A Data Alignment Method for Network Packet Capture Based on DBSCAN

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.