Leveraging the capabilities of machine learning (ML) has emerged as a pivotal strategy for bolstering cybersecurity defenses. This paper provides an in-depth exploration of the …

This project focuses on detecting web application attacks using a combination of classical machine learning models and deep learning techniques. The dataset used is the CSIC 2010 …

In this work we investigate the use of machine learning techniques to leverage the performance of Web Application Firewalls (WAFs), systems that are used to detect and prevent attacks. We …

Feb 27, 2024 · Several previous studies have utilized machine learning classification methods to create an efficient IDS with various datasets for different types of attacks. This paper utilizes …

Jan 6, 2021 · In this blog, we will focus on Machine Learning techniques to detect web attack in network communication flows using continuous learning algorithm that learns the normal …

The objective is to detect cyber attacks using algorithms like artificial neural networks, convolutional neural networks, and random forests. The document outlines the structure of the …

In this article, we focus on countering emerging application layer cyber attacks since those are listed as top threats and the main challenge for network and cyber security. The major …

Abstract—The exploit of vulnerabilities present in Web appli-cations has been the main attack vector in the last decade biggest data breaches. In this work we put forward a framework to …

Global computer security issues including virus detection, ransom ware recognition, fraud detection, and spoofing identification were addressed using machine learning techniques.

Nov 6, 2020 · According to the OWASP, the 80 percent of the web attacks are done through HTTP/HTTPS requests queries. In this paper, we present a deep learning based web …