Cybersecurity threats and their mitigation approaches using Machine Learning—A Review
Machine learning is of rising importance in cybersecurity. The primary objective of applying
machine learning in cybersecurity is to make the process of malware detection more …
machine learning in cybersecurity is to make the process of malware detection more …
A comprehensive review on deep learning algorithms: Security and privacy issues
Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …
various complicated tasks that begin to modify and improve with experiences. It has become …
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 …
Modeling realistic adversarial attacks against network intrusion detection systems
The incremental diffusion of machine learning algorithms in supporting cybersecurity is
creating novel defensive opportunities but also new types of risks. Multiple researches have …
creating novel defensive opportunities but also new types of risks. Multiple researches have …
Artificial intelligence in the cyber domain: Offense and defense
Artificial intelligence techniques have grown rapidly in recent years, and their applications in
practice can be seen in many fields, ranging from facial recognition to image analysis. In the …
practice can be seen in many fields, ranging from facial recognition to image analysis. In the …
Artificial intelligence analysis in cyber domain: A review
L Zhao, D Zhu, W Shafik… - International …, 2022 - journals.sagepub.com
The application of Big Data Analytics is identified through the Cyber Research Alliance for
cybersecurity as the foremost preference for future studies and advancement in the field of …
cybersecurity as the foremost preference for future studies and advancement in the field of …
A new proposal on the advanced persistent threat: A survey
An advanced persistent threat (APT) can be defined as a targeted and very sophisticated
cyber attack. IT administrators need tools that allow for the early detection of these attacks …
cyber attack. IT administrators need tools that allow for the early detection of these attacks …
Evading anti-malware engines with deep reinforcement learning
To reduce the risks of malicious software, malware detection methods using machine
learning have received tremendous attention in recent years. Most of the conventional …
learning have received tremendous attention in recent years. Most of the conventional …
Polymorphic Adversarial DDoS attack on IDS using GAN
R Chauhan, SS Heydari - 2020 International Symposium on …, 2020 - ieeexplore.ieee.org
Intrusion Detection systems are important tools in preventing malicious traffic from
penetrating into networks and systems. Recently, Intrusion Detection Systems are rapidly …
penetrating into networks and systems. Recently, Intrusion Detection Systems are rapidly …
Privacy preservation in Distributed Deep Learning: A survey on Distributed Deep Learning, privacy preservation techniques used and interesting research directions
E Antwi-Boasiako, S Zhou, Y Liao, Q Liu… - Journal of Information …, 2021 - Elsevier
Abstract Distributed or Collaborative Deep Learning, has recently gained more recognition
due to its major advantage of allowing two or more learning participants to contribute and …
due to its major advantage of allowing two or more learning participants to contribute and …