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[HTML][HTML] Res-TranBiLSTM: An intelligent approach for intrusion detection in the Internet of Things
S Wang, W Xu, Y Liu - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT), as the information carrier of the Internet and
telecommunications networks, is a new network technology comprising physical entities …
telecommunications networks, is a new network technology comprising physical entities …
Breaking alert fatigue: AI-assisted SIEM framework for effective incident response
Contemporary security information and event management (SIEM) solutions struggle to
identify critical security incidents effectively due to the overwhelming number of false alerts …
identify critical security incidents effectively due to the overwhelming number of false alerts …
An intrusion detection system for edge-envisioned smart agriculture in extreme environment
The deployment of Internet of Things (IoT) systems in smart agriculture (SA) operates in
extreme environments, including wind, snowfall, flooding, landscape, and so on for …
extreme environments, including wind, snowfall, flooding, landscape, and so on for …
Intrusion detection system for wireless sensor networks: A machine learning based approach
In this era, plenty of wireless devices are being used with the support of WI-FI (Wireless
Fidelity) and need to be maintained and authorized. Wireless Sensor Networks (WSN), a …
Fidelity) and need to be maintained and authorized. Wireless Sensor Networks (WSN), a …
Study on empowering cyber security by using Adaptive Machine Learning Methods
Machine Learning (ML) is pivotal in enhancing cybersecurity solutions, surpassing rule-
based methods. The complexity of modern malware demands robust detection systems …
based methods. The complexity of modern malware demands robust detection systems …
[HTML][HTML] A comparative assessment of machine learning algorithms in the IoT-based network intrusion detection systems
The rapid increase in online risks is a reflection of the exponential growth of Internet of
Things (IoT) networks. Researchers have proposed numerous intrusion detection …
Things (IoT) networks. Researchers have proposed numerous intrusion detection …
Team Work Optimizer Based Bidirectional LSTM Model for Designing a Secure Cybersecurity Model
R Vallabhaneni, HS Nagamani… - 2024 International …, 2024 - ieeexplore.ieee.org
The Internet's rapid growth and the volume of data being transmitted over it have been
accompanied by a steady increase in threats to network security. Hackers attempt to steal …
accompanied by a steady increase in threats to network security. Hackers attempt to steal …
[HTML][HTML] Improved sand cat swarm optimization with deep learning based enhanced malicious activity recognition for cybersecurity
The main concept of a smart city is to join manual items with electronics, software, sensors,
and network connectivity for data contact via Internet of Things (IoT) gadgets. IoT improves …
and network connectivity for data contact via Internet of Things (IoT) gadgets. IoT improves …
Advancing IoT security: a comprehensive AI-based trust framework for intrusion detection
CP Kaliappan, K Palaniappan… - Peer-to-Peer Networking …, 2024 - Springer
Over the years, the Internet of Things (IoT) devices have shown rapid proliferation and
development in various domains. However, the widespread adoption of smart devices …
development in various domains. However, the widespread adoption of smart devices …
Arp spoofing detection using machine learning classifiers: an experimental study
S Majumder, MK Deb Barma, A Saha - Knowledge and Information …, 2025 - Springer
Recent university data breaches highlight the need to protect sensitive information and
enhance centralized security systems like Software-Defined Networking and Intrusion …
enhance centralized security systems like Software-Defined Networking and Intrusion …