Bin Cao, Zixin Wang, Long Zhang, Daquan Feng · 7 authors
In the past decade, blockchain has shown a promising vision to build trust without any powerful third party in a secure, decentralized and scalable manner. However, due to the wide application and future development from cryptocurrency to the Internet of Things, blockchain is an extremely complex system enabling integration with mathematics, computer science, communication and network engineering, etc. By revealing the intrinsic relationship between blockchain and communication, networking and computing from a methodological perspective, it provided a view to the challenge that engineers, experts and researchers hardly fully understand the blockchain process in a systematic view from top to bottom. In this article we first introduce how blockchain works, the research activities and challenges, and illustrate the roadmap involving the classic methodologies with typical blockchain use cases and topics. Second, in blockchain systems, how to adopt stochastic process, game theory, optimization theory, and machine learning to study the blockchain running processes and design the blockchain protocols/algorithms are discussed in details. Moreover, the advantages and limitations using these methods are also summarized as the guide of future work to be further considered. Finally, some remaining problems from technical, commercial and political views are discussed as the open issues. The main findings of this article will provide a survey from a methodological perspective to study theoretical model for blockchain fundamentals understanding, design network service for blockchain-based mechanisms and algorithms, as well as apply blockchain for the Internet of Things, etc.
Jan Kalbantner, Konstantinos Markantonakis, Darren Hurley-Smith, Carlton Shepherd · 5 authors
Distributed Ledger Technology (DLT) has an enormous potential but also downsides. One downside of many DLT systems, such as blockchain, is their limited transaction throughput that hinders their adoption in many use cases (e.g., real-time payments). State channels have emerged as a potential solution to enhance throughput by allowing transactions to process off-chain. While current proposals can increase scalability, they require high collateral and lack support for dynamic systems that require asynchronous state transitions. Additionally, the latency of channel initialisations can cause issues especially if fast interactions are required. In this paper, we propose an atomic, scalable and privacy-preserving protocol that enables secure and dynamic updates. We develop a smart contract-based Credit-Note System (CNS) that allows participants to lock funds before a state channel initialisation, which enhances flexibility and efficiency. We formalise our model using the Universal Composability (UC) framework and demonstrate that it achieves the stated design goals of privacy, scalability, and atomicity. Moreover, we implement a dispute process in the state channel to counter availability attacks. Finally, we analyse the protocol in the context of an asynchronous smart grid-based marketplace.
This objective of this report is to review existing enterprise blockchain technologies - EOSIO powered systems, Hyperledger Fabric and Besu, Consensus Quorum, R3 Corda and Ernst and Young's Nightfall - that provide data privacy while leveraging the data integrity benefits of blockchain. By reviewing and comparing how and how well these technologies achieve data privacy, a snapshot is captured of the industry's current best practices and data privacy models. Major enterprise technologies are contrasted in parallel to EOSIO to better understand how EOSIO can evolve to meet the trends seen in enterprise blockchain privacy. The following strategies and trends were generally observed in these technologies: Cryptography: the hashing algorithm was found to be the most used cryptographic primitive in enterprise or changeover privacy solutions. Coordination via on-chain contracts - a common strategy was to use a shared publicly ledger to coordinate data privacy groups and more generally managed identities and access control. Transaction and contract code sharing: there was a variety of different levels of privacy around the business logic (smart contract code) visibility. Some solutions only allowed authorised peers to view code while others made this accessible to everybody that was a member of the shared ledger. Data migrations for data privacy applications: significant challenges exist when using cryptographically stored data in terms of being able to run system upgrades. Multiple blockchain ledgers for data privacy: solutions attempted to create a new private blockchain for every private data relationship which was eventually abandoned in favour of one shared ledger with private data collections/transactions that were anchored to the ledger with a hash in order to improve scaling.
Hyperledger Fabric is an enterprise grade permissioned distributed ledger platform that offers modularity for a broad set of industry use cases. One modular component is a pluggable ordering service that establishes consensus on the order of transactions and batches them into blocks. However, as of the time of this writing, there is no production grade Byzantine Fault-Tolerant (BFT) ordering service for Fabric, with the latest version (v2.3) supporting only Crash Fault-Tolerance (CFT).In this work we describe the design and implementation of a BFT ordering service for Fabric, employing a new BFT consensus library. The new library, based on the BFT-SMART protocol and written in Go, is tailored to the blockchain use-case, yet is general enough to cater to a wide variety of other uses. The BFT library's design and integration into Fabric address crucial aspects that were left unsolved in all prior work, making them unfit for production use. We evaluate the new BFT ordering service by comparing it with the currently supported Raft-based CFT ordering service in Hyperledger Fabric.
