Towards model generalization for intrusion detection: Unsupervised machine learning techniques
Through the ongoing digitization of the world, the number of connected devices is
continuously growing without any foreseen decline in the near future. In particular, these …
continuously growing without any foreseen decline in the near future. In particular, these …
A spectrogram image-based network anomaly detection system using deep convolutional neural network
The dynamics of computer networks have changed rapidly over the past few years due to a
tremendous increase in the volume of the connected devices and the corresponding …
tremendous increase in the volume of the connected devices and the corresponding …
Analysis of IoT security challenges and its solutions using artificial intelligence
The Internet of Things (IoT) is a well-known technology that has a significant impact on many
areas, including connections, work, healthcare, and the economy. IoT has the potential to …
areas, including connections, work, healthcare, and the economy. IoT has the potential to …
[HTML][HTML] Dependable intrusion detection system using deep convolutional neural network: A novel framework and performance evaluation approach
Intrusion detection systems (IDS) play a critical role in safeguarding computer networks
against unauthorized access and malicious activities. However, traditional IDS approaches …
against unauthorized access and malicious activities. However, traditional IDS approaches …
A comprehensive deep learning benchmark for IoT IDS
The significance of an intrusion detection system (IDS) in networks security cannot be
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …
Explainable artificial intelligence for intrusion detection system
S Patil, V Varadarajan, SM Mazhar, A Sahibzada… - Electronics, 2022 - mdpi.com
Intrusion detection systems are widely utilized in the cyber security field, to prevent and
mitigate threats. Intrusion detection systems (IDS) help to keep threats and vulnerabilities out …
mitigate threats. Intrusion detection systems (IDS) help to keep threats and vulnerabilities out …
Survey on wireless network security
A wireless network is used to connect various wired organizational structures and provide
connectivity within the organization for employees to move freely by avoiding the hurdle of a …
connectivity within the organization for employees to move freely by avoiding the hurdle of a …
Comparative analysis of intrusion detection systems and machine learning based model analysis through decision tree
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
[HTML][HTML] Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets
Abstract The Internet of Things (IoT) has transformed many aspects of modern life, from
healthcare and transportation to home automation and industrial control systems. However …
healthcare and transportation to home automation and industrial control systems. However …
Machine learning in identity and access management systems: Survey and deep dive
S Aboukadri, A Ouaddah, A Mezrioui - Computers & Security, 2024 - Elsevier
The evolution of identity and access management (IAM) has been driven by the expansion
of online services, cloud computing, and the Internet of Things (IoT). The proliferation of …
of online services, cloud computing, and the Internet of Things (IoT). The proliferation of …