AI-Driven Threat Detection Architecture

Abstract

The rapid proliferation of digital infrastructure, spanning cloud computing, the Internet of Things (IoT), edge networks, and mobile platforms, has dramatically expanded the attack surface available to cybercriminals. Traditional signature-based intrusion detection systems, while effective against known threats, are fundamentally inadequate in the face of zero-day exploits, advanced persistent threats (APTs), encrypted malicious traffic, and evolving ransomware campaigns. This chapter presents a comprehensive examination of AI-driven threat detection architectures as the next-generation response to these escalating cybersecurity challenges. It explores the full spectrum of the threat landscape, encompassing DDoS attacks, botnets, APTs, and cloud-specific vulnerabilities, before detailing the layered architectural framework through which AI-based detection systems operate, from raw data collection at the network and endpoint layer, through preprocessing and feature extraction, to model inference and automated response. A range of machine learning and deep learning methodologies is evaluated, including supervised classifiers such as decision trees, random forests, k-nearest neighbors, and convolutional neural networks, as well as unsupervised approaches like autoencoders and graph neural networks. Benchmark datasets, including CICIDS2017 and UNSW-NB15, are used to assess comparative model performance across accuracy, precision, recall, and F1-score. The chapter further addresses the deployment challenges of AI-based intrusion detection, including class imbalance, adversarial evasion, concept drift, computational cost, privacy concerns, and surveys emerging research directions such as federated learning, explainable AI, large language model integration, and the long-term vision of autonomous security operations centers. Together, these discussions establish a technical and strategic foundation for building intelligent, scalable, and resilient cybersecurity systems in modern enterprise environments.