AI-Driven Intrusion Detection Systems for Cybersecurity
DOI:
https://doi.org/10.64235/ntebwf71Keywords:
Artificial Intelligence, Intrusion Detection Systems, Cybersecurity, Machine Learning, Deep Learning, Network Security, Threat Detection, Anomaly Detection, Internet of Things, Cloud Computing.Abstract
Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) have become a vital part of the cybersecurity landscape, offering intelligent, adaptive, and real-time solutions to detect malicious activities in various computing environments. Traditional signature-based detection methods have been found to be limited in their ability to detect new and changing attack patterns as cyber threats grow in complexity, numbers and sophistication. AI-powered IDS solve these issues by utilizing machine learning, deep learning, neural networks, and hybrid analytical methods to effectively identify anomalies, classify threats, and automate incident responses with greater accuracy and efficacy. This study analyzes the development of AI-driven intrusion detection systems, their components, the key AI techniques used and implementation in enterprise networks, cloud computing systems, Internet of Things (IoT) environments, critical infrastructure and host-based systems. The research also examines the performance benefits of AI-powered detection models, such as better detection accuracy and lower false positive rates, and how these models can be scaled up to handle large-scale network monitoring. Besides, it explores the key challenges that are typically encountered in the implementation of AI systems, like adversarial attacks, data privacy, computational complexity, and model interpretability, and identifies some recent trends, such as explainable AI, federated learning, edge intelligence, and predictive threat detection. Overall, the results show that AI-enabled intrusion detection systems can greatly improve cybersecurity resilience, allowing for proactive, adaptive, and intelligent defense strategies that can tackle increasingly complex cyber threats.
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