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Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …
many desirable features, including flexibility and manageability. Despite those advantages …
Cyber security intrusion detection for agriculture 4.0: Machine learning-based solutions, datasets, and future directions
In this paper, we review and analyze intrusion detection systems for Agriculture 4.0 cyber
security. Specifically, we present cyber security threats and evaluation metrics used in the …
security. Specifically, we present cyber security threats and evaluation metrics used in the …
SDN security review: Threat taxonomy, implications, and open challenges
Software-Defined networking (SDN) is a networking paradigm to enable dynamic, flexible,
and programmatically efficient configuration of networks to revolutionize network control and …
and programmatically efficient configuration of networks to revolutionize network control and …
Security control and data planes of SDN: a comprehensive review of traditional, AI and MTD approaches to security solutions
Software-Defined Networking (SDN) is a groundbreaking technology that has transformed
network management significantly. By integrating data and control, SDN offers unparalleled …
network management significantly. By integrating data and control, SDN offers unparalleled …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Performance and features: Mitigating the low-rate TCP-targeted DoS attack via SDN
D Tang, Y Yan, S Zhang, J Chen… - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
Software-Defined Networking (SDN) is an emerging network architecture. The decoupled
data and control plane provides programmability for efficient network management …
data and control plane provides programmability for efficient network management …
A data-driven network intrusion detection system using feature selection and deep learning
L Zhang, K Liu, X **e, W Bai, B Wu, P Dong - Journal of Information Security …, 2023 - Elsevier
Network intrusion detection system (NIDS) is an important line of defense for network
security as network attacks become more frequent. In this paper, we propose a data-driven …
security as network attacks become more frequent. In this paper, we propose a data-driven …
Machine-learning-based traffic classification in software-defined networks
Many research efforts have gone into upgrading antiquated communication network
infrastructures with better ones to support contemporary services and applications. Smart …
infrastructures with better ones to support contemporary services and applications. Smart …
Attack-specific feature selection for anomaly detection in software-defined networks
N Abbas, Y Nasser, M Shehab… - 2021 3rd IEEE middle …, 2021 - ieeexplore.ieee.org
Due to the rapid advancement of technologies including the tremendous growth of
multimedia content, cloud computing and mobile usage, conventional networks are not able …
multimedia content, cloud computing and mobile usage, conventional networks are not able …