Bitcoin builds upon an unstructured peer-to-peer overlay network to disseminate transactions and blocks. Broadcast in such a network is slow and brings inconsistencies, i.e., peers have different views of the system state. Due to the delayed block propagation and the competition of mining, forking, i.e., the blockchain temporarily diverges into two or more branches, occurs frequently, which wastes computation power and causes security issues. This paper proposes an autonomous and distributed topology optimization mechanism to reduce block propagation delay and hence reduce the occurrence of blockchain forks. In the proposed mechanism, a node can autonomously update his neighbor set using the information provided by his current neighbors, since each neighbor will recommend a peer from his own neighbor set, i.e., a neighbor's neighbor, to this node. Each recommendation is based on a peer's propagation ability, which is characterized as a criteria function obtained through a combination of empirical analysis and machine learning. We further propose some metrics to evaluate a Bitcoin network topology. Experiment results reflect the effectiveness of the proposed mechanism and also indicate the correlation between block propagation time and fork rate.
Yuntao Wang, Zhou Su, Jiliang Li, Ning Zhang · 7 authors
With the proliferation of electric vehicles (EVs), private charging pile (PCP) sharing networks are likely to be an integral part of future smart cities, especially in places with limited public charging infrastructure. However, there are a number of operational challenges associated with the deployment of PCPs in such a shared and untrusted environment. For example, how do we formulate efficient PCP sharing strategies in PCP sharing networks, while also taking into consideration the dynamic charging behaviors of EVs? Therefore, in this paper, we propose an energyblockchain-based secure PCP sharing scheme (BBC) for PCP sharing networks. First, an energy blockchain-based framework is designed for PCP sharing networks to facilitate energy sharing services for EVs and PCPs, using both distributed ledgers and cryptocurrency. Then, we devise a reputation-based secure PCP sharing algorithm to improve consensus efficiency with smaller signature sizes. In addition, a distributed reputation mechanism is constructed to assess the trustworthiness of consensus nodes in blockchain, based on ratings, behaviors, and fading. We also model the interactions among EVs and cooperative PCPs as a joint coalition-matching game, and obtain the optimal strategies of PCPs and EVs by analyzing the Nash-stable coalitional structure and stable many-to-one matching pairs. Extensive simulations and the real-world implementation demonstrate that the proposed approach improves the utility of EV users and renewable energy efficiency in PCP sharing networks.
Dec 1, 2021·2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)
P2P Botnet is famous for the resilience against termination. However, its dependence on Neighbor List (NL) makes it susceptible to infiltration and poison, also leading to a dearth of adequate protection of Botmaster's identity. So as to overcome these weaknesses, the novel botnet infrastructure combined with blockchain emerges. But due to some flaws such like high latency and expensive transactions fees on blockchain, these new schemes can't satisfy the need of constructing hyper large-scale botnet in practice. We propose ZombieCoin3.0, a Botnet underlying overlay leveraging IoT devices to be maintainers and integrated with Distributed Ledger Technology (DLT), which is able to deploy bots fully on blockchain. And it is versatile for file transfer, data feedback and other command and control scenarios that many contemporaries are impotent to cope with. Our proposal eliminates the P2P botnets' dependence on NL and the bottlenecks that other blockchain combined botnets have. Experiments' results authenticated that the effectiveness of our proposal as well as low latency of communication and nearly zero overhead of cost other comparatives unable to attain are achieved.
In recent years, blockchain-based cryptocurren-cies have attracted much attention. Attacks targeting cryptocurrencies and related services directly profit an attacker if successful. Related studies have reported attacks targeting configuration-vulnerable nodes in Ethereum using a method called honeypots to observe malicious user attacks. They have analyzed 380 million observed requests and showed that attacks had to that point taken at least 4193 Ether. However, long-term observations using honeypots are difficult because the cost of maintaining honeypots is high. In this study, we analyze the behavior of malicious users using our honeypot system. More precisely, we clarify the pre-investigation that a malicious user performs before attacks. We show that the cost of maintaining a honeypot can be reduced. For example, honeypots need to belong in Ethereum's P2P network but not to the mainnet. Further, if they belong to the testnet, the cost of storage space can be reduced.
