A Proactive Approach to Generative AI for Cybersecurity
Generative AI for cybersecurity is new, confusing, and somewhat scary for many infosec professionals. While this might be true, it also has great potential to help organizations improve threat detection and response, automate processes, augment staff, and mitigate risks. CISOs should remain open-minded, explore generative AI use cases, and select vendor partners with the right frameworks, large language models, coverage, and functionality.
If you would like to learn more about cybersecurity and recent trends and. Then this white-paper is for you:
- Generative AI has potential to improve threat detection and response, automate processes, augment staff, and mitigate risks.
- Organizations face simultaneous and difficult cybersecurity trends: increasing threats, a cybersecurity workforce shortage, and hybrid IT support.
- Constant firefighting: Security operations teams are overwhelmed by critical alerts and high-priority remediation activities, leading to burnout.
- Monitoring security across a growing attack surface: Security teams are asked to monitor security hygiene and respond to threats across remote user systems, cloud-native applications, SaaS providers, and third-party partners.
- Operationalizing threat intelligence: Many organizations lack the right skills or processes to transform raw information into blocking rules, threat hunts, and strategic decisions.
- Security technology vendors are introducing generative AI capabilities to improve security efficacy, operational efficiency, and staff productivity. Some security professionals remain skeptical due to potential issues with false positive results, data leakage, privacy, and hallucinations.
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