Artificial Intelligence is reshaping cybersecurity by enabling predictive threat detection, automated response and smarter risk management. This article explores how AI and machine learning models—from supervised classifiers to generative adversarial networks—are applied to intrusion detection, phishing mitigation and insider threat analysis. It also covers practical risks, attacker tactics and how to evaluate AI-based security tools. Whether you're building in-house models or assessing vendor solutions, this guide helps you move from hype to hands-on defence.

Splunk and Sentinel are Security Information Event Management SIEM solutions. They centralise log data, correlate events, and automate alerts—giving security teams the visibility they need to protect digital assets. Let Lockdown Market help you evaluate, deploy and optimize your SIEM strategy.

1. Security Concepts

Case Study: Cloud Adoption and Security Strategy

A financial services firm is transitioning to the cloud but wants to focus solely on application development without managing infrastructure. They opt for Platform as a Service (PaaS), allowing them to streamline operations while maintaining security.

Microsoft Security Copilot leverages the power of artificial intelligence AI to provide to enhance security operations. It is used in Sentinel, Microsoft Defender and other services for automation, detection, security insight plus much more.

Artificial intelligence AI in now used in cybersecurity with Microsoft Defender and Sentinel. An example is prompts that can be converted in KQL queries for threat intelligence. Copilot a virtual assistant powered by AI used for Security is a revolutionary tool designed to enhance security operations. This article is about practical applications of AI for threat detection, risk mitigation and proactive defence.