Page 14 - Security Today, November/December 2024

C O V E R S T O R Y
Damian Sobczyk/stock.adobe.com
Securing the Edge
Of course, once any degree of network connectivity or shared
access is attached to an edge device, the potential for intrusion or
vulnerability increases. This leads to a heightened need for secur-
ing the devices on the edge of a network, at the point where a
company’s internet service comes onto the network at each end-
point before the traffi c reaches a centrally orchestrated network.
Security at the edge can be highly effective and the fact that
it is decentralized gives organizations more options for manag-
ing their own unique security requirements. Securing the edge
of an organization’s network computing also protects data and
workloads in remote locations, which can be more vulnerable to
threats and intrusions.
Many customers running AI models on the edge will try to
build a wall of security around their IoT devices, placing cameras
in an isolated network that doesn’t have Internet access. That way,
they are not as vulnerable to attacks. In this case, it is critical
when you choose an IoT device or IP cameras to have many lay-
1 4 “One method that has been widely
embraced by the industry is
Edge AI. The emergence of edge
computing has transformed the
way security and surveillance data
is gathered, managed, processed
and stored for efficient use.”
ers of protection against attacks. Edge security can also be con-
fi gured in a layered approach, based on the idea that the more
“walls” that potential bad actors must penetrate, the harder it is
to ultimately reach the device.
An Edge AI approach can help large enterprises with existing
infrastructures of hundreds of cameras as well as smaller organi-
zations just starting to adopt AI. Edge AI offers a fl exible, cost-
N O V E M B E R / D E C E M B E R 2 0 2 4 | S E C U R I T Y T O D A Y