Industry executives and experts share their predictions for 2022. Read them in this 14th annual VMblog.com series exclusive.
What's in store for network detection and response
By Eyal Elyashiv, CEO and co-founder; and Dr. Aviv
Yehezkel, CTO and co-founder;
Cynamics
Businesses
and governments are in a vulnerable state. With cyberattacks proliferating
every industry and at greater speed, scale and sophistication, organizations
need to make bold moves to succeed in this fight. Cybercriminals are
opportunistic and during the pandemic, they were able to capitalize on the fact
that critical infrastructure had to move operations online nearly overnight to
accommodate the need for remote work. Organizations need to utilize protection
capabilities to bridge that gap created in the rapid transition to the cloud
during COVID-19.
Threats to the network continue to grow more
sophisticated
Attackers,
terrorist groups and political activists are going to be using advanced
technological capabilities to progress their agendas and carry out more
sophisticated and widespread attacks than when business and the global economy
were in survival mode. In the coming year, we'll see more of this taking place.
Cybercrime is an iterative process; just as our solutions and technologies get
smarter, so do the very criminals who seek to take down corporations and
governments for ransom.
Bad actors will take greater advantage
Just
like organizations are using AI to cut through the noise and provide predictive
rules - curating intelligence beyond what the human brain is capable of -
cybercriminals are also taking advantage of this technology. AI can be found on
both sides of the coin; AI is arming opportunistic bad actors with the
intelligence needed to study and target organizations through things like
random memory attacks, identification of specific vulnerabilities, exposing
weaknesses, and launching custom attacks that go undetected due to no actual
misconfiguration. Organizations need to fight machines with machines to
overcome, outsmart, and dead end these attackers.
The need for total visibility will be top of
mind for network security operators
In
the never-ending game against cybercriminals, network security operators must
continuously monitor the landscape. But they're burdened with using a myriad of
tools that require integrations, knowledgeable personnel to manage and update
systems. This is cumbersome, time-consuming, expensive, and if not closely
monitored, could expose backdoors. Network operators must keep pace with
advanced technologies and interconnectedness, but this leads to an increase in
the attack surface, network complexity, and progresses the thread landscape due
to potential vulnerabilities and exposed backdoors. It's impossible for
businesses and governments to get ahead of the curve when they're deploying
reactive cybersecurity - which is riddled with holes, exhaustive, costly, and
not a long-term solution to an ever-ending problem.
Moving toward AI-based network detection and
response
Traditionally,
network detection and response (NDR) solutions have utilized deep packet
inspection (DPI) to manually process traffic across the network. This was
sufficient decades ago, but with today's landscape and increasing connectivity,
it's nearly impossible for organizations and governments to adequately monitor
the volume and variety of network traffic. Going forward, next-gen NDR solutions
must use pattern inspection to analyze and monitor network traffic.
Organizations will start capitalizing on AI and ML to digest traffic behavior,
comparing historical values and trends to identify and predict suspicious
patterns. Solutions that offer sample-based tools to support multi-architecture
and multi-environment will gain in popularity as these can collect data from
every network device and provide a flow summarization of 100% of the network
packets. This lowers processing costs, requires no changes to the network, and
imposes no additional risk on organizations.
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ABOUT THE AUTHORS
Eyal Elyashiv is the CEO and co-founder and Dr. Aviv Yehezkel is the CTO and co-founder of Cynamics. Cynamics is the only Next Generation (NG) Network
Detection and Response (NDR) solution in the market today using standard
sampling protocols built-in to every gateway, patented algorithms, and AI and
Machine Learning, to provide threat prediction and visibility at speed and
scale.