[HTML][HTML] Cyber risk and cybersecurity: a systematic review of data availability
Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …
indicating an increase of more than 50% since 2018. With the average cyber insurance …
Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
[HTML][HTML] A hybrid CNN+ LSTM-based intrusion detection system for industrial IoT networks
Abstract The Internet of Things (IoT) ecosystem has proliferated based on the use of the
internet and cloud-based technologies in the industrial area. IoT technology used in the …
internet and cloud-based technologies in the industrial area. IoT technology used in the …
A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges
A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
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 …
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 …
MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …
involve many electronic control units connected through intravehicle networks (IVNs) to …
Internet of things (IoT) security dataset evolution: Challenges and future directions
The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
A deep learning model for network intrusion detection with imbalanced data
Y Fu, Y Du, Z Cao, Q Li, W **ang - Electronics, 2022 - mdpi.com
With an increase in the number and types of network attacks, traditional firewalls and data
encryption methods can no longer meet the needs of current network security. As a result …
encryption methods can no longer meet the needs of current network security. As a result …