Platooning technologies enable trucks to drive cooperatively and automatically, which bring benefits including less fuel consumption, more road capacity and safety. In order to establish trust during dynamic platoon formation, ensure vehicular data integrity, and guard platoons against potential attackers, it is pivotal to verify any given vehicle's identity information before granting it access to join a platoon. To address this concern in dynamic truck platooning, we present a novel location-aware and privacy-preserving verification protocol based on zero-knowledge proof and permissioned blockchain. By performing the verification process within the spatially-local area defined by a given platoon, our system can provide lower latency and communication overhead compared to a location-agnostic blockchain system. We prototype the proposed system and perform benchmark tests on the Hyperledger platform. The experimental results show that our system is suitable for real-world truck platooning.
Permissionless blockchain protocols are known to consume an outrageous amount of computing power and suffer from a trade-off between latency and confidence in transaction confirmation. The recently proposed Algorand blockchain protocol employs Byzantine agreements and has shown transaction confirmation latency on the order of seconds. Its strong resilience to Denial-of-Service and Sybil attacks and its low computing power footprint make it a strong candidate for the venue of decentralized economies and business ecosystems across industries. Nevertheless, Algorand's throughput is still far from the requirements of such applications. In this paper, we empower Algorand's protocol by multiplexing its byzantine agreements in order to improve performance. Experiments on wide area networks with up to ten thousand nodes show a 4-fold throughput increase compared to the original Algorand protocol.
The advent of distributed energy resources (DERs), such as distributed renewables, energy storage, electric vehicles, and controllable loads, \rv{brings} a significantly disruptive and transformational impact on the centralized power system. It is widely accepted that a paradigm shift to a decentralized power system with bidirectional power flow is necessary to the integration of DERs. The virtual power plant (VPP) emerges as a promising paradigm for managing DERs to participate in the power system. In this paper, we develop a blockchain-based VPP energy management platform to facilitate a rich set of transactive energy activities among residential users with renewables, energy storage, and flexible loads in a VPP. Specifically, users can interact with each other to trade energy for mutual benefits and provide network services, such as feed-in energy, reserve, and demand response, through the VPP. To respect the users' independence and preserve their privacy, we design a decentralized optimization algorithm to optimize the users' energy scheduling, energy trading, and network services. Then we develop a prototype blockchain network for VPP energy management and implement the proposed algorithm on the blockchain network. By experiments using real-world data-trace, we validated the feasibility and effectiveness of our algorithm and the blockchain system. The simulation results demonstrate that our blockchain-based VPP energy management platform reduces the users' cost by up to 38.6% and reduces the overall system cost by 11.2%.
The sixth generation (6G) systems are generally recognized to be established on ubiquitous Artificial Intelligence (AI) and distributed ledger such as blockchain. However, the AI training demands tremendous computing resource, which is limited in most 6G devices. Meanwhile, miners in Proof-of-Work (PoW) based blockchains devote massive computing power to block mining, and are widely criticized for the waste of computation. To address this dilemma, we propose an Evolved-Proof-of-Work (E-PoW) consensus that can integrate the matrix computations, which are widely existed in AI training, into the process of brute-force searches in the block mining. Consequently, E-PoW can connect AI learning and block mining via the multiply used common computing resource. Experimental results show that E-PoW can salvage by up to 80 percent computing power from pure block mining for parallel AI training in 6G systems.
Distributed Ledger Technologies (DLT) and Decentralized File Storages (DFS) are becoming increasingly used to create common, decentralized and trustless infrastructures where participants interact and collaborate in Peer-to-Peer interactions. A prominent use case is represented by decentralized data marketplaces, where users are consumers and providers at the same time, and trustless interactions are required. However, data in DLTs and DFS are usually unstructured and there are no efficient mechanisms to query a certain type of data for the search in the market. In this paper, we propose the use of a Distributed Hash Table (DHT) as a layer on top of DLTs where, once the data are acquired and stored in the ledger, these can be searched through multiple keyword based queries, thanks to the lookup functionalities offered by the DHT. The DHT network is a hypercube overlay structure, organized for an efficient processing of multiple keyword-based queries. We provide the architecture of such solution for a decentralized data marketplace and an analysis based on a simulation that proves the viability of the proposed approach.
