Mathematics and machine learning approach at the advent of cyberattacks and threats mutations and sophistication.
In our digital-world, flooded by the unstructured and structured data from
multiple sources (online, on-premise, mobile, sensors, trackers, etc.),
combined with the power of this new currency, it is henceforth clear to observe
that, the rate at which these
threats mutate and the sophistication with which they traverse networks is
frequently astounding and has transformed the way we need to think about our
defensive strategies.
At , Connectikpeople.co soon #Retinknow®, when it
comes to meet this reality, we recommend collaboration in terms of information,
intelligence, technologies, strategies, good practices, and good methodologies
between all actors (solution providers, end-users, specialists, to name a few),
of the cyber security industry.
The mathematics and machine learning approach and methodologies,
progressively gain in maturity, by their capability to help delivering:
- Real-time, self-learning threat detection capabilities,
- Helping to develop new signal intelligence capabilities,
- Strategic planning for understanding and responding to cyber-attacks,
- Abilities to experiencing threats of all forms and factors,
- Detect when abnormal events occur ,
- Enterprise Immune System technology,
- Self-learning platform to spot anomalous activity within the enterprise.
As part of our global commitment, Connectikpeople.co
soon #Retinknow®, encourages Darktrace, to continue addressing the
challenge of insider threat and advanced cyber-attacks through its progressive ability
to detect previously unidentified threats in real time.
