Node Consistency Consensus Algorithm for Malicious Node Attacks in Internet of Vehicles

doi:10.3778/j.issn.1002-8331.2209-0469

Abstract

Abstract: Aiming at the nodes in the internet of vehicles（IoV）, they are vulnerable to malicious node attacks during the consensus process, resulting in low transaction throughput and long transaction delays of the blockchain consensus algorithm. Therefore, the paper proposes a node consistency consensus algorithm for malicious node attacks in the IoV（NCCA）. Firstly, NCCA divides the network of the IoV into several cellular single regions. It determines the list of trusted nodes based on the credit score of nodes and updates the verification nodes periodically. Secondly, NCCA proposes a voting mechanism with different weights of voting types to calculate the voting number of transactions and select the set of transactions requiring consensus. It also improves the node selection of block verification in the process of consensus and selects high-credit value verification nodes to complete consensus. Finally, NCCA proposes a two-round detection mechanism of malicious nodes for the active detection of malicious node attacks, which combines multi-area cooperative detection and local detection in a single area, and implements the operations of empowering and stopping the detected nodes. Experimental results show that NCCA can efficiently detect malicious nodes and reduce the impact of poor performance nodes and malicious nodes on the efficiency of block consensus. NCCA can improve transaction throughput, reduce the average transaction delay and average node communication overhead, and realize efficient consensus under malicious node attacks.

Key words: node in IoV, consistency consensus, blockchain, consensus attack, malicious detection

摘要： 针对车联网节点在共识过程中易受恶意节点攻击，造成区块链共识算法交易吞吐率低、交易时延长等问题，提出一种面向恶意节点攻击的车联网节点共识算法（NCCA）。NCCA将车联网网络划分若干个蜂窝单区域，通过节点的信用值分数确定可信任节点列表，并定期更新验证节点。采用票型权重不同的投票机制计算交易的投票票数，从而选择出需要进行共识的交易集。改进共识过程中区块验证的节点选择，选择高信用值验证节点完成共识。针对恶意节点攻击进行主动检测，提出一种多区域协同检测和单区域内局部检测的恶意节点二轮检测机制，对检测后的节点执行赋权和停权操作。实验结果表明，NCCA能高效检测出恶意节点，并降低性能较差节点和恶意节点对区块共识效率的影响，从而提高交易吞吐量并降低平均交易时延和平均节点通信开销，实现恶意节点攻击下的高效共识。

关键词: 车联网节点, 一致性共识, 区块链, 共识攻击, 恶意检测

YANG Changchun, ZHANG Yang, CHEN Yourong, MIAO Kelei, REN Tiaojuan, WANG Zhangquan. Node Consistency Consensus Algorithm for Malicious Node Attacks in Internet of Vehicles[J]. Computer Engineering and Applications, 2023, 59(19): 229-236.

杨长春, 章阳, 陈友荣, 缪克雷, 任条娟, 王章权. 面向恶意节点攻击的车联网节点共识算法[J]. 计算机工程与应用, 2023, 59(19): 229-236.

