editor’s question
weather patterns, for example) or
analysing data in a computer
network (to highlight
anomalies that indicate a
security threat).
DAVID EMM,
PRINCIPAL
SECURITY
RESEARCHER AT
KASPERSKY LAB
O
ne of the danger s
of hype, in any
area of human
activity, is that
some people
use it to create
unrealistic
expectations. When the ‘bubble’ created
by the hype bursts, there’s a risk that the
positive elements that underpinned the
hype get lost also – i.e. that we end up
throwing out the baby with the bathwater.
This is certainly possible with the hype
surrounding ‘AI’ – which threatens to
overshadow the real development and
application of intelligent systems.
And yet Machine Learning undoubtedly
brings great benefits. Without it, we
would drown in a sea of data. Intelligent
systems allow us to automatically gather
data, analyse the data in real time and
make informed decisions.
This could include analysing data in
a physical environment (to predict
30
Vendors continue
to invest in smart
technologies,
including Machine
Learning that has
been developed to
detect sophisticated
targeted attacks and
proactively protect
against future threats.
One particularly promising
area of development is in
increasing the complexity of the
correlational picture of events across
all levels of infrastructure and further
machine analysis of the data landscape
to detect the most complex cyberattacks
accurately and reliably.
Machine Learning is not new.
Technologies have been used for many
years. In cybersecurity, for example,
robots do a great deal of the work. They
find and identify malware and analyse
it, then they create a ‘repellent’, test and
distribute it and make it a part of the
global protection.
All this happens hundreds of thousands
of times a day – automatically. Moreover,
the robots are always learning and the
detection is constantly correcting itself
and improving. Only a tiny fraction of
the work needs the input of a human
expert. Nevertheless, the combination of
machine and human remains essential.
The key feature of pure ‘AI’ is the ability
for a machine to forever improve and
It is of utmost
importance that all
Machine Learning
devices are robustly
secured.
Where a technology
is being built into
our world gradually
and affects every
different area of
our lives, the threat
vector grows.
perfect itself without the intervention of
man – an ability that may grow and grow
to eventually step outside the bounds
of its algorithms. There is no doubt that
developments in AI are set to accelerate,
becoming more integral to the industry.
For some time to come, however, human
input remains essential.
It’s also important to remember that
there will always be those who seek
to exploit technology for illegal and/or
immoral reasons. We know that hackers
will always look to exploit security flaws
in any vulnerable devices or networks.
Building Machine Learning into our
society presents amazing opportunities
but it also poses worrying implications to
its infrastructure.
Where a technology is being built into our
world gradually and affects every different
area of our lives, the threat vector grows.
If this technology isn’t implemented
securely, it could result in widespread
vulnerabilities – even more so as we
become more reliant on these systems.
It’s always a cat and mouse game in
cybersecurity – where opportunities for
growth can be explored, cybercriminals
will work to develop attacks on and
against them.
We’ve seen critical systems infiltrated
and sabotaged in the past and it is likely
that they will continue to be targeted
well into the future – so it is of utmost
importance that all Machine Learning
devices are robustly secured. u
Issue 06
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