{"title":"Network scan detection with LQS: a lightweight, quick and stateful algorithm","authors":"Mansour Alsaleh, P. V. Oorschot","doi":"10.1145/1966913.1966928","DOIUrl":null,"url":null,"abstract":"Network scanning reveals valuable information of accessible hosts over the Internet and their offered network services, which allows significant narrowing of potential targets to attack. Addressing and balancing a set of sometimes competing desirable properties is required to make network scanning detection more appealing in practice: 1) fast detection of scanning activity to enable prompt response by intrusion detection and prevention systems; 2) acceptable rate of false alarms, keeping in mind that false alarms may lead to legitimate traffic being penalized; 3) high detection rate with the ability to detect stealthy scanners; 4) efficient use of monitoring system resources; and 5) immunity to evasion. In this paper, we present a scanning detection algorithm designed to accommodate all of these goals. LQS is a fast, accurate, and light-weight scan detection algorithm that leverages the key properties of the monitored network environment as variables that affect how the scanning detection algorithm operates. We also present what is, to our knowledge, the first automated way to estimate a reference baseline in the absence of ground truth, for use as an evaluation methodology for scan detection. Using network traces from two sites, we evaluate LQS and compare its scan detection results with those obtained by the state-of-the-art TRW algorithm. Our empirical analysis shows significant improvements over TRW in all of these properties.","PeriodicalId":72308,"journal":{"name":"Asia CCS '22 : proceedings of the 2022 ACM Asia Conference on Computer and Communications Security : May 30-June 3, 2022, Nagasaki, Japan. ACM Asia Conference on Computer and Communications Security (17th : 2022 : Nagasaki-shi, Japan ; ...","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia CCS '22 : proceedings of the 2022 ACM Asia Conference on Computer and Communications Security : May 30-June 3, 2022, Nagasaki, Japan. ACM Asia Conference on Computer and Communications Security (17th : 2022 : Nagasaki-shi, Japan ; ...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1966913.1966928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

Network scanning reveals valuable information of accessible hosts over the Internet and their offered network services, which allows significant narrowing of potential targets to attack. Addressing and balancing a set of sometimes competing desirable properties is required to make network scanning detection more appealing in practice: 1) fast detection of scanning activity to enable prompt response by intrusion detection and prevention systems; 2) acceptable rate of false alarms, keeping in mind that false alarms may lead to legitimate traffic being penalized; 3) high detection rate with the ability to detect stealthy scanners; 4) efficient use of monitoring system resources; and 5) immunity to evasion. In this paper, we present a scanning detection algorithm designed to accommodate all of these goals. LQS is a fast, accurate, and light-weight scan detection algorithm that leverages the key properties of the monitored network environment as variables that affect how the scanning detection algorithm operates. We also present what is, to our knowledge, the first automated way to estimate a reference baseline in the absence of ground truth, for use as an evaluation methodology for scan detection. Using network traces from two sites, we evaluate LQS and compare its scan detection results with those obtained by the state-of-the-art TRW algorithm. Our empirical analysis shows significant improvements over TRW in all of these properties.
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网络扫描检测与LQS:一个轻量级,快速和有状态的算法
网络扫描揭示了互联网上可访问主机及其提供的网络服务的有价值的信息,从而可以显著缩小潜在攻击目标的范围。为了使网络扫描检测在实践中更具吸引力,需要对一组有时相互竞争的理想属性进行寻址和平衡:1)快速检测扫描活动,使入侵检测和防御系统能够迅速响应;2)可接受的假警报率,请记住,假警报可能导致合法流量被处罚;3)检出率高,可检测隐身扫描仪;4)有效利用监测系统资源;5)免于逃避。在本文中,我们提出了一种扫描检测算法,旨在适应所有这些目标。LQS是一种快速、准确、轻量级的扫描检测算法,它利用被监控网络环境的关键属性作为影响扫描检测算法运行方式的变量。我们还提出了,据我们所知,在没有地面真相的情况下估计参考基线的第一种自动化方法,用于扫描检测的评估方法。使用来自两个站点的网络痕迹,我们评估了LQS,并将其扫描检测结果与最先进的TRW算法获得的结果进行了比较。我们的实证分析表明,在所有这些特性上,TRW都有显著的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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