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Convergent Quantitative Cyber Risk Assessment to Optimize (Mining) Enterprise Reliability

Convergent Quantitative Cyber Risk Assessment to Optimize (Mining) Enterprise Reliability

Jun 21st, 2018

Date/Time
Date(s) - 21/06/2018
12:00 pm - 1:30 pm

Location
CIM MES

Categories


CIM MES invite Franco Oboni to present on Convergent Quantitative Cyber Risk Assessment to Optimize (Mining) Enterprise Reliability

Convergent Quantitative Cyber Risk Assessment to Optimize (Mining) Enterprise Reliability

  • Cyber risks in mining companies are a reality like those generated by storms, quakes and equipment failures.
  • The deployment of an adequate siloes-busting convergent risk analysis methodology eliminates capex squandering and increases overall enterprise reliability.
  • We should seek to maximize mitigative benefits within sustainable and reasonable investments.

Convergent Quantitative Cyber Risk Assessment to Optimize (Mining) Enterprise Reliability

Information technology (IT) , Internet of Things (IoT), and spreading connectivity are bringing very significant benefits to mining, but increase the mining industry’s exposure to cyber criminals and possibly terrorists. This phenomenon is general and occurs in every single industrial, infrastructural and service space, not only in cyber risks in mining.

During the last decade the techniques and tools of cyber attacks have become more sophisticated, the distinctions between actors and threats have become blurred and attack prospects more worrying.

Reportedly at least one major mining company has been the target of a massive hack, but serious infrastructural damages have only seldom been inflicted, and not in mining (as far as we know), but in other industries. Indeed, given the rapid escalation in the number and sophistication of cyber attacks, infrastructural damages are to be expected “any time”. Any infrastructural damage, especially those with environmental consequences or harm to people, will lead to significant crisis potential, reputational damages and legal consequences. Cyber risks in mining oil and gas companies are a reality we cannot ignore.

Wide spectrum of threats and potential consequences

There is a wide spectrum of threats and potential consequences spanning across the various functions of a mining company. From management to production and logistics. It show that:

  • siloed approaches do not work,
  • integrative one are slightly better and finally,
  • convergent approaches offer an optimum to increase reliability while mitigating risks.

Broad spectrum protection investments and particularly poorly prioritized ones are not efficient. Indeed other operational requirements oftentimes limit their scope. So it is simply not possible to protect each property from each threat. The cyberdefense must find its roots in intelligence based on convergent prioritized Risk Management. Not on standardized audits and practice of indolent regulations. Or the biased advice of fear monger solutions sellers.

Encouraging information

Encouraging information reports that, recently and in some cases, two-thirds of the overall capex on the cyber risk mitigation strategies was non-technology driven. The idea that cyber risk is not only an IT issue is finally sinking. This, however, does not necessarily mean the capex is allotted in the most efficient way at all, unless proper prioritization was performed and silo-culture is replaced by a “horizontal” thinking. And all of the above does not necessarily mean the integration of cyber risks in the ERM program.

Closing remarks

Cyber risks in mining oil and gas companies are a reality. The deployment of an adequate siloes-busting convergent analysis methodology will eliminate capex squandering and increase overall enterprise reliability.

Risk Management offers ultimately support for operational decisions and protection (mitigation). That is, provided that we:

  • define the level of acceptable risk reduction/ mitigation. and
  • formulate measurable performance targets to achieve.

 

Category: Risk Analysis, Risk Management

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