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 …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions
N Moustafa, N Koroniotis, M Keshk… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research
attention in recent years, aiming to provide interpretability and confidence to the inner …
attention in recent years, aiming to provide interpretability and confidence to the inner …
Fusion of statistical importance for feature selection in Deep Neural Network-based Intrusion Detection System
Abstract Intrusion Detection System (IDS) is an essential part of network as it contributes
towards securing the network against various vulnerabilities and threats. Over the past …
towards securing the network against various vulnerabilities and threats. Over the past …
A dependable hybrid machine learning model for network intrusion detection
Network intrusion detection systems (NIDSs) play an important role in computer network
security. There are several detection mechanisms where anomaly-based automated …
security. There are several detection mechanisms where anomaly-based automated …
Machine learning based solutions for security of Internet of Things (IoT): A survey
Over the last decade, IoT platforms have been developed into a global giant that grabs every
aspect of our daily lives by advancing human life with its unaccountable smart services …
aspect of our daily lives by advancing human life with its unaccountable smart services …
[HTML][HTML] MapReduce based intelligent model for intrusion detection using machine learning technique
With the emergence of the Internet of Things (IoT), the computer networks' phenomenal
expansion, and enormous relevant applications, data is continuously increasing. In this way …
expansion, and enormous relevant applications, data is continuously increasing. In this way …
Performance analysis of machine learning models for intrusion detection system using Gini Impurity-based Weighted Random Forest (GIWRF) feature selection …
To protect the network, resources, and sensitive data, the intrusion detection system (IDS)
has become a fundamental component of organizations that prevents cybercriminal …
has become a fundamental component of organizations that prevents cybercriminal …
A feature selection algorithm for intrusion detection system based on pigeon inspired optimizer
Feature selection plays a vital role in building machine learning models. Irrelevant features
in data affect the accuracy of the model and increase the training time needed to build the …
in data affect the accuracy of the model and increase the training time needed to build the …