, effective price ranges, and invalid bids are set in two contracts, respectively. The experimental results show that the proposed model has tamper resistance and low complexity, and it is feasible to use this model for covert communication.

Bohan Li, Ruochen Liang, Wei Zhou, Hailian Yin · 6 authors

In Internet of Vehicles (IoV), the vehiclead hocnetwork (VANET) provides the location-based service (LBS) when vehicles communicate with the dynamic environment. As an integration of satellite systems and terrestrial communications, the space–air–ground integrated network (SAGIN) provides a reliable and efficient way for LBS. But the privacy protection in SAGIN cannot meet LBS security requirements well, so we present a blockchain-based LBS security preserving trust model.$K$-anonymous location privacy protection algorithm is used to hide users’ real position so that users can avoid personal privacy disclosure when requesting LBSs. We propose a trust management algorithm which can detect the malicious behaviors when constructing anonymous regions and clear the malicious users out of the system. Besides, we use blockchain to implement the transparency and conditional anonymity of the system. Missive experiments indicate that our scheme is feasible and outperforms part of state-of-the-art privacy protection approaches.

R Manikandaprabhu, Mohamed Ashwak M., Mohamed Ashwak P, K Jegan · 5 authors

An electoral system or voting system is a set of rules that determine how elections and referendums are conducted and how their results are determined. Election is a very important event in a modern democracy but large sections of society around the world do not trust their election system which is major concern for the democracy. Distributed ledger technology is an exciting technological advancement in the information technology world. Blockchain Technologies offer an infinite range of applications benefiting from sharing economies. In this paper the proposed system is to store the ballot information as a block node for each and every voter and transfer the voters vote hash over the internet to all other nodes. The proposed system is cost-efficient when compared to the traditional electronic voting machines.

Yuanyu Zhang, Ruka Nakanishi, Masahiro Sasabe, Shoji Kasahara

Unauthorized resource access represents a typical security threat in the Internet of Things (IoT), while distributed ledger technologies (e.g., blockchain and IOTA) hold great promise to address this threat. Although blockchain-based IoT access control schemes have been the most popular ones, they suffer from several significant limitations, such as high monetary cost and low throughput of processing access requests. To overcome these limitations, this paper proposes a novel IoT access control scheme by combining the fee-less IOTA technology and the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology. To control the access to a resource, a token, which records access permissions to this resource, is encrypted by the CP-ABE technology and uploaded to the IOTA Tangle (i.e., the underlying database of IOTA). Any user can fetch the encrypted token from the Tangle, while only those who can decrypt this token are authorized to access the resource. In this way, the proposed scheme enables not only distributed, fee-less and scalable access control thanks to the IOTA but also fine-grained attribute-based access control thanks to the CP-ABE. We show the feasibility of our scheme by implementing a proof-of-concept prototype system using smart phones (Google Pixel 3XL) and a commercial IoT gateway (NEC EGW001). We also evaluate the performance of the proposed scheme in terms of access request processing throughput. The experimental results show that our scheme enables object owners to authorize access rights to a large number of subjects in a much (about 5 times) shorter time than the existing access control scheme called Decentralized Capability-based Access Control framework using IOTA (DCACI), significantly improving the access request processing throughput.

Hirotsugu Seike, Yasukazu Aoki, Noboru Koshizuka

In recent years, DNNs (Deep Neural Networks) have been applied into various fields and expected to be deployed into real-world applications. On the other hand, lack of transparency in DNNs makes them unreliable. To ensure transparency in DNN models, it's necessary that model validators can verify the entire learning process and convince third parties with limited resource that the given model is correctly generated. For this purpose, we propose a smart contract that is based on the dispute resolution protocol for verifying DNN model generation process. We divide the entire learning process into layer-based computations. The necessary data for validating each computation, such as the outputs of neurons, weights between layers and their gradients, are uniquely determined by the one-way hash function and the hashes are combined by multiple structured Merkle trees. This enables an honest validator to make a proof that asserts the target model is incorrectly generated, and third parties can check whether the assertion is true by only performing the given computation. Finally, to reveal how our proposal affects the performance degradation during the training, we evaluated running time for deep learning that enables our proofs. This result shows that our proposal can be applied into real applications. For this purpose, we propose a smart contract that is based on the dispute resolution protocol for verifying DNN model generation process. We divide the entire learning process into layer-based computations. The necessary data for validating each computation, such as the outputs of neurons, weights between layers and their gradients, are uniquely determined by the one-way hash function and the hashes are combined by multiple structured Merkle trees. This enables an honest validator to make a proof that asserts the target model is incorrectly generated, and third parties can check whether the assertion is true by only performing the given computation. Finally, to reveal how our proposal affects the performance degradation during the training, we evaluated running time for deep learning that enables our proofs. This result shows that our proposal can be applied into real applications. Finally, to reveal how our proposal affects the performance degradation during the training, we evaluated running time for deep learning that enables our proofs. This result shows that our proposal can be applied into real applications.

Muhammad Asad, Ahmed Moustafa, Muhammad Aslam

No abstract is available for this record.