A Data Alignment Method for Network Packet Capture Based on DBSCAN
DOI:
https://doi.org/10.13052/jwe1540-9589.2374Keywords:
DBSCAN, data alignment, network quality detectionAbstract
This paper investigates the issues of packet alignment and consistency among PLC devices based on industrial network environments, aiming to ensure the integrity and accuracy of packets from sender to receiver. To achieve this goal, we propose an anomaly detection method that combines the DBSCAN clustering algorithm with the 3-sigma principle to identify and handle abnormal packets that may occur during transmission. By comparing the data between the sending and receiving ends, and analyzing based on timestamps and data content, we validate the alignment of packets in the network environment. Experimental results demonstrate that the proposed method effectively detects and corrects packet loss or delay jitter, thereby enhancing the reliability of communication between PLC devices and the consistency of data transmission. The scheme presented in this paper enables quicker and more precise identification of packet loss and delays, adapting well to various network load conditions. Further experimental analysis indicates that this method excels in reducing both false positive and false negative rates, and it exhibits good scalability, making it applicable to data alignment and consistency verification in other industrial automation scenarios. Ultimately, this novel solution provides stability and accuracy for data transmission among devices in a network environment.
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References
Adanza D, Gifre L, Alemany P, et al. Enabling traffic forecasting with cloud-native SDN controller in transport networks[J]. Computer Networks, 250110565–110565, 2024.
Qiongqiong S, Longfei Y. Enhanced computer network security assessment through employing an integrated LogTODIM-TOPSIS technique under interval neutrosophic sets[J]. International Journal of Knowledge-based and Intelligent Engineering Systems, 28(3):419-434, 2024.
Shahid K, Ahmad N S, Rizvi H T S. Optimizing Network Performance: A Comparative Analysis of EIGRP, OSPF, and BGP in IPv6-Based Load-Sharing and Link-Failover Systems[J]. Future Internet, 16(9): 339–339, 2024.
Luo Y, Ke W, Lam T C, et al. An accurate slicing method for dynamic time warping algorithm and the segment-level early abandoning optimization[J]. Knowledge-Based Systems, 300112231–112231, 2024.
Gao Wei, Qian Chengyang, Zhang Qi, et al. Trajectory similarity algorithm based on dynamic time warping and trajectory point compression [J/OL]. Control and Information Technology, 1–8, 2024.
Beqirllari K, Ozansoy C, Gomes D, et al. High-bandwidth coupling circuit design for PLC applications on SWER networks: From design to production[J]. Engineering Science and Technology, an International Journal, 58101840–101840, 2024.
Daniel S, Jörg K. Requirements for Crafting Virtual Network Packet Captures[J]. Journal of Cybersecurity and Privacy, 2(3):516–526, 2022.
Zhongxing D. Network Traffic Monitoring Algorithm Based on Big Data Analysis[J]. Academic Journal of Computing & Information Science, 6(5), 2023.
Yang Xuerong, Wang Longfei, Yuan Ranhui, Shan Shangqiu. Cooperative Objective-Oriented Multi-UAV Clock Synchronization Algorithm [J]. 32(6): 573–578, 2024.
Cheng Shunling, Li Changxian, Zhao Ke. Optimization of Train Communication Network Time Synchronization Based on PTP Protocol [J]. 45(18): 92–98, 2022
Cai Z, Gu Z, He K. A self-adaptive density-based clustering algorithm for varying densities datasets with strong disturbance factor[J]. Data & Knowledge Engineering, 153102345–102345, 2024.
Zhang Yanlong, Zhu Huabing, Liu Zhengyu, Wen Jian. Depth Grouping Method for Retired Power Batteries Based on DBSCAN Clustering [J]. Power Technology, 47(4): 462–468, 2023.
Ge Chengpeng, Zhao Dong, Wang Rui, Ma Qinghua. Segmented Point Cloud Denoising Method Based on Improved DBSCAN and Distance Consensus Evaluation [J]. Journal of System Simulation, 1–11, 2024.
Liao Yong, Huang Lei. Research on the Design of Operation and Maintenance Platform and Anomaly Detection Based on Microservices, 2021.
Hermans C, Koussa A J, Oevelen V T, et al. Fault detection for district heating substations: Beyond three-sigma approaches[J]. Smart Energy, 16100159–100159, 2024.
Ding Zuokun, Ding Jingjing. Optimization of Human Settlement Environment Improvement Based on Information Technology [J]. Modern Computer, (08): 54–59, 2021.
Shi Linjun, Dai Tao, Lao Wenjie, Wu Feng, Lin Keming, Li Yang, Zhu Ling, Huang Xifang. Operational State Recognition of New Energy Power Generation Units Based on Improved KNN Algorithm, Power Automation Equipment.
Olabanjo O, Wusu A, Aigbokhan E, et al. A novel graph convolutional networks model for an intelligent network traffic analysis and classification[J]. International Journal of Information Technology, (prepublish):1–13, 2024.
Abdulabbas FAA Barbaros P. Effect of Sliding Windows Technique on the Performance of TCP/IP Networks[J]. Journal of Smart Internet of Things, 1(1):46–55, 2023.
Kumar K, Ghosh K S, Neelam, et al. Indian Standard Time Dissemination Using Precision Time Protocol: Toward Resilient Time Synchronization Using Optical Fibers for Critical Infrastructure in India[J]. MAPAN, 39(3):475–482, 2024.
