MalFilter: A Lightweight Real-Time Malicious URL Filtering System in Large-Scale Networks

2018 ◽  
Author(s):  
Guolin Tan ◽  
Peng Zhang ◽  
Qingyun Liu ◽  
Xinran Liu ◽  
Chunge Zhu ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Large Scale Networks ◽  
Url Filtering

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 Multi Comm_Plus: A Community Detection System for Identification of Community in Multi-Dimensional Networks

2016 ◽  
Vol 4 (05) ◽  
pp. 9879-9884
Author(s):  
Dhanya Sudhakaran ◽  
Shini Renjith
Keyword(s):  
Big Data ◽  
Real Time ◽  
Community Detection ◽  
Data Analytics ◽  
Selection Criteria ◽  
Large Scale ◽  
Detection System ◽  
Big Data Analytics ◽  
Detection Algorithms ◽  
Large Scale Networks

Community detection is a common problem in graph and big data analytics. It consists of finding groups of densely connected nodes with few connections to nodes outside of the group. In particular, identifying communities in large-scale networks is an important task in many scientific domains. Community detection algorithms in literature proves to be less efficient, as it leads to generation of communities with noisy interactions. To address this limitation, there is a need to develop a system which identifies the best community among multi-dimensional networks based on relevant selection criteria and dimensionality of entities, thereby eliminating the noisy interactions in a real-time environment.

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