Malicious Miners Research Articles

Statistical detection of selfish mining in proof-of-work blockchain systems

The core of many cryptocurrencies is the decentralised validation network operating on proof-of-work technology. In these systems, validation is done by so-called miners who can digitally sign blocks once they solve a computationally-hard problem. Conventional wisdom generally considers this protocol as secure and stable as miners are incentivised to follow the behaviour of the majority. However, whether some strategic mining behaviours occur in practice is still a major concern. In this paper we target this question by focusing on a security threat: a selfish mining attack in which malicious miners deviate from protocol by not immediately revealing their newly mined blocks. We propose a statistical test to analyse each miner’s behaviour in five popular cryptocurrencies: Bitcoin, Litecoin, Monacoin, Ethereum and Bitcoin Cash. Our method is based on the realisation that selfish mining behaviour will cause identifiable anomalies in the statistics of miner’s successive blocks discovery. Secondly, we apply heuristics-based address clustering to improve the detectability of this kind of behaviour. We find a marked presence of abnormal miners in Monacoin and Bitcoin Cash, and, to a lesser extent, in Ethereum. Finally, we extend our method to detect coordinated selfish mining attacks, finding mining cartels in Monacoin where miners might secretly share information about newly mined blocks in advance. Our analysis contributes to the research on security in cryptocurrency systems by providing the first empirical evidence that the aforementioned strategic mining behaviours do take place in practice.

BitTrace

Bitcoin is a digital currency system built on the foundation of fairness. However, some malicious miners, driven by their own interests, employ unfair tactics such as selfish mining to compete, which disregard the legitimate miners' investments in computational power and energy consumption. In order to assess the efficiency of the Bitcoin system in real-time and promptly detect malicious miners in the network, this paper proposes a data collection framework called BitTrace, which addresses the issues of low efficiency, lack of timeliness, and data loss in traditional data collection frameworks. BitTrace enables real-time collection and analysis of the blockchain formation process, storing it as structured data. Furthermore, the paper discusses factors that influence the efficiency of data collection and proposes a topological control scheme based on the DPC algorithm to enhance the integrity and efficiency of data collection. Researchers can explore various research areas and applications, such as selfish mining detection and legitimate mining strategy research.

The Threat of Disruptive Jamming to Blockchain-Based Decentralized Federated Learning in Wireless Networks.

Machine learning techniques have attracted considerable attention for wireless networks because of their impressive performance in complicated scenarios and usefulness in various applications. However, training with and sharing raw data obtained locally from each wireless node does not guarantee privacy and requires a large communication overhead. To mitigate such issues, federated learning (FL), in which sharing parameters for model updates are shared instead of raw data, has been developed. FL has also been studied using blockchain techniques to efficiently perform learning in distributed wireless systems without having to deploy a centralized server. Although blockchain-based decentralized federated learning (BDFL) is a promising technique for various wireless sensor networks, malicious attacks can still occur, which result in performance degradation or malfunction. In this study, we analyze the impact of a jamming threats from malicious miners to BDFL in wireless networks. In a wireless BDFL system, it is possible for malicious miners with jamming capability to interfere with the collection of model parameters by normal miners, thus preventing the victim miner from generating a global model. By disrupting normal miners participating in BDFL systems, malicious miners with jamming capability can more easily add malicious data to the mainstream. Through various simulations, we evaluated the success probability performance of malicious block insertion and the participation rate of normal miners in a wireless BDFL system.

Analysis of interaction between miner decision making and user action for incentive mechanism of bitcoin blockchain

In Bitcoin blockchain, miner nodes are likely to choose transactions with high fee to be included in a block. This makes transactions with high fee being processed fast, affecting the amount of transaction fee that users want to pay. The reward for a winning miner consists of transaction fee and newly issued coins, and hence the amount of newly issued coins also affects the miner decision to participate in the mining competition. In addition, mining reward also affects the total hash computing power, which plays an important role of Bitcoin security for reducing the success probability of security attack by a malicious miner. In this paper, we develop a mathematical model for analyzing the interaction between miner decision making and user actions in terms of transaction fees, transaction-confirmation time, and security. We analyze the transaction-inclusion process with queueing theory, while decision making processes of miners and users are analyzed in the context of Nash equilibrium. The numerical examples show how the mining costs and newly issued coins affect miner decision making.

