SDoS: Selfish Mining-Based Denial-of-Service Attack

Wang, Qiuhua; Xia, Tianyu; Wang, Dong; Ren, Yizhi; Miao, Gongxun; Choo, Kim‐Kwang Raymond

doi:10.1109/tifs.2022.3202696

Cited by 10 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hayat et al [11] proposed a multilayer combination attack method (ML-DDoS) based on DDoS attacks and smart contracts, which was designed to obtain more rewards from attackers. Wang et al [12] designed a new mining attack, a selfish mining-based denial-of-service (SDoS) attack, which targeted the blockchain system based on the PoW mechanism and analyzed the gains and strategies of the attacker and the honest miners through game theory. Mirkin et al [13] implemented a novel DDoS attack based on blockchain incentives called blockchain denial of service (BDoS).…”

Section: The Ddos-based Combination Attacks In Blockchain Systemsmentioning

confidence: 99%

“…Academics have proposed many methods to solve the DDoS attack problem in the blockchain network layer. At present, these methods can be mainly divided into the following categories: DDoS defense methods combined with blockchain technology, DDoS combination attacks combined with other blockchain attacks, and static game strategies based on the blockchain mining pool [10][11][12][13][14][15][16][17]. Among these existing studies, the use of a static game approach to mitigate DDoS attacks is the most effective [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analyzing Miners’ Dynamic Equilibrium in Blockchain Networks under DDoS Attacks

Liu,

Huang,

Wang

et al. 2023

Electronics

View full text Add to dashboard Cite

Proof of work (PoW) is one of the most widely used consensus algorithms in blockchain networks. It mainly uses the competition between mining nodes to obtain block rewards. However, this competition for computational power will allow malicious nodes to obtain illegal profits, bringing potential security threats to blockchain systems. A distributed denial of service (DDoS) attack is a major threat to the PoW algorithm. It utilizes multiple nodes in the blockchain network to attack honest miners to obtain illegal rewards. To solve this problem, academia has proposed a DDoS attack detection mechanism based on reinforcement learning methods and static game modeling methods based on mining pools. However, these methods cannot effectively make miners choose the strategy with the best profit over time when facing DDoS attacks. Therefore, this paper proposes a dynamic evolutionary game model for miners facing DDoS attacks under blockchain networks to solve the above problems for the first time. We address the model by replicating the dynamic equation to obtain a stable solution. According to the theorem of the Lyapunov method, we also obtain the only stable strategy for miners facing DDoS attacks. The experimental results show that compared with the static method, the dynamic method can affect game playing and game evolution over time. Moreover, miners’ strategy to face DDoS attacks gradually shifts from honest mining to launching DDoS attacks against each other as the blockchain network improves.

show abstract

Section: The Ddos-based Combination Attacks In Blockchain Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analyzing Miners’ Dynamic Equilibrium in Blockchain Networks under DDoS Attacks

Liu,

Huang,

Wang

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

“…However, these systems suffer hash computation overheads due to the fact thatPoW is used in the distributed shard grouping process to verify identities. However, the SSChain blockchain uses the current PoW algorithm for shard consensus and, because of its non-reshuffled structure, supports sharding of both transactions and states [34,35,36]. The security of the root chain may also be seriously compromised since SSChain operates on two separate chain architectures.…”

Section: Introductionmentioning

confidence: 99%

LQMPCS: Design of a Low-Complexity Q-Learning Model based on Proof-of-Context Consensus for Scalable Side Chains

Pandey,

Misal

2023

IJRITCC

View full text Add to dashboard Cite

Single-chained blockchains are being rapidly replaced by sidechains (or sharded chains), due to their high QoS (Quality of Service), and low complexity characteristics. Existing sidechaining models use context-specific machine-learning optimization techniques, which limits their scalability when applied to real-time use cases. Moreover, these models are also highly complex and require constant reconfigurations when applied to dynamic deployment scenarios. To overcome these issues, this text proposes design of a novel low-complexity Q-Learning Model based on Proof-of-Context (PoC) consensus for scalable sidechains. The proposed model initially describes a Q-Learning method for sidechain formation, which assists in maintaining high scalability even under large-scale traffic scenarios. This model is cascaded with a novel Proof-of-Context based consensus that is capable of representing input data into context-independent formats. These formats assist in providing high-speed consensus, which is uses intent of data, instead of the data samples. To estimate this intent, a set of context-based classification models are used, which assist in representing input data samples into distinctive categories. These models include feature representation via Long-Short-Term-Memory (LSTM), and classification via 1D Convolutional Neural Networks (CNNs), that can be used for heterogeneous application scenarios. Due to representation of input data samples into context-based categories, the proposed model is able to reduce mining delay by 8.3%, reduce energy needed for mining by 2.9%, while maintaining higher throughput, and lower mining jitters when compared with standard sidechaining techniques under similar use cases.

show abstract