The growing popularity of Blockchain networks attracts also malicious and hacking users. Effectively detecting inappropriate and malicious activity should thus be a top priority for safeguarding blockchain networks and services. Blockchain behavior analysis can be used to detect unusual account activities or time periods with network-wide irregular properties. Thus, optimized anomaly detection based on historical data is an essential task for securing transactions and services. However, processing the complete blockchain history can be slow and costly due to its large size and rapid growth. In this paper we suggest addressing this challenge by analyzing summarized blocks data structures, called sketches, rather than the entire blockchain. Sketches are common data structures used in computer systems and blockchain networks, to allow compact data representation while supporting efficient executions of particular queries. We study how sketches can be used to detect suspicious accounts or time periods without the need to maintain or go through the entire blockchain data. We design solutions for the major known attacks and conduct experiments to evaluate them based on real Ethereum data. We compare the accuracy, run-time and memory usage of our algorithms with traditional detection algorithms relying on the complete blockchain data. Our results indicate that sketch-based anomaly detection methods can provide a practical scalable solution for detecting anomalies in blockchain networks.
Igor D. Alvarenga, Gustavo F. Camilo, Lucas Airam C. de Souza, Otto Carlos M. B. Duarte
The rise of 5G mobile broadband networks creates new possibilities for the Internet of Things. Billions of devices will provide comprehensive services, including e-health applications, smart grids, and industry 4.0. Distributed ledger technologies solve most security and privacy threats of current IoT systems connected to a cloud or multi-access edge communication (MEC). Unfortunately, the volume of transactions imposed by 5G networks prevents blockchain-based solutions due to scalability issues. Nonetheless, emerging solutions based on directed acyclic graphs (DAG), still require some form of centralization or global view. This article proposes DAGSec, a hybrid distributed ledger architecture that provides a secure Internet of Things environment with high throughput and low latency. Our proposal uses directed acyclic graphs and local transaction validation instead of global transaction validation to attain a high transaction rate. Furthermore, we propose a blockchain-based witness system to approximate chronological order of independent transactions.
Blockchain technology provides a “tamper-proof distributed ledger” for its users. Typically, to ensure the integrity and immutability of the transaction data, each node in a blockchain network retains a full copy of the ledger; however, this characteristic imposes an increasing storage burden upon each node with the accumulation of data. In this paper, an off-chain solution is introduced to relieve the storage burden of blockchain nodes while ensuring the integrity of the off-chain data. In our solution, an off-chain remote DB server stores the fully replicated data while the nodes only store the commitments of the data to verify whether the off-chain data are tampered with. To minimize the influence on performance, the nodes will store data locally at first and transfer it to the remote DB server when otherwise idle. Our solution also supports accessing all historical data for newly joined nodes through a snapshot mechanism. The solution is implemented based on the Hyperledger Fabric (HLF). Experiments show that our solution reduces the block data for blockchain nodes by 93.3% compared to the original HLF and that our advanced solution enhances the TPS by 9.6% compared to our primary solution.
Jianhong Lin, Emiliano Marchese, Claudio J. Tessone, Tiziano Squartini
The Bitcoin Lightning Network (BLN) was launched in 2018 to scale up the number of transactions between Bitcoin owners. Although several contributions concerning the analysis of the BLN binary structure have recently appeared in the literature, the properties of its weighted counterpart are still largely unknown. The present contribution aims at filling this gap, by considering the Bitcoin Lightning Network over a period of 18 months, ranging from 12th January 2018 to 17th July 2019, and focusing on its weighted, undirected, daily snapshot representation - each weight representing the total capacity of the channels the two involved nodes have established on a given temporal snapshot. As the study of the BLN weighted structural properties reveals, it is becoming increasingly ‘centralized’ at different levels, just as its binary counterpart: (1) the Nakamoto coefficient shows that the percentage of nodes whose degrees/strengths ‘enclose’ the 51% of the total number of links/total weight is rapidly decreasing; (2) the Gini coefficient confirms that several weighted centrality measures are becoming increasingly unevenly distributed; (3) the weighted BLN topology is becoming increasingly compatible with a core–periphery structure, with the largest nodes ‘by strength’ constituting the core of such a network, whose size keeps shrinking as the BLN evolves. Further inspection of the resilience of the weighted BLN shows that removing such hubs leads to the network fragmentation into many components, an evidence indicating potential security threats — as the ones represented by the so called ‘split attacks’.
