Anomaly Detection Sensors for a Modbus-Based Oil and Gas Well-Monitoring System

Xinchi He, Ethan Robards, R. Gamble, M. Papa
{"title":"Anomaly Detection Sensors for a Modbus-Based Oil and Gas Well-Monitoring System","authors":"Xinchi He, Ethan Robards, R. Gamble, M. Papa","doi":"10.1109/ICDIS.2019.00008","DOIUrl":null,"url":null,"abstract":"Timely detection of network traffic anomalies in oil and gas wells is critical to support operations. This paper describes a network sensor that has been specifically designed to operate within an existing well-monitoring infrastructure. Network traffic and flow features are extracted in real-time and compared against pre-set and moving averages to detect and report anomalies. A prototype has been tested using the Modbus protocol and network traffic covering several months of operations. In order to avoid potential impact on the production environment, scripts captured network packets that were then replayed on the IMUNES network emulator. Preliminary results have identified useful metrics for anomaly detection in a production environment.","PeriodicalId":181673,"journal":{"name":"2019 2nd International Conference on Data Intelligence and Security (ICDIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference on Data Intelligence and Security (ICDIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIS.2019.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Timely detection of network traffic anomalies in oil and gas wells is critical to support operations. This paper describes a network sensor that has been specifically designed to operate within an existing well-monitoring infrastructure. Network traffic and flow features are extracted in real-time and compared against pre-set and moving averages to detect and report anomalies. A prototype has been tested using the Modbus protocol and network traffic covering several months of operations. In order to avoid potential impact on the production environment, scripts captured network packets that were then replayed on the IMUNES network emulator. Preliminary results have identified useful metrics for anomaly detection in a production environment.
基于modbus的油气井监测系统异常检测传感器
及时发现油气井网络流量异常对于支持作业至关重要。本文介绍了一种专门设计用于现有井监测基础设施的网络传感器。实时提取网络流量和流量特征,并与预设平均值和移动平均值进行比较,以检测和报告异常情况。一个原型已经使用Modbus协议和网络流量进行了几个月的测试。为了避免对生产环境的潜在影响,脚本捕获网络数据包,然后在IMUNES网络模拟器上重播这些数据包。初步结果已经确定了在生产环境中进行异常检测的有用度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信