… ensemble learning models as cybersecurity attack prediction … learning techniques in
conjunction with deep learning models. … current efforts in cybersecurity attack prediction with …

… cyber-attacks and insights of malicious samples and attacks, computational intelligence in
cybersecurity … The idea behind this method is keeping the known or seen attack behaviors as …

… Three deep learning methods for cybersecurity IDS are used in this study, namely (a) CNN,
(… The methodology adopted in this study is illustrated in Figure 8 . After capturing these logs, …

… For each cybersecurity threat or attack, we discuss the challenges for using … method based
on CVAEs for an IoT network. This research work is relevant because the proposed method …

… To calculate the CS statistic, we use the “chi2” function that is included as part of the Scikit-learn
library. One may employ the same method to rank features of a dataset with any of these …

… of cybersecurity where machine learning is used as a tool. We also provide a few glimpses of
adversarial attacks on machine learning … Distributed machine learning is a methodology for …

… How to identify various network attacks, particularly not previously seen attacks, is a key …
uses the depth learning method we have developed to take registry keys) and learn to extract …

… attacks are a particular crime that obtain personal information from users by fraudulent web
sites, and is the most common method … are an ensemble learning method for classification, …

… system is used to detect different kinds of attack based on deep learning method, which
is … In this paper, the cybersecurity attack detection based on deep learning methods is …

… In this paper, we present “CyberLearning”, a machine learning-based cybersecurity … A
decision tree is a method of non-parametric supervised learning that breaks down a given …