Blockchain-based IoT systems can manage IoT devices and achieve a high level of data integrity, security, and provenance. However, incorporating the existing consensus protocols in many IoT systems limits scalability and leads to high computational cost and network latency. We propose a hierar-chical and location-aware consensus protocol for IoI-blockchain applications inspired by the original Raft protocol to address these limitations. The proposed consensus protocol generates the consensus candidate groups based on nodes' individual reputation and distance information to elect the leader in each sub-layer blockchain and uses our threshold signature scheme to reach global consensus. Experimental results show that the proposed consensus protocol is scalable for large IoT applications and significantly reduces the communication cost, network latency, and agreement time by more than 50% compared with the Raft protocol for consensus processing.
Blockchain has been widely deployed in various sectors, such as finance, education, and public services. Since blockchain runs as an immutable distributed ledger, it has decentralized mechanisms with persistency, anonymity, and auditability, where transactions are jointly performed through cryptocurrency-based consensus algorithms by worldwide distributed nodes. There have been many survey papers reviewing the blockchain technologies from different perspectives, e.g., digital currencies, consensus algorithms, and smart contracts. However, none of them have focused on the blockchain data management systems. To fill in this gap, we have conducted a comprehensive survey on the data management systems, based on three typical types of blockchain, i.e., standard blockchain, hybrid blockchain, and DAG (Directed Acyclic Graph)-based blockchain. We categorize their data management mechanisms into three layers: blockchain architecture, blockchain data structure, and blockchain storage engine, where block architecture indicates how to record transactions on a distributed ledger, blockchain data structure refers to the internal structure of each block, and blockchain storage engine specifies the storage form of data on the blockchain system. For each layer, the works advancing the state-of-the-art are discussed together with technical challenges. Furthermore, we lay out the future research directions for the blockchain data management systems.
The progressive decentralization of web services brought a need for new instruments to support the development of P2P protocols and applications. The only tools available are network or event simulators, which help the development in artificial or extremely controlled environments. They usually provide low-level support with completely unstructured networks. LibP2P is a library that tries to solve all such problems, letting the users easily deploy nodes on the Internet. It also comes with a set of functionalities, to solve the most important problems of P2P networks, such as NAT traversal, peer and content discovery and routing, and much more. In this paper, we employ LibP2P to implement min-bitcoin, a minimal version of the protocol used by the Bitcoin network to exchange the blocks. We evaluate our implementation to assess the applicability of LibP2P in a real-life blockchain scenario. The evaluation uncovers that setting up communication channels is time-consuming, but data transfers are fast. Additionally, LibP2P efficiently manages cases in which nodes are behind a NAT, under VPN, or in geographically distant places.
Joachim Neu, Srivatsan Sridhar, Lei Yang, David Tse · 5 authors
Spamming attacks are a serious concern for consensus protocols, as witnessed by recent outages of a major blockchain, Solana. They cause congestion and excessive message delays in a real network due to its bandwidth constraints. In contrast, longest chain (LC), an important family of consensus protocols, has previously only been proven secure assuming an idealized network model in which all messages are delivered within bounded delay. This model-reality mismatch is further aggravated for Proof-of-Stake (PoS) LC where the adversary can spam the network with equivocating blocks. Hence, we extend the network model to capture bandwidth constraints, under which nodes now need to choose carefully which blocks to spend their limited download budget on. To illustrate this point, we show that 'download along the longest header chain', a natural download rule for Proof-of-Work (PoW) LC, is insecure for PoS LC. We propose a simple rule 'download towards the freshest block', formalize two common heuristics 'not downloading equivocations' and 'blocklisting', and prove in a unified framework that PoS LC with any one of these download rules is secure in bandwidth-constrained networks. In experiments, we validate our claims and showcase the behavior of these download rules under attack. By composing multiple instances of a PoS LC protocol with a suitable download rule in parallel, we obtain a PoS consensus protocol that achieves a constant fraction of the network's throughput limit even under worst-case adversarial strategies.
Jiarui Zhang, Yukun Cheng, Xiaotie Deng, Bo Wang · 7 authors
Blockchain protocols require nodes to verify all received transactions before forwarding them. However, massive spam transactions cause the participants in blockchain systems to consume many resources in verifying and propagating transactions. This paper proposes a reputation-based mechanism to increase the efficiency of processing transactions by considering the reputations of the sending nodes. Reputations are in turn adjusted based on the quality of transaction processing. Our proposed reputation-based mechanism offers three main contributions. First, we modify the verification strategy so that nodes set a probability of verifying a received transaction considering the likelihood of it being spam: transactions from a node with a low reputation have a high probability of being verified. Second, we optimize the transaction forwarding protocol to reduce propagation delay by prioritizing forwarding transactions to reputable receivers. Third, we design a data request protocol that provides alternative data exchange methods for nodes with different reputations. A series of simulations demonstrate the performance of our reputation-based mechanism.
