A Novel Data-Driven Evaluation Framework for Fork after Withholding Attack in Blockchain Systems

Abstract

In the blockchain system, mining pools are popular for miners to work collectively and obtain more revenue. Nowadays, there are consensus attacks that threaten the efficiency and security of mining pools. As a new type of consensus attack, the Fork After Withholding (FAW) attack can cause huge economic losses to mining pools. Currently, there are a few evaluation tools for FAW attacks, but it is still difficult to evaluate the FAW attack protection capability of target mining pools. To address the above problem, this paper proposes a novel evaluation framework for FAW attack protection of the target mining pools in blockchain systems. In this framework, we establish the revenue model for mining pools, including honest consensus revenue, block withholding revenue, successful fork revenue, and consensus cost. We also establish the revenue functions of target mining pools and other mining pools, respectively. In particular, we propose an efficient computing power allocation optimization algorithm (CPAOA) for FAW attacks against multiple target mining pools. We propose a model-solving algorithm based on improved Aquila optimization by improving the selection mechanism in different optimization stages, which can increase the convergence speed of the model solution and help find the optimal solution in computing power allocation. Furthermore, to greatly reduce the possibility of falling into local optimal solutions, we propose a solution update mechanism that combines the idea of scout bees in an artificial bee colony optimization algorithm and the constraint of allocating computing power. The experimental results show that the framework can effectively evaluate the revenue of various mining pools. CPAOA can quickly and accurately allocate the computing power of FAW attacks according to the computing power of the target mining pool. Thus, the proposed evaluation framework can effectively help evaluate the FAW attack protection capability of multiple target mining pools and ensure the security of the blockchain system.

A Repeated Game-Based Distributed Denial of Service Attacks Mitigation Method for Mining Pools

“…Therefore, the pool's returns first increase with w and then decrease as w increases to an extreme value. In the results of the mixed strategy experiments, the returns of the mining pool also increase with w finally reaching an extreme value at approximately equal to 0.43, and finally, gradually the returns decrease with w. This is consistent with the change in returns embodied in Equation (5). Finally, we find that the mining pool is in a good network state when w is approximately equal to 0.83.…”

“…This suggests that the optimal mixing probability multiplied by the optimal gain for all attack scenarios is the optimal total gain for the medium network. Then, we substitute the specific expression of p 1 in Equation ( 3) to obtain the specific value R M of the optimal return of the mixed strategy, as described in Equation (5).…”

“…The consensus algorithm [1], specifically the Proof of Work (PoW) [2], is a cornerstone of blockchain technology, ensuring data consistency and system consensus [3]. However, PoW's reliance on computational power exposes blockchain to security risks, including selfish mining (SM) attacks [4], block withholding (BWH) attacks [5], and Distributed Denial of Service (DDoS) attacks [6]. SM attacks gain additional revenue by creating redundant private chains in addition to the public chain [7].…”

K-Anonymity Privacy Protection Algorithm for Multi-Dimensional Data against Skewness and Similarity Attacks

“…Attackers can use public data to analyze sensitive personal information, which may result in privacy disclosure. It is necessary for both data owners and data publishers to protect privacy in data publication and data use [ 5 , 6 , 7 ]. Thus, a publicly published privacy protection method for multi-dimensional data is needed to prevent the privacy disclosure of multiple sensitive attributes.…”

Critical Controlling for the Network Security and Privacy Based on Blockchain Technology: A Fuzzy DEMATEL Approach

“…Some studies focused on traditional security measures to secure communication across devices, such as authentication, privacy, and trust management [16][17][18]. They are, however, insufficient since data must be safely transmitted to the correct location, at the proper time, and in a valid format [19][20][21]. Others focus on the literature surrounding the use of blockchains.…”