[HTML][HTML] A comprehensive review of AI based intrusion detection system

T Sowmya, EAM Anita - Measurement: Sensors, 2023 - Elsevier
In today's digital world, the tremendous amount of data poses a significant challenge to
cyber security. The complexity of cyber-attacks makes it difficult to develop efficient tools to …

Cyber security in smart cities: a review of deep learning-based applications and case studies

D Chen, P Wawrzynski, Z Lv - Sustainable Cities and Society, 2021 - Elsevier
On the one hand, smart cities have brought about various changes, aiming to revolutionize
people's lives. On the other hand, while smart cities bring better life experiences and great …

Review of botnet attack detection in SDN-enabled IoT Using machine learning

WG Negera, F Schwenker, TG Debelee, HM Melaku… - Sensors, 2022 - mdpi.com
The orchestration of software-defined networks (SDN) and the internet of things (IoT) has
revolutionized the computing fields. These include the broad spectrum of connectivity to …

A survey on the role of artificial intelligence, machine learning and deep learning for cybersecurity attack detection

A Salih, ST Zeebaree, S Ameen… - … & Innovation amid …, 2021 - ieeexplore.ieee.org
With the growing internet services, cybersecurity becomes one of the major research
problems of the modern digital era. Cybersecurity involves techniques to protect and control …

[PDF][PDF] Deep analysis of risks and recent trends towards network intrusion detection system

D Shankar, GVS George, JN JNSS… - International Journal of …, 2023 - researchgate.net
In the modern world, information security and communications concerns are growing due to
increasing attacks and abnormalities. The presence of attacks and intrusion in the network …

Lightweight Model for Botnet Attack Detection in Software Defined Network-Orchestrated IoT

WG Negera, F Schwenker, TG Debelee, HM Melaku… - Applied Sciences, 2023 - mdpi.com
The Internet of things (IoT) is being used in a variety of industries, including agriculture, the
military, smart cities and smart grids, and personalized health care. It is also being used to …

Applying transfer learning approaches for intrusion detection in software-defined networking

HM Chuang, LJ Ye - Sustainability, 2023 - mdpi.com
In traditional network management, the configuration of routing policies and associated
settings on individual routers and switches was performed manually, incurring a …

Deep learning-based cyber security solutions for smart-city: application and review

T Bhardwaj, H Upadhyay, L Lagos - Artificial Intelligence in Industrial …, 2022 - Springer
This book chapter provides the readers hands-on experience about the deep learning
algorithms and their use case for cyber security solutions in the smart city ecosystem. In this …

Intrusion detection in software defined network using deep learning approach

B Susilo, RF Sari - 2021 IEEE 11th Annual Computing and …, 2021 - ieeexplore.ieee.org
The development of IoT technology and virtualization has made network management
increasingly complex. Software-Defined Network has become a standard in virtualizing …

ML-SDNIDS: an attack detection mechanism for SDN based on machine learning

X Guo, W Bai - International Journal of Information and …, 2022 - inderscienceonline.com
With the rapid development of network technology, there are more and more application
scenarios of software defined networking (SDN), such as big data, cloud computing, internet …