Data Encryption, Protecting data by converting it into a secret code that only authorized users can read., Multi-Factor Authentication (MFA), A security method that requires more than one way to verify a user’s identity., Phishing Attack, A fake message or website designed to steal personal or login information., Data Breach, An incident where private data is accessed or stolen without permission., Ransomware, Malware that locks systems or data and demands payment to restore access., Access Control, Rules that define who can view or use specific systems or data., API Security, Protecting APIs from unauthorized access, misuse, or attacks., Model Poisoning, When attackers inject bad data to manipulate how an AI system learns., Prompt Injection, A technique that tricks AI systems into ignoring rules and giving unsafe answers., Personally Identifiable Information (PII), Information that can be used to identify a specific person., Data Anonymization, Removing or changing personal data so individuals cannot be identified., Regulatory Compliance, Following laws and regulations related to data and security., Zero Trust Security, A security model where no user or system is trusted by default., Rate Limiting, Restricting how many requests a user or system can make in a given time., Responsible AI, Designing AI systems that are fair, transparent, and safe., Data Retention Policy, Rules about how long data is stored before being deleted.

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