Automatic Detection System for Abnormal Storage of Sensitive Data in Coastal Port Network Communication

Abstract

Wang, Z., 2020. Automatic detection system for abnormal storage of sensitive data in coastal port network communication. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 868–872. Coconut Creek (Florida), ISSN 0749-0208.In order to effectively prevent the security threat of data storage in network communication and improve the accuracy of anomaly detection, an automatic anomaly detection system for sensitive data storage in coastal port network communication based on Linux platform is proposed and designed. The system is divided into data acquisition, protocol analysis, rule loading, exception detection, console and other functional modules. Among them, the data acquisition module mainly discusses the optional method of capturing data packets and BPF capture mechanism. The acquired network packets are processed by protocol analysis module and converted into data that can be easily analyzed; the rule description language is designed in the rule loading module to effectively discover and warn the abnormal behaviors by matching with the established rules; the information entropy is used to extract the behavioral characteristic parameters of network traffic in the abnormal detection part, and the detection process and detection method are discussed. The console module is designed as a web page based on WebSocket communication protocol, which is convenient to control the detection system across platforms. Experimental results show that the system has strong detection performance, high accuracy and reliability.