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1
Introduction
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Outline
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Agenda
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AI for Cybersecurity Overview
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AI for Cybersecurity Life Cycle
6
Data Sources
7
External Data Sources
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Cyber Security Initiatives
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Key Limitations
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Promising Directions
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Research Illustration
12
Existing AI for Cybersecurity Initiatives
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Exploit Data
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Vulnerability Assessment Data
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Vulnerability Exploit Matching
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Device Vulnerability Severity Metric
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Vulnerability Assessment
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Workforce Development
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Funding
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Conclusion
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Questions
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Minimum Data Set Size
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Decision Automation
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Weak Signals
25
Honey Pots
26
AI in IoT
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What comes first
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What is the best solution
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AI ML
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MITRE Framework
31
Business Logic Vulnerabilities
Description:
Explore the intersection of artificial intelligence and cybersecurity in this 55-minute webcast from RSA Conference. Gain insights into prevailing cybersecurity data sources and AI applications in Security Operations Centers, Cyber Threat Intelligence, disinformation, and adversarial machine learning. Delve into key limitations and opportunities in the current landscape, and discover a multi-disciplinary roadmap for future AI developments in cybersecurity. Learn about external data sources, cyber security initiatives, and research illustrations covering exploit data, vulnerability assessment, and workforce development. Engage with topics such as decision automation, weak signals, AI in IoT, and business logic vulnerabilities. Presented by Sagar Samtani, Assistant Professor and Grant Thornton Scholar from Indiana University's Department of Operations and Decision Technologies.

AI for Cybersecurity - Overview of the Field and Promising Future Directions

RSA Conference
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