Data Science and Intelligent Computing Techniques
An Approach for Network Based Intrusion Detection System using Snort
Authors: Pavithra P S and Durgadevi P
Publishing Date: 22-10-2023
ISBN: 978-81-955020-2-8
Abstract
The newest technology, the Internet of Things, uses IoT devices to transmit data through networks. The biggest challenge with IoT is ensuring data transfer security. An intrusion detection system (IDS) is suggested as a solution to this problem. An essential network security tool for protecting computers and network systems is the IDS. It is capable of detecting and watching network activity. To find the unusual activity, we used the Snort IDS programme. An open source network security tool is Snort IDS. Both recognized and unidentified hazards might be found. To find attacks and produce alerts, it may search and compare the rules with network traffic data. This article examines protocol risks, attacks, and security problems related to network security. It also includes a plan to mitigate these risks. The MIT-DARPA 1999 data collection was used to produce the experiment's findings. The Snort IDS is used to identify anomalous behavior data since behaviour pattern datasets can be both normal and aberrant. The effectiveness of Snort's rule was assessed and put to the test in this article.
Keywords
Alert Correlation, Intrusion Detection system (IDS), NIDS, Security, Snort rules
Cite as
Pavithra P S and Durgadevi P, "An Approach for Network Based Intrusion Detection System using Snort", In: Satyasai Jagannath Nanda and Rajendra Prasad Yadav (eds), Data Science and Intelligent Computing Techniques, SCRS, India, 2023, pp. 481-491. https://doi.org/10.56155/978-81-955020-2-8-44