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Cyber risk and cybersecurity: a systematic review of data availability
Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …
indicating an increase of more than 50% since 2018. With the average cyber insurance …
Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives
Nowadays, cybersecurity challenges and their ever-growing complexity are the main
concerns for various information technology-driven organizations and companies. Although …
concerns for various information technology-driven organizations and companies. Although …
Deep Neuro-Fuzzy System application trends, challenges, and future perspectives: A systematic survey
Deep neural networks (DNN) have remarkably progressed in applications involving large
and complex datasets but have been criticized as a black-box. This downside has recently …
and complex datasets but have been criticized as a black-box. This downside has recently …
Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments
MP Novaes, LF Carvalho, J Lloret… - Future Generation …, 2021 - Elsevier
Over the last few years, Software Defined Networking (SDN) paradigm has become an
emerging architecture to design future networks and to meet new application demands. SDN …
emerging architecture to design future networks and to meet new application demands. SDN …
[HTML][HTML] Dependable intrusion detection system using deep convolutional neural network: A novel framework and performance evaluation approach
Intrusion detection systems (IDS) play a critical role in safeguarding computer networks
against unauthorized access and malicious activities. However, traditional IDS approaches …
against unauthorized access and malicious activities. However, traditional IDS approaches …
Optimization enabled deep learning‐based ddos attack detection in cloud computing
S Balasubramaniam, C Vijesh Joe… - … Journal of Intelligent …, 2023 - Wiley Online Library
Cloud computing is a vast revolution in information technology (IT) that inhibits scalable and
virtualized sources to end users with low infrastructure cost and maintenance. They also …
virtualized sources to end users with low infrastructure cost and maintenance. They also …
Cloud security based attack detection using transductive learning integrated with Hidden Markov Model
In recent years, organizations and enterprises put huge attention on their network security.
The attackers were able to influence vulnerabilities for the configuration of the network …
The attackers were able to influence vulnerabilities for the configuration of the network …
A comprehensive review of deep neuro-fuzzy system architectures and their optimization methods
Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …
Distributed denial of service attacks in cloud: State-of-the-art of scientific and commercial solutions
Cloud computing model provides on demand, elastic and fully managed computer system
resources and services to organizations. However, attacks on cloud components can cause …
resources and services to organizations. However, attacks on cloud components can cause …
Cloud network anomaly detection using machine and deep learning techniques-recent research advancements
A Abdallah, A Alkaabi, G Alameri, SH Rafique… - IEEE …, 2024 - ieeexplore.ieee.org
In the rapidly evolving landscape of computing and networking, the concepts of cloud
networks have gained significant prominence. Although the cloud network offers on-demand …
networks have gained significant prominence. Although the cloud network offers on-demand …