INDUSTRY WATCH
MACHINE LEARNING
MAKES SECURITY
TEAMS BETTER, AND
VICE VERSA. HUMAN-
MACHINE TEAMS
DELIVER THE BEST OF
BOTH WORLDS.
M
achine learning is all around
us, enriching our online lives
everyday. We see it with
our own eyes when search engines
accurately predict what we’re looking
for after we type only a few letters.
We feel it protecting our bank
accounts, evaluating credit card
transactions for signs of fraud. We
notice it in selections of articles
and ads in online newspapers. We
no longer think twice about these
conveniences; in fact, it’s hard to
imagine online life without machine
learning. In relation to cybersecurity,
machine learning has been
changing the game as a means of
managing the massive amounts of
data within corporate environments.
However, machine learning lacks the
innately human ability to creatively
solve problems and intellectually
analyse events.
It has been said time and again that
people are a company’s greatest
asset. Machine learning makes
security teams better, and vice versa.
Human-machine teams deliver the
best of both worlds.
Machine learning allows endpoint
security to continually evolve to
stop new attack tactics
The Dark Web is driven by intelligent
‘bad actors’ who are often financially
motivated to create new threats
www.intelligentcio.com
with new attack techniques. Security
becomes personal when you consider
the people behind the attacks,
making the human-machine team
the best sustaining defence.
CSOs empower security operations
to blend the best elements of
art and science, where security
team employees provide creative
responses and leverage machine
learning to provide high-
performance scientific responses.
While machine learning can detect
patterns hidden in the data at
rapid speeds, the less obvious value
of machine learning is providing
enough automation to allow
humans the time and focus to
initiate creative responses when
responses are less obvious.
By using a filter for optimisation
across the best advantages of both
human and machine elements, it’s
easier to evaluate the relationship
between them.
Machine learning adds critical
capability to security strategies
The process of security researchers
analysing malware to develop
signatures is still important, but
only as a capability to address the
large volume of known malware
because it cannot be expected
to evolve quickly enough to meet
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