… systems besides traditional security methods. As a result, proactive cyber security systems
such as network behavior analysis, machine learning, threat analysis are developed. …

… and methods In this section, we present our security model of machine learning to detect
cyber… This involved several processing steps: exploring the security dataset, preparing raw data, …

… Although, the association analysis is popular in machine learning techniques to build rule-based
intelligent systems [21,22,23], in this work, we primarily focus on classification …

… of security incidents, several machine learning techniques, … , and association analysis, or
neural network-based deep learning … cybersecurity systems are composed of network security …

… machine learning techniques applied in cyber security and point out the trend of using machine
learning techniques for cyber security. … DL algorithms for analytical and logical thinking. …

… Consider a dynamic analysis classifier that uses API calls. An equivalent to changing a single
pixel’ s color would be to change a single API call to another API call. Even if we disregard …

… malware detection and network security, AI-… intelligence and predictive analytics. Research
by Liang et al. (2021) examined the role of machine learning algorithms in forecasting cyber …

… survey of deep learning approaches for cyber security … deep learning approaches. The
dataset plays an important role in intrusion detection, therefore we describe 35 well-known cyber …

… This paper explores how adversarial learning can be used to target supervised models by
… Saliency Map attack and exploring classification behaviours. The analysis also includes the …

… provide an experimental analysis of federated deep learning with three deep learning …
information on federated deep learning approaches with emerging technologies for cyber security. …