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adapt, learn and secure. This is crucial
to enabling the huge potential of this
technology to be realised.
By setting up comprehensive visibility
Machine Learning-based analytics can
also build baselines for normal IoT
devices – like authentication, remote
access and internal access to high-value
resources as well as cloud app usage
across network and log data.
Step three: Monitoring for
suspicious behaviour
Once you’ve used the above steps
to allow a device onto your network
however you can’t just leave it
unchecked. You can only accurately
enforce and create a relevant and
applicable access policy if you are
continually monitoring activities.
Active monitoring is essential to keeping
your network secure, looking for
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Issue 22
authenticity, new behaviours and new
vulnerabilities – profiling and analytics
are key here.
A friendly device may not always be
friendly and you should always be on the
lookout for recognised devices acting
in unusual ways or trying to access
different parts of the network. Security
is a constantly evolving and changing
landscape and unfortunately the job will
never be ‘done’.
Securing the IoT revolution
The advent of IoT has the potential
to revolutionise business critical
applications. We shouldn’t shy away
from this potential because of concerns
about risk – instead we must plan,
as an essential foundation and then
building Machine Learning and Artificial
Intelligence on top of this teams can
stay one step ahead of, and reduce,
the escalating number of risks facing
the business. Security is not a barrier
to IoT adoption, it is the cornerstone for
successful adoption. u
Security is not
a barrier to IoT
adoption, it is the
cornerstone for
successful adoption.
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