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AI cybersecurity is the use of artificial intelligence (AI) to protect data from cyberattacks. The technology enhances existing endpoint detection and response (EDR) solutions to improve security posture, identify attacks faster, and prevent unauthorized access or exfiltration of sensitive data.

Threat detection: AI watches for unusual login behavior, anomalous network traffic, or suspicious file activity to spot threats that can’t be spotted with preset rules. This enables it to catch more sophisticated cyberattacks, reduces false positives, and helps the system adapt to new risks.

Analysis: When a threat is detected, the AI can quickly determine its severity and what systems it might target. It can then act fast to isolate entry points, halt the attack, and send alerts to the right people.

Protection: AI-powered DLP combines content inspection with user behavior analytics to catch intentional and accidental data exposure. This stops malicious insiders and negligent employees from misusing their permissions, reduces alert fatigue, and reduces the number of incidents that require human intervention.

AI security solutions should automatically discover and map all AI models, services, and SDKs in your cloud environments to prevent shadow AI (unauthorized or undocumented AI usage). They should also support compliance automation for standards like GDPR and CCPA. Additionally, they should provide tools to help you secure training data with cryptography and automate the process of encrypting and tokenizing sensitive data. Look for tools that include the Adversarial Robustness Toolbox from the LF AI & Data Foundation to evaluate and test your AI model’s robustness against adversarial attacks.