Artificial Intelligence

AI’s Dual Role in Cybersecurity: Defense Tool or Attack Vector? Introduction Artificial Intelligence (AI) is no longer a futuristic concept—it’s a core component of modern cybersecurity. On one hand, AI empowers defenders to automate threat detection, identify anomalies, and respond to incidents faster than ever. On the other hand, attackers are weaponizing AI to scale attacks, bypass defenses, and even generate malicious code in seconds. This post explores both sides of AI in cybersecurity, provides practical defensive strategies, and introduces a mini hands-on lesson to get you started building more secure AI-integrated environments. ...

ETR-2: AI & ML for Threat Detection Lab Overview In this lab, you’ll apply machine learning techniques to detect anomalies in log data—mimicking how AI supports SOC teams. You’ll use Python tools such as scikit-learn or PyCaret to train unsupervised models and compare results to traditional rule-based detection. Lab Instructions 1. Setting Up Your Environment You will need: Python 3.9+ Jupyter Notebook or Google Colab Install required libraries: pip install pandas matplotlib seaborn scikit-learn pycaret Download a sample log dataset (or use the instructor-provided logs). Suggested sources: ...