[HTML][HTML] A Comprehensive Survey on Generative AI Solutions in IoT Security
JL López Delgado, JA López Ramos - Electronics, 2024 - mdpi.com
The influence of Artificial Intelligence in our society is becoming important due to the
possibility of carrying out analysis of the large amount of data that the increasing number of …
possibility of carrying out analysis of the large amount of data that the increasing number of …
An IoT Intrusion Detection Approach Based on Salp Swarm and Artificial Neural Network
ABSTRACT The Internet of Things has emerged as a significant and influential technology in
modern times. IoT presents solutions to reduce the need for human intervention and …
modern times. IoT presents solutions to reduce the need for human intervention and …
A comprehensive survey on intrusion detection algorithms
Y Li, Z Li, M Li - Computers and Electrical Engineering, 2025 - Elsevier
Although there are many reviews on Intrusion Detection Systems (IDS), the basic parts of
Intrusion Detection Algorithms (IDA), such as imbalanced datasets, feature engineering, and …
Intrusion Detection Algorithms (IDA), such as imbalanced datasets, feature engineering, and …
Securing smart agriculture networks using bio-inspired feature selection and transfer learning for effective image-based intrusion detection
The smart agricultural system integrates advanced technologies to optimize farming
practices and increase productivity. It gathers images from sensors, drones, and other …
practices and increase productivity. It gathers images from sensors, drones, and other …
Advancements in training and deployment strategies for AI-based intrusion detection systems in IoT: a systematic literature review
Abstract As the Internet of Things (IoT) grows, ensuring robust security is crucial. Intrusion
Detection Systems (IDS) protect IoT networks from various cyber threats. This systematic …
Detection Systems (IDS) protect IoT networks from various cyber threats. This systematic …
Anonymizing Big Data Streams Using In-memory Processing: A Novel Model Based on One-time Clustering
Big data privacy preservation is a critical challenge for data mining and data analysis.
Existing methods for anonymizing big data streams using k-anonymity algorithms may cause …
Existing methods for anonymizing big data streams using k-anonymity algorithms may cause …
[PDF][PDF] A Hybrid Heuristic AI Technique for Enhancing Intrusion Detection Systems in IoT Environments.
In the evolving landscape of the Internet of Things (IoT), effective intrusion detection is
paramount for maintaining security and data integrity. This study introduces a hybrid …
paramount for maintaining security and data integrity. This study introduces a hybrid …
Fine-tuning CNN for Enhanced Security in WSN-Based Forest Fire Detection
In recent years, Wireless Sensor Networks (WSNs) have gained significant attention for their
role in forest fire detection, offering early detection and real-time monitoring capabilities …
role in forest fire detection, offering early detection and real-time monitoring capabilities …
An Intrusion Detection System over the IoT Data Streams Using eXplainable Artificial Intelligence (XAI)
A Alabbadi, F Bajaber - Sensors, 2025 - mdpi.com
The rise in intrusions on network and IoT systems has led to the development of artificial
intelligence (AI) methodologies in intrusion detection systems (IDSs). However, traditional AI …
intelligence (AI) methodologies in intrusion detection systems (IDSs). However, traditional AI …
Building a Cybersecurity AI Dataset: A Survey of Malware Detection Techniques
Datasets are a foundational step in the development of any Artificial Intelligence (AI)
powered solutions. In cybersecurity, especially in malware detection and mitigation …
powered solutions. In cybersecurity, especially in malware detection and mitigation …