Blockchain Papers

Yu Yu, Xiang Xie

This perspectives article surveys the most promising privacy-preserving cryptographic technologies including secure multiparty computation, zero-knowledge proofs and fully homomorphic encryption, and their various real-world applications.

Oliver Stengele, Markus Raiber, Jörn Müller‐Quade, Hannes Hartenstein

We address the Threshold Information Disclosure (TID) problem on Ethereum: An arbitrary number of users commit to the scheduled disclosure of their individual messages recorded on the Ethereum blockchain if and only if all such messages are disclosed. Before a disclosure, only the original sender of each message should know its contents. To accomplish this, we task a small council with executing a distributed generation and threshold sharing of an asymmetric key pair. The public key can be used to encrypt messages which only become readable once the threshold-shared decryption key is reconstructed at a predefined point in time and recorded on-chain. With blockchains like Ethereum, it is possible to coordinate such procedures and attach economic stakes to the actions of participating individuals. In this paper, we present ETHTID, an Ethereum smart contract application to coordinate Threshold Information Disclosure. We base our implementation on ETHDKG [1], a smart contract application for distributed key generation and threshold sharing, and adapt it to fit our differing use case as well as add functionality to oversee a scheduled reconstruction of the decryption key. For our main cost saving optimisation, we show that the security of the underlying cryptographic scheme is maintained. We evaluate how the execution costs depend on the size of the council and the threshold and show that the presented protocol is deployable on Ethereum with a council of more than 200 members with gas savings of 20-40% compared to ETHDKG.

Shichang Xuan, Ming Jin, Xin Li, Zhaoyuan Yao · 6 authors

The rapid development in network technology has resulted in the proliferation of Internet of Things (IoT). This trend has led to a widespread utilization of decentralized data and distributed computing power. While machine learning can benefit from the massive amount of IoT data, privacy concerns and communication costs have caused data silos. Although the adoption of blockchain and federated learning technologies addresses the security issues related to collusion attacks and privacy leakage in data sharing, the “free-rider attacks” and “model poisoning attacks” in the federated learning process require auditing of the training models one by one. However, that increases the communication cost of the entire training process. Hence, to address the problem of increased communication cost due to node security verification in the blockchain-based federated learning process, we propose a communication cost optimization method based on security evaluation. By studying the verification mechanism for useless or malicious nodes, we also introduce a double-layer aggregation model into the federated learning process by combining the competing voting verification methods and aggregation algorithms. The experimental comparisons verify that the proposed model effectively reduces the communication cost of the node security verification in the blockchain-based federated learning process.

Xuewei Li, Yue Chen, HuaiYu Zhu

Abstract With the large-scale application of cloud storage systems, lots of attribute-based access control (ABAC) schemes have been introduced to protect data and user security in this insecure environment. ABAC can make data owners control their own data and protect data security and privacy. However, there are two serious privacy leakage problems, namely user attribute privacy and policy privacy, should be solved in the process of constructing ABAC schemes. In this paper, an ABAC scheme supporting privacy protection is constructed, which can solve privacy leakage problems of user attribute privacy and policy privacy in large universe attribute system. Furthermore, a framework is proposed. The framework combines our ABAC scheme, the Ethereum blockchain and blockchain-based storage system. In this framework, the security characteristics of blockchain technology are used to realize decentralization, tamper-resistant and avoiding single point of failure. Besides, the problems of attribute revocation and policy updating are solved by smart contract on the Ethereum blockchain. Finally, we established an initial implementation on Linux and Rinkeby test network, and the experimental results show that our scheme is feasible.

Yang Liu, Terry N. Guo, Zhe Chen, Xueying Jiang

Blockchain's immutability can resist unauthorized changes of ledgers, thus it can be used as a trust enhancement mechanism to a shared system. Indeed, blockchain has been considered to solve the security and privacy issues of the Internet of Things (IoT). In this regard, most researches currently focus on the realization of various access control models and architectures, and are working towards making full use of the blockchain to secure IoT systems. It is worth noting that there has been an increasingly heavy pressure on the blockchain storage caused by dealing with massive IoT data and handling malicious access behaviors in the system, and not many countermeasures have been seen to curb the increase. However, this problem has not been paid enough attention. In this paper, we implement an attribute-based access control scheme using smart contracts in Quorum blockchain. It provides basic access control functions and conserves storage by reducing the number of smart contracts. In addition, a reputation-based technique is introduced to cope with malicious behaviors. Certain illegal transactions can be blocked by the credit-assessment algorithm, which deters possibly malicious nodes and gives more chance to well-behaved nodes. The feasibility of our proposed scheme is demonstrated by doing experiment on a testbed and conducting a case study. Finally, the system performance is assessed based on experimental measurement.

