Network intrusion detection system using advanced machine learning
These days, with all our fancy communication tools, networks are dealing with a crazy mix of data. Problem is, that’s made it easier for troublemakers to sneak in, and folks are stressing about security big time. People are working hard on something called NIDS to fight back. The cool part? They’re using AI to catch anything weird, and it’s looking pretty promising. But there’s a snag—too much normal stuff and not enough bad stuff in the data throws things off. In our project, we’re making an NIDS that uses AI to fix that and spot trouble better. We’ve got this trick with autoencoders that checks out errors and finds the sneaky attacks. We ran a ton of tests, and it’s beating the old ways hands down.
Authors
- Bhimanadhula Nandini
- G. Rohith
- Amit Kumar (ORCID: https://orcid.org/0000-0001-8499-6324)
- D. Sirisha
- S.V. Rama Rao
Institutions
- National Institute of Technology Andhra Pradesh (IN)
Publication Details
- Journal
- IET conference proceedings.
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1049/icp.2025.1678
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00