[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 …
[HTML][HTML] A hybrid CNN+ LSTM-based intrusion detection system for industrial IoT networks
HC Altunay, Z Albayrak - … Science and Technology, an International Journal, 2023 - Elsevier
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 …
lIDS-SIoEL: intrusion detection framework for IoT-based smart environments security using ensemble learning
Smart cities are being enabled all around the world by Internet of Things (IoT) applications.
A smart city idea necessitates the integration of information and communication …
A smart city idea necessitates the integration of information and communication …
Ai meta-learners and extra-trees algorithm for the detection of phishing websites
Phishing is a type of social web-engineering attack in cyberspace where criminals steal
valuable data or information from insensitive or uninformed users of the internet. Existing …
valuable data or information from insensitive or uninformed users of the internet. Existing …
An advanced intrusion detection system for IIoT based on GA and tree based algorithms
SM Kasongo - IEEE Access, 2021 - ieeexplore.ieee.org
The evolution of the Internet and cloud-based technologies have empowered several
organizations with the capacity to implement large-scale Internet of Things (IoT)-based …
organizations with the capacity to implement large-scale Internet of Things (IoT)-based …
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction
Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS)
play a critical role in protecting interconnected networks by detecting malicious actors and …
play a critical role in protecting interconnected networks by detecting malicious actors and …
Modern Smart Cities and Open Research Challenges and Issues of Explainable Artificial Intelligence
SR Sindiramutty, CE Tan, WJ Tee, SP Lau… - … in Explainable AI …, 2024 - igi-global.com
This chapter's purpose is to review the modern smart cities and open research challenges
and issues of explainable artificial intelligence (XAI). With the advent of XAI, people's lives …
and issues of explainable artificial intelligence (XAI). With the advent of XAI, people's lives …
Robust and accurate performance anomaly detection and prediction for cloud applications: a novel ensemble learning-based framework
Effectively detecting run-time performance anomalies is crucial for clouds to identify
abnormal performance behavior and forestall future incidents. To be used for real-world …
abnormal performance behavior and forestall future incidents. To be used for real-world …
Multi-class segmentation of organ at risk from abdominal ct images: A deep learning approach
Medical imaging segmentation is an essential technique for modern medical applications. It
is the foundation of many aspects of clinical diagnosis, oncology and computer-integrated …
is the foundation of many aspects of clinical diagnosis, oncology and computer-integrated …
Evaluation of machine learning techniques for traffic flow-based intrusion detection
Cybersecurity is one of the great challenges of today's world. Rapid technological
development has allowed society to prosper and improve the quality of life and the world is …
development has allowed society to prosper and improve the quality of life and the world is …