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Darktrace Industrial uses machine learning to identify cyber campaigns targeting critical infrastructure

By Paul Dvorak | November 16, 2017

Darktrace, a developer of machine learning technology for cyber defense, has announced the creation of Darktrace Industrial, a new business unit dedicated to identifying emerging and existing compromises on industrial systems and critical infrastructure networks.

Darktrace says its Industrial Immune System technology uses AI algorithms that mimic the human immune system to defend industrial networks of all types and sizes. 

“Cyber-threats to critical infrastructure are evolving at a pace that is nearly impossible to keep up with, and coupled with the escalated international attention to ICS threats, the security of our systems is our utmost business priority,” commented Michael Sherwood, Director of Technology and Innovation, City of Las Vegas.

“Darktrace Industrial is fundamentally changing the game of ICS cyber defense – armed with its machine learning technology, we feel confident in our ability to identify the subtle and increasingly sophisticated attacks threatening our infrastructure. The Industrial Immune System’s combination of genuine AI and unprecedented visibility heralds a new future for proactively defending OT environments.”

Threats to critical infrastructure are garnering worldwide attention. Recently, the U.S. government issued a rare public warning that sophisticated threat-actors are targeting energy and industrial firms. In addition, the European Union Network and Information Security (NIS) Directive introduced security requirements as legal obligations for operators providing essential services including industrial automation control systems and connected devices.

A product update, Darktrace Industrial Immune System version 3, can detect silent and subtle attacks on control systems with new capabilities including:

  • New mathematical techniques focused on detecting low and slow attacks
  • Powerful ways to analyze and visualize ICS zone structures
  • Improved detection of compliance breaches within OT environments
  • Expanded support for legacy industrial systems and non-traditional IT, such as IoT

    Industrial environments, reliant on legacy bespoke systems, face new security challenges such as connected industrial devices, sensors, remote maintenance repair operations, and increasing connectivity to IT environments. Darktrace’s self-learning approach understands the normal ‘pattern of life’ for every operator and device automatically without requiring agents, or knowledge of operating systems.

    “Industrial control systems have long operated under ‘air-gap’ principles that assume their isolation from IT and publicly accessible networks. In reality, many are accessible from IT networks for control and integration,” commented Scott Crawford, Research Director for information security with 451 Research. “As ‘smart’ technologies become more integral to physical controls, their wide accessibility and connections to public networks are only likely to grow. This is an increasingly serious concern, considering the public and personal safety dependent on ICS, and the potential for disruption and catastrophic damage.”

    “With increased digitization and the rise of the Industrial Internet of Things, the need for cybersecurity within operational environments has never been higher,” commented Andrew Tsonchev, Director of Technology at Darktrace Industrial. “Darktrace has a four-year investment in the Industrial Immune System, the world’s first and only proven machine learning technology capable of detecting emerging attacks on OT environments, including ‘low and slow’ attacks, and ‘unknown unknowns’. Darktrace Industrial will enable the accelerated adoption of this pioneering technology, which already defends some of the world’s most complex industrial control environments from nuclear plants to power grids.”

    For more information:  darktraceindustrial.com


Filed Under: Cybersecurity
Tagged With: Darktrace
 

About The Author

Paul Dvorak

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