Ransomware reloaded: Re-examining its trend, research and mitigation in the era of data exfiltration

T McIntosh, T Susnjak, T Liu, D Xu, P Watters… - ACM Computing …, 2024 - dl.acm.org
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 …

Ai-driven cybersecurity: an overview, security intelligence modeling and research directions

IH Sarker, MH Furhad, R Nowrozy - SN Computer Science, 2021 - Springer
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 …

Cybersecurity data science: an overview from machine learning perspective

IH Sarker, ASM Kayes, S Badsha, H Alqahtani… - Journal of Big …, 2020 - Springer
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 …

Automation of human behaviors and its prediction using machine learning

H Jupalle, S Kouser, AB Bhatia, N Alam… - Microsystem …, 2022 - Springer
Prediction is a method of detecting a person's behavior toward online buying by evaluating
publically available evaluations on the web. Understanding expressive human …

Ransomware mitigation in the modern era: A comprehensive review, research challenges, and future directions

T McIntosh, ASM Kayes, YPP Chen, A Ng… - ACM Computing …, 2021 - dl.acm.org
Although ransomware has been around since the early days of personal computers, its
sophistication and aggression have increased substantially over the years. Ransomware, as …

Improving performance of autoencoder-based network anomaly detection on nsl-kdd dataset

W Xu, J Jang-Jaccard, A Singh, Y Wei… - IEEE Access, 2021 - ieeexplore.ieee.org
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 …

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 …

Deep Q-learning based reinforcement learning approach for network intrusion detection

H Alavizadeh, H Alavizadeh, J Jang-Jaccard - Computers, 2022 - mdpi.com
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 …

Cybersecurity threats and their mitigation approaches using Machine Learning—A Review

M Ahsan, KE Nygard, R Gomes… - … of Cybersecurity and …, 2022 - mdpi.com
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 …

Ae-mlp: A hybrid deep learning approach for ddos detection and classification

Y Wei, J Jang-Jaccard, F Sabrina, A Singh, W Xu… - IEEE …, 2021 - ieeexplore.ieee.org
Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet
connectivity massively grows in recent years. Conventional shallow machine learning-based …