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 …
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 …
Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
Phishing website detection with semantic features based on machine learning classifiers: a comparative study
The phishing attack is one of the main cybersecurity threats in web phishing and spear
phishing. Phishing websites continue to be a problem. One of the main contributions to our …
phishing. Phishing websites continue to be a problem. One of the main contributions to our …
Botnet Attack Detection by Using CNN‐LSTM Model for Internet of Things Applications
The Internet of Things (IoT) has grown rapidly, and nowadays, it is exploited by cyber attacks
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
Machine learning in network anomaly detection: A survey
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …
networks against malicious access is always challenging even though it has been studied …
Artificial intelligence algorithms for malware detection in android-operated mobile devices
With the rapid expansion of the use of smartphone devices, malicious attacks against
Android mobile devices have increased. The Android system adopted a wide range of …
Android mobile devices have increased. The Android system adopted a wide range of …
Botnet attack detection using local global best bat algorithm for industrial internet of things
The need for timely identification of Distributed Denial-of-Service (DDoS) attacks in the
Internet of Things (IoT) has become critical in minimizing security risks as the number of IoT …
Internet of Things (IoT) has become critical in minimizing security risks as the number of IoT …
Android mobile malware detection using machine learning: A systematic review
With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …
phones, which account for 72.2% of the total market share. Hackers try to attack …
Multi‐aspects AI‐based modeling and adversarial learning for cybersecurity intelligence and robustness: A comprehensive overview
IH Sarker - Security and Privacy, 2023 - Wiley Online Library
Due to the rising dependency on digital technology, cybersecurity has emerged as a more
prominent field of research and application that typically focuses on securing devices …
prominent field of research and application that typically focuses on securing devices …