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DarkReading DeepInstinct AI.pdf
Darkreading Deepinstinct Ai

Presentation covering AI/ML titled 'Darkreading Deepinstinct Ai'.

This page contains AI generated content. Errors or omissions may be present. Use human level critical thinking.
  • Q: What is the core technology behind Deep Instinct?
    A: Deep Learning neural networks applied to cybersecurity.
  • Q: How does Deep Learning differ from traditional Machine Learning in this context?
    A: It uses raw data input without manual feature extraction, allowing for higher accuracy with less human intervention.
  • Q: What is the primary claim regarding 'Zero-Day' prevention?
    A: Deep Instinct claims to prevent unknown and zero-day malware pre-execution.
  • Q: What is the 'Prediction' capability?
    A: The ability to identify malicious files before they run based on static analysis.
  • Q: What platforms does the solution support?
    A: Endpoints, servers, and mobile devices.
  • Q: How does the solution handle 'Fileless' attacks?
    A: By monitoring memory and script execution behaviors.
  • Q: What is the false positive rate claimed?
    A: Extremely low compared to traditional AV and ML solutions.
  • Q: Does it require frequent signature updates?
    A: No, the model is trained offline and requires infrequent updates.
  • Q: What is the deployment model?
    A: Agent-based.
  • Q: Who is the target audience for this report?
    A: CISOs and security architects looking for advanced prevention.

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