Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4572
Title: Network Security Systems Log Analysis for Trends and Insights: A Case Study
Authors: Meena, Amit Kumar
Hubballi, Neminath
Singh, Yogendra
Bhatia, Vimal
Keywords: Computer crime;Computer system firewalls;Intrusion detection;Open systems;Peer to peer networks;Domain name system;Intrusion Detection Systems;Intrusion detection/prevention systems;Network administrator;Network connection;Peer-to-peer application;Security appliances;Vulnerable systems;Network security
Issue Date: 2020
Publisher: IEEE Computer Society
Citation: Meena, A. K., Hubballi, N., Singh, Y., Bhatia, V., & Franke, K. (2020). Network security systems log analysis for trends and insights: A case study. Paper presented at the International Symposium on Advanced Networks and Telecommunication Systems, ANTS, , 2020-December doi:10.1109/ANTS50601.2020.9342776
Abstract: Network perimeter security appliances like firewalls, intrusion detection systems mediate communications and log details pertaining to various events. Logs generated by these systems are used to identify security compromises, vulnerable systems, mis-configurations, etc and serve as a valuable asset for a network administrator. In this paper, we report on a study conducted using logs generated by production level security appliances deployed in our university network. In particular, we process the logs generated by firewall, intrusion detection/prevention system and domain name system service to identify trends and gain insights. We process 71 million network connection records which includes 95.7 thousand alerts generated by an open source intrusion detection system collected over a period of 31 days and derive statistics to understand end host level behavioral trends. In our analysis we compare hosts which are known to be infected with malware or running Peer-to-Peer applications and remaining using a set of relevant parameters and identify clearly differentiated behavioral trends. © 2020 IEEE.
URI: https://doi.org/10.1109/ANTS50601.2020.9342776
https://dspace.iiti.ac.in/handle/123456789/4572
ISBN: 9781728192901
ISSN: 2153-1684
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: