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While it is relatively easy to thwart insiders who should not be accessing certain IP, stopping the developers of the IP is more challenging. This practical session will explore a scenario based on details disclosed in the FBI’s affidavit discussing the potential theft of trade secrets from GE. How can human-behavioral analytics aid in protecting IP from those who have legitimate access?
Learning Objectives:
1: Understand overlooked need to protect IP from those who create it or legitimately interact with it.
2: Gain a practical framework for choosing between various monitoring strategies and data sources.
3: Learn how to construct a defensive perimeter to effectively detect precursors to actual data theft.
Pre-Requisites:
Interest in learning more about standing up insider threat programs.
Learning Objectives:
1: Understand overlooked need to protect IP from those who create it or legitimately interact with it.
2: Gain a practical framework for choosing between various monitoring strategies and data sources.
3: Learn how to construct a defensive perimeter to effectively detect precursors to actual data theft.
Pre-Requisites:
Interest in learning more about standing up insider threat programs.
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