An Approach for Blockchain Pool Mining Employing the Consensus Protocol Robust against Block Withholding and Selfish Mining Attacks

This paper proposes an approach for pool mining in public blockchain systems based on the employment of a recently reported consensus protocol with the puzzle based on a symmetric encryption that provides an energy–space trade-off and reduces energy consumption. The proposed architecture employs a pseudo-symmetric allocation of the resources for the blockchain consensus protocol and provides protection against certain malicious actions of the pool members, as well as a miner’s opportunity for selecting the resources required for participation in the consensus protocol. Given that the considered consensus protocol employs two resources, the proposed architecture uses this two-dimensional nature to provide resistance against block withholding and selfish mining attacks, as well as a reduction in energy spending as a trade-off with the employment of certain memory resources. The high resistance of the proposed pool mining approach against the considered attacks appears to be a consequence of the success probability of the pool in comparison with the success probability of malicious miners. Assuming appropriate selection of the puzzle hardness, the probability that malicious miners can solve the puzzle without the support of the pool manager can be arbitrarily small. Implementation of the proposed approach on a modified Ethereum platform and experimental evaluation issues have also been reported. The conceptual novelty of the proposed pool mining approach is the following: Instead of separation of the blockchain consensus protocol and control of pool miners honest work, this paper proposes an approach where honest work of miners and pool managers is provided by a dedicated application of the considered consensus protocol. Advantages of the proposal in comparison with the previously reported ones include the following: (i) high resistance against block withholding and selfish mining attacks without an additional security procedure; (ii) reduction in the energy required, and at the same time preservationthe security of the consensus protocol; (iii) flexibility of the pool miners regarding selection of the resources that should be employed providing a trade-off between required energy and memory resources. The proposed architecture was implemented employing a dedicated modification of the Ethereum platform and the performed experiments confirmed the feasibility and effectiveness of the proposal.

FAWPA: A FAW Attack Protection Algorithm Based on the Behavior of Blockchain Miners.

Blockchain has become one of the key techniques for the security of the industrial internet. However, the blockchain is vulnerable to FAW (Fork after Withholding) attacks. To protect the industrial internet from FAW attacks, this paper proposes a novel FAW attack protection algorithm (FAWPA) based on the behavior of blockchain miners. Firstly, FAWPA performs miner data preprocessing based on the behavior of the miners. Then, FAWPA proposes a behavioral reward and punishment mechanism and a credit scoring model to obtain cumulative credit value with the processed data. Moreover, we propose a miner’s credit classification mechanism based on fuzzy C-means (FCM), which combines the improved Aquila optimizer (AO) with strong solving ability. That is, FAWPA combines the miner’s accumulated credit value and multiple attack features as the basis for classification, and optimizes cluster center selection by simulating Aquila’s predation behavior. It can improve the solution update mechanism in different optimization stages. FAWPA can realize the rapid classification of miners’ credit levels by improving the speed of identifying malicious miners. To evaluate the protective effect of the target mining pool, FAWPA finally establishes a mining pool and miner revenue model under FAW attack. The simulation results show that FAWPA can thoroughly and efficiently detect malicious miners in the target mining pool. FAWPA also improves the recall rate and precision rate of malicious miner detection, and it improves the cumulative revenue of the target mining pool. The proposed algorithm performs better than ND, RSCM, AWRS, and ICRDS.

Towards Detection of Selfish Mining Using Machine Learning

Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. The selfish miners continue to mine on their private chain while the honest miners waste resources mining on a shorter chain. According to the blockchain protocol, a longer chain takes precedent and shorter chains are discarded which allows the selfish miners to gain an advantage by keeping their chain secret. This attack can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from cryptocurrency exchanges. Several of these attacks were launched in 2018 and 2019 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but the effectiveness of the fixes is currently unknown. Although this attack is possible against both Proof-of-Work and Proof-of-Stake blockchains, this research concentrates on detection in Proof-of-Work blockchains. As is difficult to evaluate security advances in the real-time blockchain, it is imperative to focus on simulation to evaluate blockchain security properties. To this end, we extend a blockchain simulator and add the ability to simulate selfish mining attacks. Several existing simulators are examined before choosing SimBlock for this research. Our goal is to identify the factors that identify selfish mining. Using existing research, we choose several factors that could identify an attack in an unlaunched state, an active state, or historically. We plan to use simulated data to train a machine learning model to detect selfish mining. Using the modified simulator, we generate training and test data for unlaunched and active attacks. For historical attacks, we will use historical data from known selfish mining attacks. While some existing research has examined the detection of selfish mining, it only examines active attacks. In this paper, we seek to lay the groundwork for future research into detecting attacks that are unlaunched, active, or historical.

