Study of the SNORT intrusion detection system based on machine learning

O El Aeraj, C Leghris - 2023 7th IEEE Congress on Information …, 2023 - ieeexplore.ieee.org
Internet users can carry out their attacks by taking advantage of the flaws in networks and
systems, therefore they are not always acting with good intentions. The repercussions of …

Analysis of the SNORT intrusion detection system using machine learning

O El Aeraj, C Leghris - International Journal of Information Science and …, 2024 - innove.org
Today, cyber-attacks that exploit networks and systems vulnerabilities are becoming more
and more effective, reflecting the malicious intentions of certain Internet users. These attacks …

JARVIS: An Intelligent Network Intrusion Detection and Prevention System

AP Patil, H Premkumar, MHM Kiran… - 2022 IEEE Fourth …, 2022 - ieeexplore.ieee.org
With the current advances in networking and the usage of computer networks in different
sectors of technology, network security plays a prime role in enabling the proper functioning …

[PDF][PDF] Toward an Appropriate Approach for Intelligent Intrusion and Detection Systems

O Elaeraj, C Leghris - Journal of Artificial Intelligence & Cloud …, 2022 - academia.edu
Now a days, the company's information security become among a main priority. Indeed, the
more the attack force on the network develops, the more it is necessary to develop the …

The Implementation of Machine Learning for Optimizing Network-Based Intrusion Detection in the Snort Application

RE Febrita, L Hakim, AP Utomo - 2023 6th International …, 2023 - ieeexplore.ieee.org
Along with the increasing need for computer and mobile applications, communication, and
information over internet networks, the need for data security guarantees that must be …

Integrating artificial intelligence into Snort IDS

X Fang, L Liu - 2011 3rd International Workshop on Intelligent …, 2011 - ieeexplore.ieee.org
Snort is an open source network intrusion detection and prevention system (IDS/IPS)
utilizing a rule-driven language, its shortcoming is unable to detect new attacks. This paper …

A Novel Approach for Anomaly Detection using Snort Integrated with Machine Learning

T Preethi, PR Reddy, L Likhitha… - … on Computing for …, 2024 - ieeexplore.ieee.org
In today's digital world, it is crucial to keep a company's information safe from cyber threats.
With new and more sophisticated network attacks emerging all the time, better security …

Using machine learning techniques to improve intrusion detection accuracy

H Zhang, KY Lin, W Chen… - 2019 IEEE 2nd …, 2019 - ieeexplore.ieee.org
In recent years, network intrusions have emerged in an endless stream and have generated
a lot of financial losses. An intrusion detection system (IDS) is used to detect network …

A study of network intrusion detection systems using artificial intelligence/machine learning

P Vanin, T Newe, LL Dhirani, E O'Connell, D O'Shea… - Applied Sciences, 2022 - mdpi.com
The rapid growth of the Internet and communications has resulted in a huge increase in
transmitted data. These data are coveted by attackers and they continuously create novel …

Study of snort-based IDS

S Chakrabarti, M Chakraborty… - Proceedings of the …, 2010 - dl.acm.org
General trend in industry is a shift from Intrusion Detection Systems (IDS) to Intrusion
Prevention Systems (IPS). In this paper, we have investigated the motivations behind this …