A Novel Data Mining Approach for Analysis and Pattern Recognition of Active Fingerprinting Components

Gujral, Harshit; Mittal, Sangeeta; Sharma, Abhinav

doi:10.1007/s11277-019-06135-1

Cited by 3 publications

(3 citation statements)

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“…And third, the presence of vulnerable or outdated services. In addition, the module is extended for the prediction of IP-ID sequences and network traffic using correlations among RTTs [ 23 ].…”

Section: Architecture Of Modules For the Network Administratormentioning

confidence: 99%

“…However, this limits the effectiveness of these systems in detecting granular network patterns. The authors describe the importance of such granular patterns, followed by utilizing them to identify anomalous fingerprints, in their previous work [ 23 ]. None of the existing open-source solutions provides the mechanism for assessing and maintaining the overall network health, whereas none of the propriety tools provides an insight into their working and the quantification of network health.…”

Section: Introductionmentioning

confidence: 99%

“…This suggests a monopoly of propriety tools in this field. Here, we emphasize building an open-source network health monitoring system by utilizing novel anomalous fingerprinting identification techniques described by the authors in the previous work [ 23 ], as well as open-source tools and libraries. We achieve this by highlighting the research aspects of monitoring architecture, anomaly detection, and vulnerability identification.…”

Section: Introductionmentioning

confidence: 99%

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Design and Implementation of a Quantitative Network Health Monitoring and Recovery System

Gujral

Sharma

Jain

et al. 2022

Wireless Pers Commun

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A network health monitoring system focuses on the quantification of the network’s health by taking into account various security flaws, leaks, and vulnerabilities. A plethora of propriety tools and patents are available for network health quantification. However, there is a paucity of available research and literature in this field. Thus, in this study, we present an architectural design of a network health monitoring system. The design focuses on the quantification of the network health of each end-user as well as the entire network. The network health score for each end-user is quantified by identifying (1) illicit egress-ingress traffic, (2) anomalous fingerprints, and (3) system-network vulnerabilities based on the NVD-CVSS (National Vulnerability Database, Common Vulnerability Severity Score) standards. An overall network-health score is produced, along with a prevention and recovery mechanism that is triggered upon the detection of an anomaly. The proposed system is implemented in a local area network and has demonstrated to protect the network against various threats successfully. The study is concluded by comparing the proposed tool with the popular propriety tools available in the field. The results outline that the proposed system garners features of open-source tools and enriches them by introducing a state-of-the-art architecture coupled with multiple novel features like exhaustive identification of vulnerability and detection of network aberrations using timers.

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Section: Architecture Of Modules For the Network Administratormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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