On the Use of Proof-of-Work in Permissioned Blockchains: Security and Fairness

In permissioned blockchains, a set of identifiable miners validates transactions and creates new blocks. In scholarship, the proposed solution for the consensus protocol is usually inspired by the Byzantine fault tolerance (BFT) based on voting rather than the proof-of-work (PoW). The advantage of PoW with respect to BFT is that it allows the final user to evaluate the cost required to change a confirmed transaction without the need to trust the consortium of miners. In this paper, we analyse the problems that arise from the application of PoW in permissioned blockchains. In standard PoW, it may be easy for colluded miners to temporarily reach 50% of the total hash power (HP). Moreover, since mining rewards are not usually expected in permissioned contexts, the problem of balancing the computational efforts among the miners becomes crucial. We propose a solution based on a sliding window algorithm to address these problems and analyse its effectiveness in terms of fairness and security. Furthermore, we present a quantitative, analytical model in order to assess its capacity to balance the hash power provided by heterogeneous miners. Our study considers the trade-off between the need to trust the entire consortium of miners guaranteed by the global HP invested by the mining process and the need to prevent collusion among malicious miners aimed at reaching 50% of the total HP. As a result, the model can be used to find the optimal parameters for the sliding window protocol.

Block diffusion delay attack and its countermeasures in a Bitcoin network

SummaryIn the Bitcoin system, transactions and their collections (i.e., blocks) are distributed over a peer‐to‐peer (P2P) network (i.e., Bitcoin network) constructed by participating nodes. Each node maintains a distributed ledger (i.e., blockchain) consisting of retrieved blocks. Therefore, speedy block distribution over the Bitcoin network is essential for all nodes to reach a global consensus on the blockchain. On the other hand, Bitcoin clients are developed as open source software, and thus they can be modified by malicious users. Existing work has pointed out that an attacker can delay the block propagation between neighboring nodes by exploiting the regular timeout mechanism for unexpected slow block transfer caused by temporal network trouble. In this paper, we focus on block diffusion delay attacks, where multiple attackers collude with a specific miner (i.e., a special node that creates new blocks and broadcasts these blocks to the other miners) to disturb the propagation of blocks generated by competing miners. Through simulation experiments, we first reveal that about 30% of honest nodes cannot normally retrieve a block when there are only 1% of the nodes in the system are high‐degree adversary nodes in the system. This indicates that the malicious miner colluding with the attackers can intentionally delay the diffusion of the block mined by the competing miner, so as to win the competitive block diffusion even if it loses at the competitive block mining. To alleviate the block diffusion delay attack, we propose two kinds of countermeasures: a proactive approach that is a speedy recovery method from the interruption by adjusting the timeout value and a reactive approach that is a block retrieval node selection method based on the past download rate from each neighbor. Through simulation experiments, we show the countermeasures can effectively alleviate the risk.

Detection of Malicious Miner in Block chain Network

The block chain innovation has developed as an alluring answer for address execution and security issues in disseminated frameworks. Block chain’s open and dispersed friend topper record ability benefits distributed computing administrations which require capacities, for example, guaranteed information provenance, examining, the board of advanced resources, and disseminated agreement. Block chain’s fundamental agreement system permits to construct a carefully designed condition, where exchanges on any advanced resources are confirmed by set of genuine members or excavators. With utilization of solid cryptographic strategies, blocks of exchanges are binded together to empower permanence on the records. Not with standing, accomplishing agreement requests computational force from the diggers in return of attractive prize. Along these lines, eager diggers consistently attempt to abuse the framework by increasing their mining power. Right now, first talk about block chain’s capacity in giving guaranteed information provenance in cloud and present vulnerabilities in block chain cloud. Actualized at the mining pool chief, Silent Time stamping doesn’t require organizing nor any conduct or usage changes in the diggers; the absence of the execution overheads recognize Silent Time stamping from different plans which have been proposed yet had constrained achievement by and by. We break down the ideal assailant conduct against Silent Time stamping and the adequacy of Silent Time stamping against FAW assault. Quiet Time stamping adequately invalidates the prize addition of the FAW assault and lessens the ideal FAW aggressor technique to be either the problematic block-retaining assault (which never presents the retained block in the undermined pool and gives constrained motivators to a normal assailant) or legitimate mining.