Mani Karthik Suhas Suripeddi, Pradnya Purandare

Abstract This research work aims to investigate Blockchain technology and GDPR compliance studies. This will analyze the data privacy perspective with respect to distributed ledger technology. Blockchain has become one of the most frequently discussed technologies for its ability to allow for peer-to-peer transactions without a centralized intermediary. The GDPR was implemented in May 2018 for EU member states to maintain data privacy. DLT, the underlying technology of blockchain as is a decentralized system without any monetary authority. This research conducted a thorough literature review on prior conducted research to investigate the problems and determine the gaps of GDPR compliance with blockchain technologies and discuss the technical, use-case designs or solutions that make blockchain more compliant GDPR in terms of privacy. This systematic literature review addresses the gaps, feasibility, efficiency, and data privacy issues on compatibility problems that are primarily concerned with how a distributed ledger technology system in which recorded data or transaction cannot be changed or erased is challenging the GDPR data subject access rights (DSAR), where every data subject’s personal data which is compliant to GDPR has a right to exercise their Rights to rectify, delete or limit the processing of your personal data at any time if necessary.

Sonia Alice George, Steffie Maria Stephen, Arunita Jaekel

A vehicular ad hoc network (VANET) consists of vehicles, roadside units, and other infrastructures that communicate with each other with the goal of improving road safety, reducing accidents, and alleviating traffic congestion. For safe and secure operation of critical applications in VANET, it is essential to ensure that only authenticated vehicles can participate in the network. Another important requirement for VANET communication is that the privacy of vehicles and their users must be protected. Privacy can be improved by using pseudonyms instead of actual vehicle identities during communication. However, it is also necessary to ensure that these pseudonyms can be linked to the real vehicle identities if needed, in order to maintain accountability. In this paper, we propose a new blockchain-based decentralized pseudonym management scheme for VANET. This allows the vehicles to maintain conditional anonymity in the network. The blockchain is used to maintain a record of each vehicle and all of its pseudo-IDs. The information in the blockchain can only be accessed by authorized entities and is not available to all vehicles. The proposed distributed framework maintains an immutable record of the vehicle data, which is not vulnerable to a single point of failure. We compared the performance of the proposed approach with a traditional PKI scheme and shown that it significantly reduces the authentication delay.

Liang Zhu, Xiaowei Liu, Liping Yu, Zengyu Cai · 5 authors

The rise of Internet of Things (IoT) technology promotes the rapid development of location services industry. The idea of smart connectivity also provides a new direction for Location-Based Social Networks (LBSNs). However, due to limited calculate ability and internal storage space of IoT devices, historical location data of users is generally stored in the central server, which is likely to cause the disclosure of users’ private data. In this paper, we propose a Blockchain-enabled Privacy-Preserving Location Sharing (B-PPLS) scheme, which is a new framework that not only protects user location privacy but also provides effective location sharing services for users. For B-PPLS, location data owners can share the location area instead of location coordinates to Requesters, in order to realize the location privacy preserving. Also, the Merkle hash tree is utilized to divide the location area, so as to realize the multilevel privacy preserving. Furthermore, four algorithms are proposed to achieve the four stages of initialization, location record, location sharing, and location verification, respectively. Finally, we analyze the security of the proposed B-PPLS scheme and compare the performance with other related location privacy-preserving schemes by experimental evaluation.

Yin Yang

Deep neural networks (DNNs) could be very useful in blockchain applications such as DeFi and NFT trading. However, training / running large-scale DNNs as part of a smart contract is infeasible on today's blockchain platforms, due to two fundamental design issues of these platforms. First, blockchains nowadays typically require that each node maintain the complete world state at any time, meaning that the node must execute all transactions in every block. This is prohibitively expensive for computationally intensive smart contracts involving DNNs. Second, existing blockchain platforms expect smart contract transactions to have deterministic, reproducible results and effects. In contrast, DNNs are usually trained / run lock-free on massively parallel computing devices such as GPUs, TPUs and / or computing clusters, which often do not yield deterministic results. This paper proposes novel platform designs, collectively called A New Hope (ANH), that address the above issues. The main ideas are (i) computing-intensive smart contract transactions are only executed by nodes who need their results, or by specialized serviced providers, and (ii) a non-deterministic smart contract transaction leads to uncertain results, which can still be validated, though at a relatively high cost; specifically for DNNs, the validation cost can often be reduced by verifying properties of the results instead of their exact values. In addition, we discuss various implications of ANH, including its effects on token fungibility, sharding, private transactions, and the fundamental meaning of a smart contract.

