Aprendizado de máquinas aplicado à segurança cibernética de plantas industriais

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This document discusses how machine learning can be applied to industrial control system (ICS) cybersecurity. It provides examples of machine learning applications like self-driving cars and recommendations. For ICS cybersecurity, the Nozomi SCADA Guardian solution uses machine learning to automatically discover industrial network assets, develop security and process profiles, and monitor the system in real time to detect cyber threats and process anomalies. It concludes by demonstrating how machine learning could protect a natural gas plant and questioning if companies are truly protected against attacks.

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Machine Learning applied to ICS Cybersecurity
Disruptive technologies in the fight against cyber attacks
Hannover, April 2019
Marcelo Branquinho, CEO & Founder

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Marcelo Branquinho
CEO & Founder
marcelo@tisafe.com

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Agenda
• What is Machine Learning?
• The use of Machine Learning in ICS Cybersecurity
• Using Machine Learning to Protect a Natural Gas Plant

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Why security
solutions fail?
• One popular solution used in ICS Cybersecurity
is to install a firewall between business and
control networks.
• Known as “Bastion Model” since it is based on
a single point of security.
• Example: Chinese Wall

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Pathways inside the control network
• Protecting only the perimeter of the OT network is not
enough.
• A Worm infiltrated in:
o A nuclear plant through a mobile 3G connection
o A SCADA power system through a VPN
o An Oil & Gas control system through the laptop
of an outsourcer
• There were firewalls protecting the OT network
perimeter in all these cases.
• It’s necessary to protect the factory floor with modern
and in-depth defense technologies.

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
What is Machine Learning?
• Machine learning is a method of data analysis that
automates the construction of analytical models.
• It is an artificial intelligence strand that is based on
the idea that systems can learn from data, identify
patterns and make decisions with the least human
intervention.
• It was born of pattern recognition and the theory that
machines can learn without being programmed to
perform specific tasks.
• The iterative aspect of machine learning is important
because, as models are exposed to new data, they
can adapt independently. They learn from previous
calculations to produce reliable, repeatable
decisions and results.

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Where is Machine Learning used?
• Here are some well-known examples of machine learning applications:
• Autonomous Google cars: the essence of machine learning;
• Suggested offers such as Amazon and Netflix: daily machine
learning applications;
• Know what your customers are talking about you on Twitter:
Machine learning associated with creating language rules;
• Detection of undue behavior of equipment in automation systems
(ICS): machine learning applied to industrial cyber security;

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
The use of Machine Learning in ICS Cybersecurity
• Machine Learning technology is implemented in the
Nozomi SCADA Guardian solution, specific for ICS
Cybersecurity
• Detects cyber threats and process anomalies,
providing unprecedented operational visibility.
• Automatically discovers the industrial network
assets, including its components, connections and
topology.
• Develops security and process profiles, as well as
monitoring the system in real time for any change.

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Using Machine Learning to
Protect a Natural Gas Plant
Technical demonstration that shows how
Machine Learning technology can be applied in
ICS Cybersecurity.

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
How will
your
company
respond to
an attack
like this?
Are there cyber
security
specialists in
the automation
team?
Is your
company's
automation
network really
protected?

© 2007-2019 – TI Safe
All rights reserved www.tisafe.com
Thank You!
marcelo@tisafe.com
Want to know more, see Machine Learning live
in our stand at Digital Factory.

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O documento discute a análise de riscos de cibersegurança, planejamento e implantação de contramedidas para conformidade com as novas regras do ONS para o Complexo de Belo Monte. Apresenta o histórico de cibersegurança da Norte Energia, a necessidade de conformidade regulatória e o planejamento de segurança. Também descreve a contratação da TI Safe para fornecer a solução ONS Ready e o progresso do projeto, com a Fase 1 concluída e a Fase 2 parcialmente implementada.

CLASS 2022 - Nycholas Szucko (Nozomi Networks) - Antifragilidade Cibernética ...

TI Safe

CLASS 2022 - Gustavo Merighi (Energisa) e Alessandro Moretti (Thales) - O Des...

TI Safe

O documento discute o desafio de implementar controle de acesso e autenticação multifator (MFA) no Grupo Energisa. O Grupo Energisa implementou uma solução tecnológica de MFA para melhorar a segurança, cumprir normas regulatórias e restringir acessos não autorizados. A implantação enfrentou desafios como a falta de base centralizada de usuários e mudança de cultura. A solução é gerenciada por meio de um SOC interno que monitora tentativas inválidas de login e aprova novos

CLASS 2022 - Marcelo Branquinho (TI Safe) - Ameaças Modernas e Ataques às red...

TI Safe

Webinar cci por que nao se deve contratar so cs de ti hibridos para proteg...

TI Safe

Este documento discute por que não se deve contratar SOCs de TI/híbridos para proteger redes industriais. Primeiramente, devido às diferenças no viés operacional entre TI e automação industrial, com a disponibilidade sendo o principal pilar de segurança para sistemas industriais. Além disso, pessoas, tecnologias e serviços de um SOC de TI podem não ser adequados para redes industriais e colocar a operação em risco. Um SOC dedicado à automação industrial deve ter especialistas qualificados, tecnologias apropriadas e procedimentos volt

Retrospectiva

TI Safe

Em 2020 o mundo experimentou uma situação inédita para a maioria dos seres humanos: uma pandemia global, provocada por um vírus desconhecido, que gerou mudanças significativas na vida de todos. No universo das empresas, foi observado um movimento de intensa digitalização de processos e adequação ao distanciamento social. Muitas delas, inclusive as indústrias, adotaram o trabalho remoto para seus colaboradores. Conforme as empresas adaptaram as suas operações, os criminosos também estabeleceram mudanças. São facilmente encontradas notícias relativas a golpes por email, WhatsApp e telefone. E com “chave de ouro”, 2021 foi aberto com o mega (ou seriaTera?) vazamento de dados de brasileiros, o que fornece mais combustível para esses golpes. O ICS-SOC (Centro de Operações de Segurança Cibernética Industrial, localizado no Rio de Janeiro) da TI Safe protege seus clientes contra ataques cibernéticos que possam afetar suas operações, fundamentais para a população e a cadeia de suprimentos do Brasil.Os dados de (milhões de) ataques de 2020, relativos a projetos desenvolvidos pela empresa, foram analisados para entender o aumento dos ataques em relação a 2019. Por uma questão de privacidade dos dados dos clientes, as informações serão apresentadas em percentuais.

Pacote TI Safe ONS Ready v1

TI Safe

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