The Ethereum ecosystem was maintained by a distributed global network of computers that required massive amounts of computational power. Previous work on estimating the energy use and emissions of the Ethereum network has relied on top-down economic analysis and rough estimates of hardware efficiency and emissions factors. In this work we provide a bottom-up analysis that works from hashrate to an energy usage estimate, and from mining locations to an emissions factor estimate, and combines these for an overall emissions estimate. We analyze the entire history of PoW Ethereum, from creation to the merge.
Security and privacy are the primary concerns for IoT devices but because of their inherent limitation both in terms of processing and energy, IoT devices cannot be deployed at their full scale. To alleviate such security and privacy issues, the interaction of blockchain with IoT systems has acquired significant attention these days because blockchain has presented an underlying mechanism of immutability, audibility, and transparency for data storage. However due to the intrinsic nature of a blockchain containing complex mathematical proof concepts such as Merkle Hash Tree and Proof of Work (PoW) which demands high computation power making it less viable for IoT devices to be connected with. To overcome these issues, a novel scheme is proposed in this paper, which deploys private by design based blockchain architecture for IoT devices using low complex consensus algorithm and low computation cryptographic mechanism which suits best for IoT devices to address the privacy concerns. Unlike the traditional blockchain network in which every node maintained a copy of the transaction, we have proposed a new architecture in which block validation and block generation logic has been modified so that a transaction will be limited to the trusted recipient only. The proposed scheme outperforms the contemporary approaches both in terms of throughput and latency as observed through simulation results as well as maintaining the privacy concerns which will encourage the actual implementation of IoT applications in the real world. Moreover, the evaluation analysis demonstrate that the approach has major potential in a trusted network computing system and provides a substantial secure environment for IoT users.
Tharindu Ranathunga, Ramona Marfievici, Alan McGibney, Susan Rea
This paper presents a decentralized district energy management platform leveraging permissioned Blockchain, Smart Contracts, IoT, and Cloud Computing. This platform facilitates digitizing assets and data in a decentralized energy ecosystem in a trusted manner without a central point of authority, enabling the implementation of distributed applications to create new value-added services. As part of the distributed application design, this paper investigates Blockchain integration and trust aspects. Different Blockchain configurations are deployed and analyzed under real-world operating conditions, using a Blockchain network based on the Hyperledger Fabric framework. Our analysis shows that the platform can handle up to 150 transactions per second with a 0.5 second latency under the baseline configurations provided. The paper further investigates strategies to improve scalability to meet future application requirements.
Aishah Abdullah ALFRHAN, Tarek Moulahi, Abdulatif Alabdulatif
Over the last few years, there has been a great interest in the Internet of Things (IoT). This is mainly because the IoT interacts directly with people's everyday lives in critical applications, such as in smart homes and healthcare applications. IoT devices typically have a resource-constrained architecture, rendering them vulnerable to cyberattacks. Accordingly, smart devices and stored data need to be secured through lightweight and energy-efficient security solutions, which have been identified as the main challenge facing adoption of IoT systems. To address this problem, a disruptive technology (blockchain) has been foreseen by the industry and research community as being able to deliver secure, fast, reliable, and transparent solutions for IoT systems. Hence, this work investigates the adoption of lightweight blockchain technology, mainly as a method of securing IoT systems. Because hashing plays a major role in creating a robust blockchain structure, we select a number of different hash techniques to be executed on a Raspberry Pi device. In summation, this work provides a numerical study to evaluate the performance of well-known hash functions that can be used for lightweight blockchain-based IoT.
Xiaoqing Wang, Chunping Wang, Kun Zhou, Hongbing Cheng
With the continuous development of blockchain technology, Bitcoin as the first cryptocurrency has drawn massive attention from various sectors. Bitcoin on-chain data storage is over 338GB as of September 1, 2021. According to the exponential growth trend of block data, the size of a Bitcoin full node will exceed 500GB in two years. The huge storage problem makes it difficult for general users to store complete Bitcoin data conveniently, which weakens the decentralization capability of Bitcoin network. In this work, we propose an efficient storage scheme (ESS) based on the distribution characteristics of the unspent transaction outputs in Bitcoin network. ESS sets a UTXO-weight for each block. According to UTXO-weight, it dynamically prunes the blocks which have lower query frequency, improving the scalability of the Bitcoin network. When a new block is generated, ESS enables joining nodes to verify most of the transaction inputs instantly. Only a small amount of transaction outputs of older blocks need to be retrieved from the full node for payment verification. Experimental results demonstrated that ESS can reduce the size of a normal node in current Bitcoin network by about 82.14% at a low communication cost.
