Emerging Technologies: Tech Innovators in AI Attack Detection - Demand Side
According to Gartner, "Security vendors across segments are using artificial intelligence to improve attack detection in the continuously evolving threat landscape. Product leaders can analyze how key innovators are utilizing these artificial intelligence technologies to address different customer demands."
Repoart Key Findings:
- An inability to customize and audit artificial intelligence (AI) models is a major inhibitor of the adoption of AI-based attack detection solutions. Vendors struggle to offer models customized to each customer’s environment in a scalable way.
- Organizations require solutions that address their expanded threat potential. Accelerating digital transformation and the work from home (WFH) trend have expanded the corporate attack surface from networks and endpoint devices to social media, mobile chat, collaboration platforms and cloud applications.
- Improve adoption of AI-enabled solutions by moving away from a “black-box” approach toward explainable and customizable AI models that can be tuned based on analyst feedback.
- Broaden AI capabilities to comprehensively monitor the increased attack surface channels. The ability to analyze associated unstructured, high-volume data streams for attack signals is a critical capability.
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