Jingwei Ye, Xin Kang, Ying‐Chang Liang, Sumei Sun

Blockchain is a promising technology for future dynamic spectrum access (DSA) management due to its decentralization, immutability, and traceability. However, many challenges need to be addressed to integrate the blockchain to DSA, such as the trustworthiness of participating nodes’ spectrum sensing results, privacy protection of sensing nodes’ identities, and affordable lightweight consensus algorithms for IoT devices. In this article, we propose a trust-centric privacy-preserving blockchain for DSA in IoT networks. To be specific, we propose a trust evaluation mechanism to evaluate the trustworthiness of sensing nodes and design a Proof-of-Trust (PoT) consensus mechanism to build a scalable blockchain with high transaction-per-second (TPS). Moreover, a privacy protection scheme is proposed to protect sensors’ real-time geolocation information when they upload sensing data to the blockchain. Two smart contracts are designed to make the whole procedure (spectrum sensing, spectrum auction, and spectrum allocation) run automatically. Simulation results demonstrate the expected computation cost of the PoT consensus algorithm for reliable nodes is low, and the cooperative sensing performance is improved with the help of the trust evaluation mechanism. In addition, incentivization and security are also analyzed, which show that our system can not only encourage nodes’ participation, but also resist many kinds of attacks which are frequently arise in the trust management mechanism and blockchain-based IoT systems.

Munan Yuan, Xiaofeng Li, Xiru Li, Haibo Tan · 5 authors

Three-dimensional (3D) data are easily collected in an unconscious way and are sensitive to lead biological characteristics exposure. Privacy and ownership have become important disputed issues for the 3D data application field. In this paper, we design a privacy-preserving computation system (SPPCS) for sensitive data protection, based on distributed storage, trusted execution environment (TEE) and blockchain technology. The SPPCS separates a storage and analysis calculation from consensus to build a hierarchical computation architecture. Based on a similarity computation of graph structures, the SPPCS finds data requirement matching lists to avoid invalid transactions. With TEE technology, the SPPCS implements a dual hybrid isolation model to restrict access to raw data and obscure the connections among transaction parties. To validate confidential performance, we implement a prototype of SPPCS with Ethereum and Intel Software Guard Extensions (SGX). The evaluation results derived from test datasets show that (1) the enhanced security and increased time consumption (490 ms in this paper) of multiple SGX nodes need to be balanced; (2) for a single SGX node to enhance data security and preserve privacy, an increased time consumption of about 260 ms is acceptable; (3) the transaction relationship cannot be inferred from records on-chain. The proposed SPPCS implements data privacy and security protection with high performance.

Zeba Mahmood, Vacius Jusas

This paper introduces a blockchain-based federated learning (FL) framework with incentives for participating nodes to enhance the accuracy of classification problems. Machine learning technology has been rapidly developed and changed from a global perspective for the past few years. The FL framework is based on the Ethereum blockchain and creates an autonomous ecosystem, where nodes compete to improve the accuracy of classification problems. With privacy being one of the biggest concerns, FL makes use of the blockchain-based approach to ensure privacy and security. Another important technology that underlies the FL framework is zero-knowledge proofs (ZKPs), which ensure that data uploaded to the network are accurate and private. Basically, ZKPs allow nodes to compete fairly by only submitting accurate models to the parameter server and get rewarded for that. We have conducted an analysis and found that ZKPs can help improve the accuracy of models submitted to the parameter server and facilitate the honest participation of all nodes in FL.

Yuhao Bai, Qin Hu, Seung-Hyun Seo, Kyubyung Kang · 5 authors

Smart cities have become a trend with improved efficiency, resilience, and sustainability, providing citizens with high quality of life. With the increasing demand for a more participatory and bottom–up governance approach, citizens play an active role in the process of policy making, revolutionizing the management of smart cities. In the example of urban infrastructure maintenance, the public participation demand is more remarkable as the infrastructure condition is closely related to their daily life. Although blockchain has been widely explored to benefit data collection and processing in smart city governance, public engagement remains a challenge. In this article, we propose a novel public participation consortium blockchain system for infrastructure maintenance that is expected to encourage citizens to actively participate in the decision-making process and enable them to witness all administrative procedures in a real-time manner. To that aim, we introduced a hybrid blockchain architecture to involve a verifier group, which is randomly and dynamically selected from the public citizens, to verify the transaction. In particular, we devised a private-prior peer-prediction-based truthful verification mechanism to tackle the collusion attacks from public verifiers. Then, we specified a Stackelberg-game-based incentive mechanism for encouraging public participation. Finally, we conducted extensive simulations to reveal the properties and performances of our proposed blockchain system, which indicates its superiority over other variations.

