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AI vs. AI: 6 ways enterprises are automating cybersecurity to counter AI-powered attacks
- AI is becoming essential for cybersecurity to combat AI-powered attacks, which are rapidly evolving in speed and sophistication.
- Malicious actors are leveraging generative AI to launch attacks at machine speed, prompting organizations to prioritize preemptive measures with predictive analysis.
- The rise of weaponized AI and malware-as-a-service (MaaS) is accelerating automated cybercrime, with MaaS comprising 57% of all cyberattacks.
- Attackers are moving faster, utilizing new techniques that legacy systems struggle to detect, indicating the need for adaptive defenses like AI-driven strategies.
- Various enterprises, such as Rate Companies, are implementing AI for threat modeling, zero-trust security, and automated response to enhance cyber resilience.
- Enhancing threat detection with self-learning AI, shifting from reactive to proactive defense, and automating phishing defenses are crucial in combating adversarial AI.
- AI-driven incident response plays a vital role in containing threats efficiently, with organizations like Rate Companies following a 1-10-60 SOC model for rapid intrusion detection and containment.
- Continuous hardening of attack surfaces using AI, detecting and mitigating insider threats with behavioral analytics, and enhancing visibility are key strategies employed by organizations.
- Implementing human-in-the-loop AI is essential for long-term cybersecurity success, as it augments human expertise rather than replacing it.
- AI in cybersecurity must collaborate with human teams to amplify defenders and make faster, smarter security decisions to keep up with the shrinking breakout times.
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