A Novel PoW Scheme Implemented by Probabilistic Signature for Blockchain

PoW (Proof of Work) plays a significant role in most blockchain systems to grant an accounting right over decentralized participants and ensure tamper resistance. Though hash functions are generally exploited for PoW due to their merits on summering, anti-collision, and irreversibility, they cannot certify that the bookkeeper is exactly the worker. Thereafter, such insistence may lead to abuse or even embezzlement of computing power for the benefit of malicious miners. To preserve the functionality of PoW but also bind the miners’ signing keys with their works, we build a post-quantum PoW scheme by changing the approximate closest vector norm for probabilistic NTRUSign. Different from the schemes based on hash functions, our scheme takes signing as the proof of work where signature verification is just the evidence of block reward. We also presented a method to adjust the difficulty of signing by modifying the probability of generating a correct signature. The performance of our scheme is also analyzed theoretically and experimentally, which implies its practicability and advantages.

Availability analysis of a permissioned blockchain with a lightweight consensus protocol

This paper offers a novel approach to the evaluation of provenance blockchain security and reliability using analytical methods for assessing system availability against malicious miner DoS attacks. In particular, we present the reliability and availability analysis of the LightWeight Mining (LWM) protocol for securing data provenance. Our analysis shows the reliability of the protocol and its ability to protect against malicious miner DoS attacks. We use digital signatures to prove integrity and non-repudiation of messages passing the system. We describe system behaviors using communicating sequential processes (CSP) to check for synchronization within a number of concurrent processes. Queuing theory is used to determine the average waiting time for client blockchain transactions when malicious miners work to slow the system. CSP and queuing theory jointly test the blockchain’s ability to make progress despite the presence of malicious miners. Further, the methodology described can be extended to other blockchain applications. Additional threats, beyond the malicious miner DoS attack, are reserved for future work.

Permissionless proof‐of‐reputation‐X: A hybrid reputation‐based consensus algorithm for permissionless blockchains

AbstractOver the past years, blockchain technology has become more and more interesting since its ability to carry out transactions without any mediator. To ensure the transactions' reliability, consensus algorithms are adopted by blockchain technology. However, due to the failure of consensus algorithms in managing nodes' identities, blockchain technology is considered inappropriate for many applications. In this article, we propose the permissionless proof‐of‐reputation‐X (PL‐PoRX) that upgrades an existing consensus algorithm, the proof‐of‐reputation‐X (PoRX). PL‐PoRX replaces the trusted identity database in PoRX with a new admission process to make the algorithm suitable for permissionless blockchains, while maintaining PoRX's reputation mechanism. Several experiments are conducted to show the efficiency of our approach under different scenarios. We also debate the security model of the new protocol and study its time complexity. The results show that PL‐PoRX decreases the number of blocks issued by malicious miners, and help benign miners build reputation faster.

Toward a Machine Learning and Software Defined Network Approaches to Manage Miners’ Reputation in Blockchain

In blockchain, transactions between parties are regrouped into blocks, in order to be added to the blockchain’s distributed ledger. Miners are nodes of the network that generate new blocks according to the consensus protocol. The miner that adds a valid block to the distributed ledger is rewarded. However, to find a valid block, the miner needs to solve a computationally difficult problem, which makes it difficult to a single miner to gain rewards. Therefore, miners join mining pools, where the powers’ of miners are federated to ensure stable revenues. In public blockchains, access to mining pools is not restricted, which makes mining pools vulnerable to considerable threats such as: block withholding (BWH) attacks and distributed denial of service (DDoS) attacks. In the present work, we propose a new reputation based blockchain named PoolCoin based on a distributed trust model for a mining pools. The trust model used by PoolCoin is inspired from the job market signaling model. The proposed PoolChain blockchain allows pool managers the selection of trusted miners in their mining pools, while miners are able to evaluate them. Furthermore, to detect malicious miners that claim bigger computing capacity, we also provided a machine learning module to estimate the real miners’ capacities. The efficiency of the proposed trust model is studied and the obtained simulation results are presented and discussed. Thus, the model parameters’ are optimized in order to detect and exclude misbehaving miners, while honest miners are maintained in the mining pool.