Plenty of research on smart mobility is currently devoted to the inclusion of novel decentralized software architectures to these systems, due to the inherent advantages in terms of transparency, traceability, trustworthiness. MOVO is a decentralized application (dApp) for smart mobility. It includes: (i) a module for collecting data from vehicles and smartphones sensors; (ii) a component for interacting with Distributed Ledger Technologies (DLT) and Decentralized File Storages (DFS), for storing and validating sensor data; (iii) a module for "offline" interaction between devices. The dApp consists of an Android application intended for use inside a vehicle, which helps the user/driver collect contextually generated data (e.g. a driver's stress level, an electric vehicle's battery level), which can then be shared through the use of DLT (i.e., IOTA DLT and Ethereum smart contracts) and DFS (i.e., IPFS). The third module consists of an implementation of a communication channel that, via Wi-Fi Direct, allows two devices to exchange data and payment information with respect to DLT (i.e. cryptocurrency and token) assets. In this paper, we describe the main software components and provide an experimental evaluation that confirms the viability of the MOVO dApp in real mobility scenarios.
Yixin Li, Bin Cao, Liang Liang, Deming Mao · 5 authors
Wireless blockchain network is proposed to enable a decentralized and safe wireless networks for various blockchain applications. To achieve blockchain consensus in wireless network, one of the important steps is to broadcast new block using wireless channel. Under wireless network protocols, the block transmitting will be affected significantly. In this work, we focus on the consensus process in blockchain-based wireless local area network (B-WLAN) by investigating the impact of the media access control (MAC) protocol, CSMA/CA. With the randomness of the backoff counter in CSMA/CA, it is possible for latter blocks to catch up or outpace the earlier one, which complicates blockchain forking problem. In view of this, we propose mining strategies to pause mining for reducing the forking probability, and a discard strategy to remove the forking blocks that already exist in CSMA/CA backoff procedure. Based on the proposed strategies, we design Block Access Control (BAC) approaches to effectively schedule block mining and transmitting for improving the performance of B-WLAN. Then, Markov chain models are presented to conduct performance analysis in B-WLAN. The results show that BAC approaches can help the network to achieve a high transaction throughput while improving block utilization and saving computational power. Meanwhile, the trade-off between transaction throughput and block utilization is demonstrated, which can act as a guidance for practical deployment of blockchain.
Due to the distributed characteristics of Federated Learning (FL), the vulnerability of global model and coordination of devices are the main obstacle. As a promising solution of decentralization, scalability and security, leveraging blockchain in FL has attracted much attention in recent years. However, the traditional consensus mechanisms designed for blockchain like Proof of Work (PoW) would cause extreme resource consumption, which reduces the efficiency of FL greatly, especially when the participating devices are wireless and resource-limited. In order to address device asynchrony and anomaly detection in FL while avoiding the extra resource consumption caused by blockchain, this paper introduces a framework for empowering FL using Direct Acyclic Graph (DAG)-based blockchain systematically (DAG-FL). Accordingly, DAG-FL is first introduced from a three-layer architecture in details, and then two algorithms DAG-FL Controlling and DAG-FL Updating are designed running on different nodes to elaborate the operation of DAG-FL consensus mechanism. After that, a Poisson process model is formulated to discuss that how to set deployment parameters to maintain DAG-FL stably in different federated learning tasks. The extensive simulations and experiments show that DAG-FL can achieve better performance in terms of training efficiency and model accuracy compared with the typical existing on-device federated learning systems as the benchmarks.
Decentralized services are increasingly being developed and their Decentralized applications are increasingly developed but their performance metrics are not tested enough. The total number of transactions that can be supported by the blockchain network and the performance effects of selecting different consensus protocols, using different block intervals and block size should be tested. There are some blockchain performance tools but most are built for specific blockchain frameworks and require complex configuration. The GoHammer tool is developed to provide an easy to use, flexible test tool for the Ethereum/Quorum blockchain frameworks. Transaction per second (TPS) values and several performance metrics will be tested. This tool is also a part of the series of tools that can be integrated with Tubu-io. This tool will help in developing more efficient decentralized systems and will affect decreasing the costs of developing decentralized application projects.
