Privacy-Preserving AI for Security Applications
Federated learning, homomorphic encryption, and secure multiparty computation applied to security.
karamdeep1990@gmail.com
Attacks on NLP Models: Prompt Injection & More
Prompt injection, model poisoning, and defensive prompt engineering.
Cybersecurity Career Paths in the Era of AI
Career pathways, skill recommendations, and certification suggestions.
Data Poisoning Attacks in ML Security
Data validation, provenance, and robust aggregation as defenses.
GANs Used for Attack & Defense
GAN use-cases for synthetic data generation and adversarial testing.
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.
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.
How Hackers Use AI (ThreatGPT, WormGPT, etc.)
Analysis of malicious generative AI usage, threat actor workflows, and mitigation.
Explainable AI (XAI) in Cybersecurity: Why It Matters
Overview of XAI techniques and why explainability is essential for SOCs and compliance.
Automating Incident Response with AI
Describes automation pipelines, orchestration, and guardrails for safe automated response.