Navin V. Keizer, Fan Yang, Ioannis Psaras, George Pavlou

Initiatives such as blockchains and decentralized storage networks are pushing for a decentralized Web3 to replace the current architecture. At the core of Web3 are network resource sharing services, which allow anyone to sell spare network capacity in return for rewards. These services require a way to establish trust, as parties are potentially malicious. This can be achieved by reputation systems. In this paper we make the case for using deep reinforcement learning in Web3 reputation calculation. More specifically, we propose a model which allows for decentralized calculation of scores with high personalization for the user.

Sukrutha L. T. Vangipuram, Saraju P. Mohanty, Elias Kougianos

With the world facing the new virus SARS-CoV-2, many countries have introduced instant Internet applications to identify people carrying the infection. Internet-of-Medical-Things (IoMT) have proven useful in collecting medical data as well in tracing an individual carrying the virus. The data collected or traced belongs to an individual and should be revealed to themselves and hospital providers, but not to any third-party unauthorized agencies. In this paper we use an off-chain distributed storage solution for loading large medical data sets and a blockchain implementation to securely transfer the data from the infected person to the hospital system using the edge infrastructure, and call it CoviChain. The Coronavirus Disease (COVID-19) statistics are loaded on to the edge, and moved to InterPlanetary File Systems (IPFS) storage to retrieve the hash of the data file. Once the hash is obtained, it is moved to the blockchain by means of smart contracts. As the information is being hashed twice, CoviChain addresses the security and privacy issues and avoid exposing individuals' data while achieving larger data storage on the blockchain with reduced cost and time.

Ammar Ahmed Khan, Muhammad Mubashir Khan, Kashif Mehboob Khan, Junaid Arshad · 5 authors

No abstract is available for this record.

Shantanu Pal, Ali Dorri, Raja Jurdak

With the rapid development of wireless sensor networks, smart devices, and traditional information and communication technologies, there is tremendous growth in the use of Internet of Things (IoT) applications and services in our everyday life. IoT systems deal with high volumes of data. This data can be particularly sensitive, as it may include health, financial, location, and other highly personal information. Fine-grained security management in IoT demands effective access control. Several proposals discuss access control for the IoT, however, a limited focus is given to the emerging blockchain-based solutions for IoT access control. In this paper, we review the recent trends and critical needs for blockchain-based solutions for IoT access control. We identify several important aspects of blockchain, including decentralised control, secure storage and sharing information in a trustless manner, for IoT access control including their benefits and limitations. Finally, we note some future research directions on how to converge blockchain in IoT access control efficiently and effectively.

Marta Bellés-Muñoz, Jordi Baylina, Vanesa Daza, José L. Muñoz

The benefits of blockchain technologies for industrial applications are unquestionable. However, it is a considerable challenge to use a transparent system like blockchain and at the same time provide privacy to sensitive data. Privacy technologies permit conducting private transactions about sensitive data over transparent networks, but their inherent complexity has been overwhelming for many developers. Closing the gap between developers and privacy-preserving technologies would help to the full adoption of the privacy by design framework for blockchain software. To this end, in this paper we present the software tools we have implemented to bring complex privacy technologies closer to developers and facilitate the job of implementing privacy-enabled blockchain applications.

Sheng Gao, Qianqian Su, Rui Zhang, Jianming Zhu · 6 authors

Traditional identity authentication solutions mostly rely on a trusted central entity, so they cannot handle single points of failure well. In addition, most of these traditional schemes need to store a large amount of identity authentication or public key information, which makes the schemes difficult to expand and use in distributed situations. In addition, the user prefers to protect the privacy of their information during the identity verification process. Due to the open and decentralized nature of the blockchain, the existing identity verification schemes are difficult to apply well in the blockchain. To solve this problem, in this article, we propose a privacy protection identity authentication scheme based on the blockchain. The user independently generates multiple-identity information, and these identities can be used to apply for an identity certificate. Authorities use the ECDSA signature algorithm and the RSA encryption algorithm to complete the distribution of the identity certificate based on the identity information and complete the registration of identity authentication through the smart contract on the blockchain. On the one hand, it can realize the protection of real identity information; on the other hand, it can avoid the storage overhead caused by the need to store a large number of certificates or key pairs. Due to the use of the blockchain, there is no single point of failure in the authentication process, and it can be applied to distributed scenarios. The security and performance analysis show that the proposed scheme can meet security requirements and is feasible.