References

[1] KANG J，XIONG Z，NIYATO D，et al.Toward secure blockchain-enabled Internet of Vehicles：optimizing consensus management using reputation and contract theory[J].IEEE Transactions on Vehicular Technology，2019，68（3）：2906-2920.
[2] LAI C，LU R，ZHENG D，et al.Security and privacy challenges in 5G-enabled vehicular networks[J].IEEE Network，2020，34（2）：37-45.
[3] 黄冬艳，李浪，陈斌，等.RBFT：基于Raft集群的拜占庭容错共识机制[J].通信学报，2021，42（3）：209-219.
HUANG D Y，LI L，CHEN B，et al.RBFT：a new Byzantine fault-tolerant consensus mechanism based on Raft cluster[J].Journal on Communications，2021，42（3）：209-219.
[4] 方燚飚，周创明，李松，等.联盟链中实用拜占庭容错算法的改进[J].计算机工程与应用，2022，58（3）：135-142.
FANG Y B，ZHOU C M，LI S，et al.Improvement of practical Byzantine fault algorithm in alliance blockchain[J].Computer Engineering and Applications，2022，58（3）：135-142.
[5] LUO Y，CHEN Y，CHEN Q，et al.A new election algorithm for DPos consensus mechanism in blockchain[C]//Proceedings of the 7th International Conference on Digital Home（ICDH），2018：116-120.
[6] XU X，ZHU D，YANG X，et al.Concurrent practical byzantine fault tolerance for integration of blockchain and supply chain[J].ACM Transactions on Internet Technology（TOIT），2021，21（1）：1-17.
[7] WANG Y，CAI S，LIN C，et al.Study of blockchains’s consensus mechanism based on credit[J].IEEE Access，2019，7：10224-10231.
[8] YOUSUF R，JEELANI Z，KHAN D A，et al.Consensus algorithms in blockchain-based cryptocurrencies[C]//Proceedings of the International Conference on Advances in Electrical，Computing，Communication and Sustainable Technologies（ICAECT），2021：1-6.
[9] SCHWARTZ D，YOUNGS N，BRITTO A.The ripple protocol consensus algorithm[J].Ripple Labs Inc White Paper，2014，5（8）：1-8.
[10] BERDIK D，OTOUM S，SCHMIDT N，et al.A survey on blockchain for information systems management and security[J].Information Processing & Management，2021，58（1）：1-28.
[11] HU W，HU Y，YAO W，et al.A blockchain-based Byzantine consensus algorithm for information authentication of the Internet of vehicles[J].IEEE Access，2019，7：139703-139711.
[12] MERSHAD K，CHEIKHROUHOU O，ISMAIL L.Proof of accumulated trust：a new consensus protocol for the security of the IoV[J].Vehicular Communications，2021，32（1）：1-19.
[13] LI C，WU H，XIONG L，et al.An IoV-PBFT consensus-based blockchain for collaborative congestion avoidance and simulation test[J].Wireless Communications and Mobile Computing，2022，9（1）：1-9.
[14] HAN R，SHAPIRO G，GRAMOLI V，et al.On the performance of distributed ledgers for internet of things[J].Internet of Things，2020，10（10）：1-12.
[15] CASTRO M，LISKOV B.Practical Byzantine fault tolerance[C]//Proceedings of the 3rd Symposium on Operating Systems Design and Implementation.New Orleans，USA：USENIX Association，1999：173-186.
[16] SAAD M，NJILLA L，KAMHOUA C，et al.Countering selfish mining in blockchains[C]//Proceedings of the International Conference on Computing，Networking and Communications（ICNC），2019：360-364.
[17] BAEK U J，JI S H，PARK J T，et al.DDoS attack detection on bitcoin ecosystem using deep-learning[C]//Proceedings of the 20th Asia-Pacific Network Operations and Management Symposium（APNOMS），2019：1-4.
[18] XU G，GUO B，SU C，et al.Am I eclipsed? a smart detector of eclipse attacks for Ethereum[J].Computers & Security，2020，88（1）：1-10.
[19] KUMAR P，KUMAR R，GUPTA G P，et al.A distributed framework for detecting DDoS attacks in smart contract-based blockchain-IoT systems by leveraging fog computing[J].Transactions on Emerging Telecommunications Technologies，2021，32（6）：1-31.
[20] 黄嘉成，许新华，王世纯.委托权益证明共识机制的改进方案[J].计算机应用，2019，39（7）：2162-2167.
HUANG J C，XU X H，WANG S C.Improved scheme of delegated proof of stake consensus mechanism[J].Journal of Computer Applications，2019，39（7）：2162-2167.
[21] LEI T，JIA X，ZHANG Y，et al.Significantly fast and robust fuzzy c-means clustering algorithm based on morphological reconstruction and membership filtering[J].IEEE Transactions on Fuzzy Systems，2018，26（5）：3027-3041.
[22] JIANG T，FANG H，WANG H.Blockchain-based internet of vehicles：distributed network architecture and performance analysis[J].IEEE Internet of Things Journal，2018，6（3）：4640-4649.
[23] WANG B，HU Y，LI S，et al.A blockchain consensus mechanism for educational administration system[C]//Proceedings of the 2nd IEEE International Conference on Electronics Technology（ICET），2019：603-608.
[24] MESHCHERYAKOV Y，MELMAN A，EVSUTIN O，et al.On performance of PBFT blockchain consensus algorithm for IoT-applications with constrained devices[J].IEEE Access，2021，9：80559-80570.