Editing Chapter 6: Edge Security and Privacy (section)

===Securing Egyptian VMSs Smart City Infrastructure===
Over hundreds of thousands of these edge devices such as traffic sensors, surveillance cameras,
smart lighting systems, and environmental monitors are deployed in an urban Smart City. We
have on the `the city edge cloud' these instruments for real-time traffic flow management, public
safety alarm, environmental monitoring with life supports among the green plants – in the area
usually known as! This city suffered a massive blackout, when multiple traffic lights were compromised at the source which caused them to act irregularly: Not
issuing signals, leading to gridlocks.
====Challenges:====
How were the traffic controllers found to be vulnerable? Meaning they hack the password hole
punch so they can bypass the external username password and gain direct access to the temples
of our data. Moreover, on some cameras, the public IP of that camera is exposed, making remote
attack possible: it was obviously a disadvantage for them. The edge network stutters steps from
one organization to the next, making it hard however much one tries to apply security policy
uniformly, as whose department is solely responsible for a given thing?
====Solutions Introduced:====
;Net Separation
: The city designed its infrastructure with isolation zones; meaning traffic
systems are completely isolated from all other municipal services so if one zone is attacked all
other zones of that type remain intact.
;Password Overhaul
: Each unit was provided with a complete rehash to change its default
passwords and other weak credentials to hardened unique passwords. Remote administrative
access was only accepted with Multi-Factor Authentication.
;Embrace of a Zero Trust Model
: In this city, we employed a robust, Zero Trust model. A
central token service gives authorization to every device communication and does not assume
the inherent trust of devices.
;Firmware Handling
: The OTA management system required by installation ensures known
exploits like traffic light management are repaired when discovered. Firmware cannot be
updated at weaker sites as the assumption is it is regularly updated.
;AI-based IDS Deployment
: An AI-based IDS at a traffic control center learns about every
equipment normal behavior going on at this session (like how frequently commands are sent out
for lighting systems) generate alerts, activate promise lockdowns any time an abnormal behavior
appears Mechanisms for rapid dissemination throughout the city.
==== Outcome:====
As a result of the proactive settings, these attempts were quickly identified and contained, with a
limited impact on operations. For example, a virus event that targeted digital kiosks was
contained through micro-segmentation and AI detection mechanisms that quickly isolated and as
such quarantined the attack. It led to enhanced overall resilience of this intelligent city — its
citizens’ trust in IoT services is continually getting better.