Ransomware reloaded: Re-examining its trend, research and mitigation in the era of data exfiltration
Ransomware has grown to be a dominant cybersecurity threat by exfiltrating, encrypting, or
destroying valuable user data and causing numerous disruptions to victims. The severity of …
destroying valuable user data and causing numerous disruptions to victims. The severity of …
Ai-driven cybersecurity: an overview, security intelligence modeling and research directions
Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (or
Industry 4.0), which can be used for the protection of Internet-connected systems from cyber …
Industry 4.0), which can be used for the protection of Internet-connected systems from cyber …
Cybersecurity data science: an overview from machine learning perspective
In a computing context, cybersecurity is undergoing massive shifts in technology and its
operations in recent days, and data science is driving the change. Extracting security …
operations in recent days, and data science is driving the change. Extracting security …
Automation of human behaviors and its prediction using machine learning
Prediction is a method of detecting a person's behavior toward online buying by evaluating
publically available evaluations on the web. Understanding expressive human …
publically available evaluations on the web. Understanding expressive human …
Ransomware mitigation in the modern era: A comprehensive review, research challenges, and future directions
Although ransomware has been around since the early days of personal computers, its
sophistication and aggression have increased substantially over the years. Ransomware, as …
sophistication and aggression have increased substantially over the years. Ransomware, as …
Improving performance of autoencoder-based network anomaly detection on nsl-kdd dataset
Network anomaly detection plays a crucial role as it provides an effective mechanism to
block or stop cyberattacks. With the recent advancement of Artificial Intelligence (AI), there …
block or stop cyberattacks. With the recent advancement of Artificial Intelligence (AI), there …
Deep cybersecurity: a comprehensive overview from neural network and deep learning perspective
IH Sarker - SN Computer Science, 2021 - Springer
Deep learning, which is originated from an artificial neural network (ANN), is one of the
major technologies of today's smart cybersecurity systems or policies to function in an …
major technologies of today's smart cybersecurity systems or policies to function in an …
Deep Q-learning based reinforcement learning approach for network intrusion detection
The rise of the new generation of cyber threats demands more sophisticated and intelligent
cyber defense solutions equipped with autonomous agents capable of learning to make …
cyber defense solutions equipped with autonomous agents capable of learning to make …
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 …
Ae-mlp: A hybrid deep learning approach for ddos detection and classification
Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet
connectivity massively grows in recent years. Conventional shallow machine learning-based …
connectivity massively grows in recent years. Conventional shallow machine learning-based …