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This keynote address argues that a professionalized identity workforce is a critical and urgent necessity for U.S. national security. The speaker highlights that while identity is the foundation for countering every major threat—from border security and cyberattacks to insider threats and fraud—the thousands of government professionals performing this work lack unified standards, formal training, and a defined career path.
The address warns that without a formalized and interoperable identity workforce; the nation remains vulnerable to adversaries who exploit identity vulnerabilities with increasing sophistication. The proposed solution is to establish a professionalized corps of identity experts, modeled after cyber and intelligence career fields. This would involve creating a clear competency framework, a training and certification pipeline, and formal career tracks. The result would be a more resilient nation, capable of faster threat attribution, stronger fraud prevention, and enhanced public trust in a rapidly evolving digital world.
Historically, both cyber and identity security systems have been designed to react to known threats, rather than proactively prevent the next threat. But is this wise? Has that orientation actually worked? It would appear that cyber attacks, breaches, hacks, frauds and other identity-related problems have grown, seemingly unencumbered, despite a massive economic investment in systems claiming to mitigate them. In fact, it's the reactive nature of these systems that enables the next attack to go unnoticed until after the fact. The dogma that identity data and biometric data must be bound to devices, rather than to each other, might help device manufacturers sell future generations of devices, but it also forces the reactive nature of identity and cyber security. It’s the intentional separation of these attributes that enables the attacks that traditional architectures can only react to. In this presentation, Jay describes why a proactive system architecture, the proper binding between a verified identity, the human that identity describes, and the privileges that person is entitled to is the key to preventing the next cyber-identity attack.
Law enforcement agencies have used tattoos for many years to assist in investigations. Historically, this has involved searching tattoo image databases using text descriptions of tattoos. However, the effectiveness of this method has been limited by the subjectivity of text-based descriptions. Recent advances in technology have enabled developers to leverage artificial intelligence (AI) to create automated, image-based tattoo search capabilities. Compared to traditional approaches that rely on subjective text descriptions, image-based searching provides a more objective means of retrieval. To determine whether these systems are fit for purpose, decision-makers will need to know their capabilities and limitations. NIST is running an evaluation program to assess the accuracy of tattoo recognition algorithms. This evaluation will measure the capability of these algorithms to detect tattoos in an image and to perform automated matching of different images of the same tattoo from the same subject over time. Thistalkwill present the state-of-the-art accuracy in image-based tattoo recognition and discuss current capabilities and limitations of the technology.
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In this session, we'll share PayPal's journey deploying Passkeys across our platforms, reaching millions of customers worldwide. If you're interested in passwordless authentication or planning your own passkey implementation, we'd love to see you there.