Exploration of Machine Learning Algorithms for Development of Intelligent Intrusion Detection Systems

Jannat, Adnan; Hayat, Umar; Sadiq, Touseef

doi:10.1109/c-code58145.2023.10139885

Cited by 2 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These logs and alerts are stored in the database because they are useful to system administrators. IDS data storage is not just for logs storage purposes, but we need to develop a wide-ranging database management system that's empowered with data organizational measures [9]. For rapid processing, the stored data is required to be in structured form.…”

Section: Database Valuations Over Nidsmentioning

confidence: 99%

Performance Improvement Scheme of NIDS Through Optimized Intrusion Pattern Database

Amjad,

Mumtaz,

Abbas

et al. 2024

IJORAS

View full text Add to dashboard Cite

Network-based intrusion detection systems (NIDS) are perceptively distributed devices within computer networks. They aim to examine traffic passing through the network on which they are installed passively. The database is the most vital part of network intrusion detection systems, as all the data converted information from the NIDS needs to be saved in a patterned structured manner. Understanding the usability of several available types of databases like central databases, Distributed databases, operational databases, etc., it is on the developer’s end to choose the most comprehensive one. Data transformation and performance speed are essential features that a stable database can handle. In this paper, we have analyzed the performance of multiple databases to find out the proficient way that favors NIDS optimization.

show abstract

Section: Database Valuations Over Nidsmentioning

confidence: 99%