Explainable artificial intelligence applications in cyber security: State-of-the-art in research
This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …
Deep learning approaches for detecting DDoS attacks: A systematic review
In today's world, technology has become an inevitable part of human life. In fact, during the
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Explainable artificial intelligence in cybersecurity: A survey
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
Internet of things (IoT) security dataset evolution: Challenges and future directions
The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
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 …
Reliable deep learning and IoT-based monitoring system for secure computer numerical control machines against cyber-attacks with experimental verification
This paper introduces a new intelligent integration between an IoT platform and deep
learning neural network (DNN) algorithm for the online monitoring of computer numerical …
learning neural network (DNN) algorithm for the online monitoring of computer numerical …
Prospects and challenges of the machine learning and data-driven methods for the predictive analysis of power systems: A review
W Strielkowski, A Vlasov, K Selivanov, K Muraviev… - Energies, 2023 - mdpi.com
The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …
systems offers the potential to accurately predict and manage the behavior of these systems …
Adversarial examples: A survey of attacks and defenses in deep learning-enabled cybersecurity systems
Over the last few years, the adoption of machine learning in a wide range of domains has
been remarkable. Deep learning, in particular, has been extensively used to drive …
been remarkable. Deep learning, in particular, has been extensively used to drive …
[HTML][HTML] An empirical assessment of ensemble methods and traditional machine learning techniques for web-based attack detection in industry 5.0
Cybersecurity attacks that target software have become profitable and popular targets for
cybercriminals who consciously take advantage of web-based vulnerabilities and execute …
cybercriminals who consciously take advantage of web-based vulnerabilities and execute …