[PDF][PDF] The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review

MM Mijwil, IE Salem, MM Ismaeel - Iraqi Journal For Computer Science and …, 2023 - iasj.net
People in the modern era spend most of their lives in virtual environments that offer a range
of public and private services and social platforms. Therefore, these environments need to …

In-network machine learning using programmable network devices: A survey

C Zheng, X Hong, D Ding, S Vargaftik… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

DDoS attacks detection using machine learning and deep learning techniques: analysis and comparison

MA Al-Shareeda, S Manickam… - Bulletin of Electrical …, 2023 - journal.beei.org
The security of the internet is seriously threatened by a distributed denial of service (DDoS)
attacks. The purpose of a DDoS assault is to disrupt service and prevent legitimate users …

Cyber-secure SDN: A CNN-based approach for efficient detection and mitigation of DDoS attacks

AA Najar, SM Naik - Computers & Security, 2024 - Elsevier
Abstract Software Defined Networking (SDN) has become popular due to its flexibility and
agility in network management, enabling rapid adaptation to changing business …

A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking

AA Bahashwan, M Anbar, S Manickam, TA Al-Amiedy… - Sensors, 2023 - mdpi.com
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …

A deep learning technique to detect distributed denial of service attacks in software-defined networks

WG Gadallah, HM Ibrahim, NM Omar - Computers & Security, 2024 - Elsevier
Abstract Software-Defined Network (SDN) is an established networking paradigm that
separates the control plane from the data plane. It has central network control, and …

Online banking user authentication methods: a systematic literature review

NA Karim, OA Khashan, H Kanaker… - Ieee …, 2023 - ieeexplore.ieee.org
Online banking has become increasingly popular in recent years, making it a target for
cyberattacks. Banks have implemented various user authentication methods to protect their …

Optimized artificial intelligence model for DDoS detection in SDN environment

Y Al-Dunainawi, BR Al-Kaseem… - IEEE Access, 2023 - ieeexplore.ieee.org
Distributed denial of service (DDoS) attacks continue to be a major security concern,
threatening the availability and reliability of network services. Software-defined networking …

[HTML][HTML] Enhancing DDoS attack detection with hybrid feature selection and ensemble-based classifier: A promising solution for robust cybersecurity

MA Hossain, MS Islam - Measurement: Sensors, 2024 - Elsevier
Distributed denial-of-service (DDoS) attacks pose a significant threat to computer networks
and systems by disrupting services through the saturation of targeted systems with traffic …

Marina: Realizing ml-driven real-time network traffic monitoring at terabit scale

M Seufert, K Dietz, N Wehner, S Geißler… - … on Network and …, 2024 - ieeexplore.ieee.org
Network operators require real-time traffic monitoring insights to provide high performance
and security to their customers. It has been shown that artificial intelligence and machine …