Big data analytics deep learning techniques and applications: A survey
Deep learning (DL), as one of the most active machine learning research fields, has
achieved great success in numerous scientific and technological disciplines, including …
achieved great success in numerous scientific and technological disciplines, including …
Zero-day attack detection: a systematic literature review
With the continuous increase in cyberattacks over the past few decades, the quest to
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …
A review of anomaly detection strategies to detect threats to cyber-physical systems
N Jeffrey, Q Tan, JR Villar - Electronics, 2023 - mdpi.com
Cyber-Physical Systems (CPS) are integrated systems that combine software and physical
components. CPS has experienced rapid growth over the past decade in fields as disparate …
components. CPS has experienced rapid growth over the past decade in fields as disparate …
[HTML][HTML] Robust DDoS attack detection with adaptive transfer learning
In the evolving cybersecurity landscape, the rising frequency of Distributed Denial of Service
(DDoS) attacks requires robust defense mechanisms to safeguard network infrastructure …
(DDoS) attacks requires robust defense mechanisms to safeguard network infrastructure …
DDoS attacks in Industrial IoT: A survey
S Chaudhary, PK Mishra - Computer Networks, 2023 - Elsevier
As the IoT expands its influence, its effect is becoming macroscopic and pervasive. One of
the most discernible effects is in the industries where it is known as Industrial IoT (IIoT). IIoT …
the most discernible effects is in the industries where it is known as Industrial IoT (IIoT). IIoT …
Enhancing the security in IoT and IIoT networks: An intrusion detection scheme leveraging deep transfer learning
Abstract The Internet of Things (IoT) networks, which are defined by their interconnected
devices and data streams are an expanding attack surface for cyber adversaries. Industrial …
devices and data streams are an expanding attack surface for cyber adversaries. Industrial …
DTL-5G: Deep transfer learning-based DDoS attack detection in 5G and beyond networks
Network slicing is considered as a key enabler for 5G and beyond mobile networks for
supporting a variety of new services, including enhanced mobile broadband, ultra-reliable …
supporting a variety of new services, including enhanced mobile broadband, ultra-reliable …
Counter denial of service for next-generation networks within the artificial intelligence and post-quantum era
Given the rise in cyber threats to networked systems, coupled with the proliferation of AI
techniques and enhanced processing capabilities, Denial of Service (DoS) attacks are …
techniques and enhanced processing capabilities, Denial of Service (DoS) attacks are …
Machine learning and deep learning for user authentication and authorization in cybersecurity: A state-of-the-art review
In the continuously develo** field of cyber security, user authentication and authorization
play a vital role in protecting personal information and digital assets from unauthorized use …
play a vital role in protecting personal information and digital assets from unauthorized use …
Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey
The Internet of Things (IoT) has witnessed unprecedented growth, resulting in a massive
influx of diverse network traffic from interconnected devices. Effectively classifying this …
influx of diverse network traffic from interconnected devices. Effectively classifying this …