ZafiyetAI is a comprehensive AI security atlas focused on research and development in cybersecurity, including data collection methods, attack techniques, vulnerabilities, and more. It explores how attackers utilize open research data and employs strategies to exploit AI systems. The platform shares insights on attack vectors like phishing, command injections, and ML model exploits. It provides a detailed examination of various methods and techniques used by attackers, emphasizing on malicious training data, backdoored models, and the effectiveness of different attack vectors against AI systems. Through structured categories, ZafiyetAI serves as a critical resource for understanding and mitigating AI vulnerabilities.
• analysis of service denial attacks in ml systems
• backdoor attack methodologies
• exploration of command injection vulnerabilities
• data leakage and adversarial attacks
• access risks to machine learning models
• phishing methods enhanced by ai
• techniques for deceiving ai models
• exploration of vulnerabilities in ai systems
• attack strategies analysis
• open research data collection
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A federated AI framework that integrates decentralized data sources for AI development.
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