Automating Incident Response with AI
Describes automation pipelines, orchestration, and guardrails for safe automated response.
Explainable AI (XAI) in Cybersecurity: Why It Matters
Overview of XAI techniques and why explainability is essential for SOCs and compliance.
How Hackers Use AI (ThreatGPT, WormGPT, etc.)
Analysis of malicious generative AI usage, threat actor workflows, and mitigation.
Building a Python Phishing Email Classifier with ML
A practical guide to building a phishing classifier with dataset prep, feature engineering, model training, and evaluation.
Understanding Adversarial Attacks in Machine Learning
Artificial Intelligence (AI) is revolutionizing the cybersecurity landscape by enabling faster, more accurate detection of threats and vulnerabilities. This article explores mechanics of adversarial attacks and defenses.
GANs Used for Attack & Defense
GAN use-cases for synthetic data generation and adversarial testing.
Data Poisoning Attacks in ML Security
Data validation, provenance, and robust aggregation as defenses.
Cybersecurity Career Paths in the Era of AI
Career pathways, skill recommendations, and certification suggestions.
Attacks on NLP Models: Prompt Injection & More
Prompt injection, model poisoning, and defensive prompt engineering.
Privacy-Preserving AI for Security Applications
Federated learning, homomorphic encryption, and secure multiparty computation applied to security.