New York CISO Town Hall
October 29, 2024 | 11:00am EDT
October 29, 2024 | 11:00am EDT
A New Paradigm for Managing Third-Party Risk
Participate with your CISO peers in the New York community in small, breakout discussions on a mission-critical priority for security leaders. These informal discussions allow you to share your insights and learn from the lessons, approaches and experiences of a diverse group of peers in virtual breakout rooms.
Join fellow CISOs in the New York community to discuss:
Balance Risk Mitigation and Value Creation
Facilitate Secure Decision-Making with Outcome-Driven Metrics
Thrive Amidst Complexity and Uncertainty
Discussion Leaders
Members of the New York CISO community will lead the interactive discussion and share lessons learned.
Shimon Modi
Dataminr
VP, Product Management, Cyber
Presenter
Linda Angles
CAA
Global IT Risk Leader
Discussion Leader
Ely Pinto
Simpson Thacher
Global CISO
Discussion Leader
Patty Voight
Webster Bank
CISO and Tech Risk Manager
Discussion Leader
Doug Greene
Guardian Life Insurance
CISO
Discussion Leader
Tomas Maldonado
National Football League
Chief Information Security Officer
Discussion Leader
Agenda
October 29, 2024
11:00am - 12:00pm EDT
A New Paradigm for Managing Third-Party Risk
Hosted by Dataminr
In the past 12 months, 87% of F1000 businesses were affected by significant cyber incidents as a result of a third-party. And yet, most rely on ‘snapshot in time’ questionnaires. While necessary, snapshots are insufficient by themselves, and must be augmented with continuous monitoring in support of ongoing security operations. This requires a different approach, that includes external threat detection capabilities by using AI across Public Data.
Join this Town Hall to learn about:
- The Public Data opportunity: collect, process, alert across multiple languages / modalities
- Real-time external threat detection on a rapidly evolving threat landscape
- The most advanced AI techniques for automating the collection, processing, delivery, and initial analysis of millions of public data sources
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