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Deep Learning at the Edge Drives New Models for Security

In this special guest feature, George Brostoff, Founder and CEO of SensibleVision, shows his excitement about AI’s potential to dramatically transform and improve the security space. When most people think of AI and security, they conjure how it might be applied to prevent hackers and malicious actors from penetrating Enterprise databases, stealing customer credit card numbers or social media profile information. But AI has the power to improve security much more broadly.  George has founded three successful tech companies, holds seven patents and grew up working in a family business. Based on his contributions to the business community, George was selected as Entrepreneur of the Year by the Detroit Free Press and Michigan Technology Council. He also received the Governor of Michigan Certificate of Appreciation for Outstanding Business Achievement. George is a graduate of the University of Michigan.

It is safe to say that AI continues to dramatically reshape traditional business processes and protocols across every industry. As an entrepreneur working for over 20 years in vision based, biometric-driven authentication, I am very excited about AI’s potential to dramatically transform and improve an area that is near and dear to me: security.

When most people think of AI and security, they conjure how it might be applied to prevent hackers and malicious actors from penetrating Enterprise databases, stealing customer credit card numbers or social media profile information. But AI has the power to improve security much more broadly.

Brain on a chip

AI solutions are not only becoming more powerful, they are also becoming more portable. As businesses continue to create exabytes of data on a daily basis, deploying AI is going to be increasingly vital to managing secure access when interacting with this torrent of information. No human brain could possibly manage it – and the implications for providing security are daunting.

The good news is that AI and machine learning solutions have been making their way from the cloud out to the edge of the network and have the potential to dramatically transform the broader security paradigm.

For example, in January at the annual CES show in Las Vegas, a new generation of AI chips was unveiled from a handful of companies including CEVA, MediaTek, NXP, Samsung, and startup Gyrfalcon. These so-called “brain on a chip” solutions are moving AI moving down the stack and opening up applicability in previously unlikely settings that will certainly impact security writ large.

Broader implications

As 3D cameras get smaller and more robust, and faster and more powerful software is developed to take advantage of the new generation of dedicated AI-chips, we are going to see a transformation in terms of how we think of security.

In the consumer space, AI-based security is already being introduced to let users unlock their smartphones and tablets quickly and securely. Apple’s iPhone X with its FaceID is an early example of this kind of approach. But AI-based solutions also have the potential to impact domestic security more broadly – helping us monitor access to door locks to keep unwanted intruders away. Making sure only authorized drivers have access to our vehicles. Our homes and cars will be much safer as they are enabled by robust AI-driven security solutions.

In commercial settings, AI can enable secure surveillance cameras capturing 3D face data. These kinds of solutions can be used to monitor access to physical settings including data centers, warehouses, border crossings, hospitals, transportation hubs and manufacturing locations. These AI-enabled approaches have the computational power to not be fooled by photos, images or videos. They are also not adversely affected by factors such as environmental conditions, camera location, lighting and subject size and behavior. Security personnel will have an increased level of control when monitoring and managing access to buildings or locations and determining who should be allowed in and who represents a risk.

And as the IoT continues to grow and more and more objects have IP addresses, AI will be used to manage secure access to the galaxy of sensors and actuators connecting everything from our cars to our clothing to our appliances.

AI-enabled security capabilities have already made inroads into smartphones and tablets and to a lesser degree in automobiles. But as AI continues its move to the edge and away from the cloud, enabled by dedicated chips and powerful software, we will see it exploited in a range of unlikely settings to enable a whole new security paradigm.

 

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