scholarly journals Flow-inspector: a framework for visualizing network flow data using current web technologies

Computing ◽  
2013 ◽  
Vol 96 (1) ◽  
pp. 15-26 ◽  
Author(s):  
Lothar Braun ◽  
Mario Volke ◽  
Johann Schlamp ◽  
Alexander von Bodisco ◽  
Georg Carle
Keyword(s):  
Network Flow ◽  
Flow Data ◽  
Web Technologies

CompactFlow: A Hybrid Binary Format for Network Flow Data

2020 ◽  
pp. 185-201
Author(s):  
Michal Piskozub ◽  
Riccardo Spolaor ◽  
Ivan Martinovic
Keyword(s):  
Network Flow ◽  
Flow Data ◽  
Binary Format

scholarly journals InSight2: A Modular Visual Analysis Platform for Network Situational Awareness in Large-Scale Networks

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1747
Author(s):  
Hansaka Angel Dias Edirisinghe Kodituwakku ◽  
Alex Keller ◽  
Jens Gregor
Keyword(s):  
Real Time ◽  
Computer Networks ◽  
Network Flow ◽  
Large Scale ◽  
Visual Analysis ◽  
Situational Awareness ◽  
Monitoring Network ◽  
Network Activity ◽  
Flow Data ◽  
Large Scale Networks

The complexity and throughput of computer networks are rapidly increasing as a result of the proliferation of interconnected devices, data-driven applications, and remote working. Providing situational awareness for computer networks requires monitoring and analysis of network data to understand normal activity and identify abnormal activity. A scalable platform to process and visualize data in real time for large-scale networks enables security analysts and researchers to not only monitor and study network flow data but also experiment and develop novel analytics. In this paper, we introduce InSight2, an open-source platform for manipulating both streaming and archived network flow data in real time that aims to address the issues of existing solutions such as scalability, extendability, and flexibility. Case-studies are provided that demonstrate applications in monitoring network activity, identifying network attacks and compromised hosts and anomaly detection.

scholarly journals Scalable Bayesian Modeling, Monitoring, and Analysis of Dynamic Network Flow Data

2018 ◽  
Vol 113 (522) ◽  
pp. 519-533 ◽  
Author(s):  
Xi Chen ◽  
Kaoru Irie ◽  
David Banks ◽  
Robert Haslinger ◽  
Jewell Thomas ◽  
...  
Keyword(s):  
Bayesian Modeling ◽  
Network Flow ◽  
Dynamic Network ◽  
Flow Data ◽  
Dynamic Network Flow

scholarly journals Visual Analysis of Network Flow Data with Timelines and Event Plots

2008 ◽  
pp. 85-99 ◽  
Author(s):  
D. Phan ◽  
J. Gerth ◽  
M. Lee ◽  
A. Paepcke ◽  
T. Winograd
Keyword(s):  
Network Flow ◽  
Visual Analysis ◽  
Flow Data

scholarly journals Identifying Network Anomalies Using Clustering Technique in Weblog Data

2012 ◽  
Vol 2 (3) ◽  
pp. 71-73 ◽  
Author(s):  
Kiran Bejjanki ◽  
A. Bhaskar
Keyword(s):  
Network Flow ◽  
Flow Data ◽  
Ip Address ◽  
Clustering Techniques ◽  
Clustering Technique ◽  
Network Anomalies

In this paper we present an approach for identifying networkanomalies by visualizing network flow data which is stored inweblogs. Various clustering techniques can be used to identifydifferent anomalies in the network. Here, we present a newapproach based on simple K-Means for analyzing networkflow data using different attributes like IP address, Protocol,Port number etc. to detect anomalies. By using visualization,we can identify which sites are more frequently accessed bythe users. In our approach we provide overview about givendataset by studying network key parameters. In this processwe used preprocessing techniques to eliminate unwantedattributes from weblog data.

Secure Outsourcing of Network Flow Data Analysis

2013 ◽  
Author(s):  
Mohamed Nassar ◽  
Bechara al Bouna ◽  
Qutaibah Malluhi
Keyword(s):  
Data Analysis ◽  
Network Flow ◽  
Flow Data ◽  
Secure Outsourcing

Analysis of Network Flow Data

2020 ◽  
pp. 169-186
Author(s):  
Eric D. Kolaczyk ◽  
Gábor Csárdi
Keyword(s):  
Network Flow ◽  
Flow Data

Bayesian Activity Modelling for Network Flow Data

2018 ◽  
pp. 55-76
Author(s):  
Henry Clausen ◽  
Mark Briers ◽  
Niall M. Adams
Keyword(s):  
Network Flow ◽  
Flow Data

Evaluation of multilayer perceptron algorithms for an analysis of network flow data

2016 ◽  
Author(s):  
Jędrzej Bieniasz ◽  
Mariusz Rawski ◽  
Krzysztof Skowron ◽  
Mateusz Trzepiński
Keyword(s):  
Multilayer Perceptron ◽  
Network Flow ◽  
Flow Data
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