The unique properties of blockchain enable central requirements of distributed secure logging: Immutability, integrity, and availability. Especially when providing transparency about data usages, a blockchain-based secure log can be beneficial, as no trusted third party is required. Yet, with data governed by privacy legislation such as the GDPR or CCPA, the core advantage of immutability becomes a liability. After a rightful request, an individual's personal data need to be rectified or deleted, which is impossible in an immutable blockchain. To solve this issue, we exploit a legal property of pseudonymized data: They are only regarded personal data if they can be associated with an individual's identity. We make use of this fact by presenting P3, a pseudonym provisioning system for secure usage logs including a protocol for recording new usages. For each new block, a one-time transaction pseudonym is generated. The pseudonym generation algorithm guarantees unlinkability and enables proof of ownership. These properties enable GDPR-compliant use of blockchain, as data subjects can exercise their legal rights with regards to their personal data. The new-usage protocol ensures non-repudiation, and therefore accountability and liability. Most importantly, our approach does not require a trusted third party and is independent of the utilized blockchain software.
Bishakh Chandra Ghosh, Tanay Bhartia, Sourav Kanti Addya, Sandip Chakraborty
With the increasing adoption of private blockchain platforms, consortia operating in various sectors such as trade, finance, logistics, etc., are becoming common. Despite having the benefits of a completely decentralized architecture which supports transparency and distributed control, existing private blockchains limit the data, assets, and processes within its closed boundary, which restricts secure and verifiable service provisioning to the end-consumers. Thus, platforms such as e-commerce with multiple sellers or cloud federation with a collection of cloud service providers cannot be decentralized with the existing blockchain platforms. This paper proposes a decentralized gateway architecture interfacing private blockchain with end-users by leveraging the unique combination of public and private blockchain platforms through interoperation. Through the use case of decentralized cloud federations, we have demonstrated the viability of the solution. Our testbed implementation with Ethereum and Hyperledger Fabric, with three service providers, shows that such consortium can operate within an acceptable response latency while scaling up to 64 parallel requests per second for cloud infrastructure provisioning. Further analysis over the Mininet emulation platform indicates that the platform can scale well with minimal impact over the latency as the number of participating service providers increases.
Haris Javaid, Ji Yang, Nathania Santoso, Mohit Upadhyay · 7 authors
In this paper, we demonstrate how Hyperledger Fabric, one of the most popular permissioned blockchains, can benefit from network-attached acceleration. The scalability and peak performance of Fabric is primarily limited by the bottlenecks present in its block validation/commit phase. We propose Blockchain Machine, a hardware accelerator coupled with a hardware-friendly communication protocol, to act as the validator peer. It can be adapted to applications and their smart contracts, and is targeted for a server with network-attached FPGA acceleration card. The Blockchain Machine retrieves blocks and their transactions in hardware directly from the network interface, which are then validated through a configurable and efficient block-level and transaction-level pipeline. The validation results are then transferred to the host CPU where non-bottleneck operations are executed. From our implementation integrated with Fabric v1.4 LTS, we observed up to 12x speedup in block validation when compared to software-only validator peer, with commit throughput of up to 68,900 tps. Our work provides an acceleration platform that will foster further research on hardware acceleration of permissioned blockchains.
At present, more than a billion closed-circuit television (CCTV) cameras are watching the world. These cameras garner a lot of visual information that is often processed and stored in remote and centralized cloud servers. Multiple occasions have revealed that this traditional approach is plagued with security and privacy breaches. The breaches could be the interception of raw videos while in transit to distant surveillance analytics centers (SAC), infiltration to cameras and network video records (NVR), or abuse of cameras and stored videos. Hence, the traditional video surveillance system (VSS) cannot guarantee the protection of the privacy of individuals caught on CCTV cameras. Therefore, this paper proposes a Secure and Privacy-preserving Stored surveillance video sharing (SePriS) mechanism for authorized users/nodes based on blockchain (BC), smart contracts, and the enciphering of video frames using DAB, a mechanism developed based on discrete cosine transform (DCT), advanced encryption standard (AES), and a block shuffling (BS) algorithm. The BC-based solution creates an environment auspicious for creating decentralized, reliable SACs and storage sites with secure and privacy-aware sharing of stored surveillance videos across SAC nodes and by law enforcers, police departments, and courts securely connected to the SAC nodes. The experiments and analyses validate that the proposed BC-based SePriS solution achieves the design purpose.
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Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
We review probabilistic models known as majority dynamics (also known as threshold Voter Models) and discuss their possible applications for achieving consensus in cryptocurrency systems. In particular, we show that using this approach straightforwardly for practical consensus in Byzantine setting can be problematic and requires extensive further research. We then discuss the FPC consensus protocol which circumvents the problems mentioned above by using external randomness.