Being the major disruptive technology in current era, Blockchain is becoming the prime choice for researchers and businesses. Consensus layer acts a backbone of any blockchain application; therefore to increase the performance of a blockchain ecosystem one should need to optimize the underlying consensus method. As almost every consensus method implemented in past poses limitations in terms of low scalability, high resource requirements, low decentralization and public-private tradeoff, there is a need to have an effective consensus protocol. Therefore, we presented a literature review of recent consensus protocols to find their applicability in IoT integration in this paper. We also described some future directions based on the literature being analyzed that would intend to serve as an effective guideline for to perform research in order to improve performance of a blockchain system.
Abstract Bitcoin is a popular decentralized cryptocurrency, and the Bitcoin network is essentially an unstructured peer-to-peer (P2P) network that can synchronize distributed database of replicated ledgers through message broadcasting. In the Bitcoin network, the average clustering coefficient of nodes is very high, resulting in low message propagation efficiency. In addition, average node degree in the Bitcoin network is also considerably large, causing high message redundancy when nodes use the gossip protocol to broadcast messages. These may affect message propagation speed, hindering Bitcoin from being applied to scenarios of high transactional throughputs. To illustrate, we have collected single-hop propagation data of transactions of 366 blocks from Bitcoin Core. The analysis results show that transaction verification and network delay are two major causes of low transaction propagation efficiency. In this paper, we propose a novel P2P network structure, called local clique network (LCN), for message broadcasting in the Bitcoin network. Specifically, to reduce transaction validation latency and message redundancy, in LCN local nodes (logically) form cliques, and only a few nodes in a clique broadcast messages to the other cliques, instead of each node sending messages to its neighboring nodes. We have conducted extensive experiments, and the results show that message redundancy is low in LCN, and message propagation speed increases significantly. Meanwhile, LCN exhibits excellent robustness when average node degree remains high in the Bitcoin network.
Energy networks are developing into more decentralized energy storage systems, adapted to heterogeneous yet competitive energy sources. To facilitate peer-to-to-peer energy transactions, we will introduce microgrids into the mix. Some see blockchains or distributed ledgers as a new and useful technology for energy companies, as well as for startups, government entities, and academia. A number of different industry sectors around the world are very enthusiastic about blockchains, believing they could bring dramatic changes. Blockchains promise to be highly transparent, impossible to falsify, and security-tamperproof, particularly when employed in tandem with smart contracts. For the final step, we extensively study blockchain’s literature and cases in order to educate the new and cutting-edge. Blockchain activities and projects are compiled and disseminated in this work to inform readers of innovative, scholarly, and theoretical research in the energy sector.
This paper investigates the problem of distributed storage of electronic documents (both metadata and files) in decentralized blockchain-based b2b systems (DApps). The need to reduce the cost of implementing such systems and the insufficient elaboration of the issue of storing big data in DLT are considered. An approach for building such systems is proposed, which allows optimizing the size of the required storage (by using Erasure coding) and simultaneously providing secure data storage in geographically distributed systems of a company, or within a consortium of companies. The novelty of this solution is that we are the first who combine enterprise DLT with distributed file storage, in which the availability of files is controlled. The results of our experiment demonstrate that the speed of the described DApp is comparable to known b2c torrent projects, and subsequently justify the choice of Hyperledger Fabric and Ethereum Enterprise for its use. Obtained test results show that public blockchain networks are not suitable for creating such a b2b system. The proposed system solves the main challenges of distributed data storage by grouping data into clusters and managing them with a load balancer, while preventing data tempering using a blockchain network. The considered DApps storage methodology easily scales horizontally in terms of distributed file storage and can be deployed on cloud computing technologies, while minimizing the required storage space. We compare this approach with known methods of file storage in distributed systems, including central storage, torrents, IPFS, and Storj. The reliability of this approach is calculated and the result is compared to traditional solutions based on full backup.