Delegated Proof of Reputation Consensus Mechanism for Blockchain-Enabled Distributed Carbon Emission Trading System

Most carbon Emission Trading Systems (ETS) rely on a centralized system to manage the transactional tasks, and are vulnerable to security threats. This article proposes a Blockchain-enabled Distributed ETS (BD-ETS) to improve the security and efficiency of the system. The BD-ETS transforms the centralized Carbon Emissions Permit (CEP) trading mode to a distributed trading system in which the trading mode is based on a smart contract performed in Hyperledger Fabric. In a smart contract, every transaction considers both the offer price and reputation value of the emitting enterprises. The voting power of the emitting enterprise is determined by its reputation value, which stems from their contributions to carbon emission reduction. To achieve consistency of every node in the CEP transactions, we propose a Delegated Proof of Reputation (DPoR) consensus mechanism. Compared to the enhanced Delegated Proof of Stake, the DPoR decreases the attack intention of malicious enterprises and performs better in finding malicious miners faster, thus improving the security of the BD-ETS. A case study and numerical simulations are developed to illustrate how the CEP trading functions, and to validate the DPoR mechanism.

Low powered blockchain consensus protocols based on consistent hash

Current blockchain consensus protocols have a triangle of contradictions in aspects of decentralization, security, and energy consumption, and cannot be synchronously optimized. We describe a design of two new blockchain consensus protocols, called “CHB-consensus” and “CHBD-consensus,” based on a consistent hash algorithm. Honest miners can fairly gain the opportunity to create blocks. They do not consume any extra computational power resources when creating new blocks, and such blocks can obtain the whole blockchain network to confirm consensus with fairness. However, malicious miners have to pay massive computational power resources for attacking the new block creation privilege or double-spending. Blockchain networks formed by CHB-consensus and CHBD-consensus are based on the same security assumption as that in Bitcoin systems, so they save a huge amount of power without sacrificing decentralization or security. We analyze possible attacks and give a rigorous but adjustable validation strategy. CHB-consensus and CHBD-consensus introduce a certification authority (CA) system, which does not have special management or control rights over blockchain networks or data structures, but carries the risk of privacy breaches depending on credibility and reliability of the CA system. Here, we analyze the robustness and energy consumption of CHB-consensus and CHBD-consensus, and demonstrate their advantages through theoretical derivation.

Trust-Based Shard Distribution Scheme for Fault-Tolerant Shard Blockchain Networks

Blockchains guarantee data integrity through consensus of distributed ledgers based on multiple validation nodes called miners. For this reason, any blockchain system can be critically disabled by a malicious attack from a majority of the nodes (e.g., 51% attack). These attacks are more likely to succeed as the number of nodes required for consensus is smaller. Recently, as blockchains are becoming too large (making them difficult to store, send, receive, and manage), sharding is being considered as a technology to help improve the transaction throughput and scalability of blockchains. Sharding distributes block validators to disjoint sets to process transactions in parallel. Therefore, the number of validators of each shard group is smaller, which makes shard-based blockchains more vulnerable to 51% attacks than blockchains that do not use sharding. To solve this problem, this paper proposes a trust-based shard distribution (TBSD) scheme that assigns potential malicious nodes in the network to different shards, preventing malicious nodes from gaining a dominating influence on the consensus of a single shard. TBSD uses a trust-based shard distribution scheme to prevent malicious miners from gathering in on one shard by integration of a trust management system and genetic algorithm (GA). First, the trust of all nodes is computed based on the previous consensus result. Then, a GA is used to compute the shard distribution set to prevent collusion of malicious miners. The performance evaluation shows that the proposed TBSD scheme results in a shard distribution with a higher level of fairness than existing schemes, which provides an improved level of protection against malicious attacks.