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.
Interoperation for data sharing between permissioned blockchain networks relies on networks' abilities to independently authenticate requests and validate proofs accompanying the data; these typically contain digital signatures. This requires counterparty networks to know the identities and certification chains of each other's members, establishing a common trust basis rooted in identity. But permissioned networks are ad hoc consortia of existing organizations, whose network affiliations may not be well-known or well-established even though their individual identities are. In this paper, we describe an architecture and set of protocols for distributed identity management across permissioned blockchain networks to establish a trust basis for data sharing. Networks wishing to interoperate can associate with one or more distributed identity registries that maintain credentials on shared ledgers managed by groups of reputed identity providers. A network's participants possess self-sovereign decentralized identities (DIDs) on these registries and can obtain privacy-preserving verifiable membership credentials. During interoperation, networks can securely and dynamically discover each others' latest membership lists and members' credentials. We implement a solution based on Hyperledger Indy and Aries, and demonstrate its viability and usefulness by linking a trade finance network with a trade logistics network, both built on Hyperledger Fabric. We also analyze the extensibility, security, and trustworthiness of our system.
As an append-only distributed database, blockchain is utilized in a vast variety of applications including the cryptocurrency and Internet-of-Things (IoT). The existing blockchain solutions show downsides in communication and storage scalability, as well as decentralization. In this article, we propose LightChain , which is the first blockchain architecture that operates over a Distributed Hash Table (DHT) of participating peers. LightChain is a permissionless blockchain that provides addressable blocks and transactions within the network, which makes them efficiently accessible by all peers. Each block and transaction is replicated within the DHT of peers and is retrieved in an on-demand manner. Hence, peers in LightChain are not required to retrieve or keep the entire ledger. LightChain is fair as all of the participating peers have a uniform chance of being involved in the consensus regardless of their influence such as hashing power or stake. We provide formal mathematical analysis and experimental results (simulations and cloud deployment) to demonstrate the security, efficiency, and fairness of LightChain , and show that LightChain is the only existing blockchain that can provide integrity under the corrupted majority power of peers. As we experimentally demonstrate, compared to the mainstream blockchains such as Bitcoin and Ethereum, LightChain requires around 66 times smaller per node storage, and is around 380 times faster on bootstrapping a new node to the system, and each LightChain node is rewarded equally likely for participating in the protocol.
With the growing commercial interest in blockchain, permissioned implementations have received increasing attention. Unfortunately, existing BFT consensus protocols that are the backbone of permissioned blockchains, either scale poorly or offer limited throughput. Most of these algorithms require at least one process to receive and validate the votes from all other processes and then broadcast the result, which is inherently non-scalable. Some algorithms avoid this bottleneck by using aggregation trees to collect and validate votes. However, to the best of our knowledge, such algorithms offer limited throughput and degrade quickly in the presence of faults. In this paper we propose \thesystem, the first BFT communication abstraction that organizes participants in a tree to perform scalable vote aggregation and that, in faulty runs, is able to terminate the protocol within an optimal number of reconfigurations ($f+1$). We define precisely which aggregation trees allow for optimal reconfiguration and show that, unlike previous protocols, when using these configurations, \thesystem scales to large number of processes and outperforms HotStuff's throughput by up to 38x.
The first generation of blockchain focused on digital currencies and secure storage, management and transfer of tokenized values. Thereafter, the focus has been shifting from currencies to a broader application space. In this paper, we systematically explore marketplace types and properties, and consider the mechanisms required to support those properties through blockchain. We propose a generic and configurable framework for blockchain-based marketplaces, and describe how popular marketplace types, price discovery policies, and other configuration parameters are implemented within the framework by presenting concrete event-based algorithms. Finally, we consider three use cases with widely diverging properties and show how the proposed framework supports them.
Decentralized services are increasingly being developed and their proper usage in different areas is being experimented with. Autonomous codes, which are also called smart contracts, can be developed with Integrated Development Environments (IDE). However, these tools lack live environment tests. The underlying blockchain technologies are also evolving and it is not easy to catch all the developments. There is a need for an easy-to-use interface by which the developers can see the results of their codes. Tubu-io decentralized application development workbench is developed to serve as an efficient way for the programmers to deploy smart contracts on the blockchain networks and interact with them easily. It can also be used for teaching decentralized application programming for junior blockchain developers on blockchain testbeds. Finally, it will have an effect in decreasing the development time and the costs of developing decentralized application projects.