A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Advancing cybersecurity: a comprehensive review of AI-driven detection techniques
As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …
A survey of multimodal hybrid deep learning for computer vision: Architectures, applications, trends, and challenges
K Bayoudh - Information Fusion, 2024 - Elsevier
In recent years, deep learning algorithms have rapidly revolutionized artificial intelligence,
particularly machine learning, enabling researchers and practitioners to extend previously …
particularly machine learning, enabling researchers and practitioners to extend previously …
Balancing QoS and security in the edge: Existing practices, challenges, and 6G opportunities with machine learning
While the emerging 6G networks are anticipated to meet the high-end service quality
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
A systematic review on machine learning and deep learning models for electronic information security in mobile networks
Today's advancements in wireless communication technologies have resulted in a
tremendous volume of data being generated. Most of our information is part of a widespread …
tremendous volume of data being generated. Most of our information is part of a widespread …
A survey of machine and deep learning methods for privacy protection in the internet of things
Recent advances in hardware and information technology have accelerated the proliferation
of smart and interconnected devices facilitating the rapid development of the Internet of …
of smart and interconnected devices facilitating the rapid development of the Internet of …
Transfer-learning-based intrusion detection framework in IoT networks
Cyberattacks in the Internet of Things (IoT) are growing exponentially, especially zero-day
attacks mostly driven by security weaknesses on IoT networks. Traditional intrusion …
attacks mostly driven by security weaknesses on IoT networks. Traditional intrusion …
Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
Path signature-based xai-enabled network time series classification
L Sun, Y Wang, Y Ren, F Xia - Science China Information Sciences, 2024 - Springer
Classifying network time series (NTS) is crucial for automating network administration and
ensuring cyberspace security. It enables the detection of anomalies, the identification of …
ensuring cyberspace security. It enables the detection of anomalies, the identification of …
Advances in Machine Learning-Driven Cognitive Radio for Wireless Networks: A Survey
NA Khalek, DH Tashman… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The next frontier in wireless connectivity lies at the intersection of cognitive radio (CR)
technology and machine learning (ML), where intelligent networks can provide pervasive …
technology and machine learning (ML), where intelligent networks can provide pervasive …