Qin Wang, Shiping Chen, Yang Xiang

Blockchain records transactions with various protection techniques against tampering. To meet the requirements on cooperation and anonymity of companies and organizations, researchers have developed a few solutions. Ring signature-based schemes allow multiple participants cooperatively to manage while preserving their individuals’ privacy. However, the solutions cannot work properly due to the increased computing complexity along with the expanded group size. In this article, we propose a Multi-center Anonymous Blockchain-based (MAB) system, with joint management for the consortium and privacy protection for the participants. To achieve that, we formalize the syntax used by the MAB system and present a general construction based on a modular design. By applying cryptographic primitives to each module, we instantiate our scheme with anonymity and decentralization. Furthermore, we carry out a comprehensive formal analysis of our exemplified scheme. A proof of concept simulation is provided to show the feasibility. The results demonstrate security and efficiency from both theoretical perspectives and practical perspectives.

Enmao Diao, Jie Ding, Vahid Tarokh

Collaborations among multiple organizations, such as financial institutions, medical centers, and retail markets in decentralized settings are crucial to providing improved service and performance. However, the underlying organizations may have little interest in sharing their local data, models, and objective functions. These requirements have created new challenges for multi-organization collaboration. In this work, we propose Gradient Assisted Learning (GAL), a new method for multiple organizations to assist each other in supervised learning tasks without sharing local data, models, and objective functions. In this framework, all participants collaboratively optimize the aggregate of local loss functions, and each participant autonomously builds its own model by iteratively fitting the gradients of the overarching objective function. We also provide asymptotic convergence analysis and practical case studies of GAL. Experimental studies demonstrate that GAL can achieve performance close to centralized learning when all data, models, and objective functions are fully disclosed.

Shayan Eskandari, Mehdi Salehi, Wanyun Catherine Gu, Jeremy Clark

One fundamental limitation of blockchain-based smart contracts is that they execute in a closed environment. Thus, they only have access to data and functionality that is already on the blockchain, or is fed into the blockchain. Any interactions with the real world need to be mediated by a bridge service, which is called an oracle. As decentralized applications mature, oracles are playing an increasingly prominent role. With their evolution comes more attacks, necessitating greater attention to their trust model. In this systemization of knowledge paper (SoK), we dissect the design alternatives for oracles, showcase attacks, and discuss attack mitigation strategies.

Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne · 6 authors

The combination of mobile edge computing (MEC) and blockchain is transforming the current computing services in Internet of Things networks, by offering task offloading solutions with security enhancement enabled by blockchain mining. Nevertheless, these important enabling technologies have been studied separately in most existing works. This article proposes a novel cooperative task offloading and block mining (TOBM) scheme to optimize the system utility in blockchain-empowered MEC. Herein, each edge device (ED) not only handles data tasks but also deals with block mining which makes the system design and optimization highly complex. Therefore, we develop a novel cooperative deep reinforcement learning (DRL) approach which allows EDs to cooperatively offload their data tasks to the MEC server and perform block mining based on a Proof-of-Reputation consensus mechanism. Simulation results demonstrate that the proposed scheme significantly improves offloading utility, reduces blockchain mining latency, and achieves better system utility, compared to other non-cooperative and cooperative schemes.

Thomas Kerber, Aggelos Kiayias, Markulf Kohlweiss

Smart contracts present a uniform approach for deploying distributed computation and have become a popular means to develop security critical applications. A major barrier to adoption for many applications is the public nature of existing systems, such as Ethereum. Several systems satisfying various definitions of privacy and requiring various trust assumptions have been proposed; however, none achieved the universality and uniformity that Ethereum achieved for non-private contracts: One unified method to construct most contracts. We provide a unified security model for private smart contracts which is based on the Universal Composition (UC) model and propose a novel core protocol, KACHINA, for deploying privacy-preserving smart contracts, which encompasses previous systems. We demonstrate the KACHINA method of smart contract development, using it to construct a contract that implements privacy-preserving payments, along the lines of Zerocash, which is provably secure in the UC setting and facilitates concurrency.