Zero in on the right Cyber Risk Quantification models for your business
Culinda Inc.,
Your Bio-Medical IoT made safe with one solution by healthcare professionals focused on healthcare security.
October has been tough for enterprise security, with major brands falling prey to major cyberattacks. Japanese electronics giant Casio is one such casualty. The effects? System downtime, negative publicity, as well as theft of sensitive data including that of employees, contractors, and business partners. Such colossal costs necessitate the use of apt cyber risk quantification (CRQ) models, especially in healthcare organizations.
Cyber risk is an inevitable cost of doing business in the modern world. An organization’s readiness to mitigate cyber risk exposure as much as possible becomes a competitive advantage in such situations. As the time proven adage goes, “You can’t manage what you can’t measure.” This is where cyber risk quantification steps in to ensure end to end business protection. In case you are new to cyber risk quantification or need to brush up on the topic, here is a handy read on the evolution of cyber risk quantification.
Selection of the right cyber risk quantification models is essential to gauge each incident’s full monetary impact and initiate proactive action. For example, what is the actual cost that your business incurs in case of a ransomware attack or a data breach? Let us assume that the use of a suitable CRQ model pegs the cost of a data breach incident at USD 5 million for your business. Such calculations typically also account for effects like loss of reputation, data privacy issues, system downtimes, and regulatory penalties. This enables infosec and risk management teams to prioritize your cybersecurity dollars in an efficient manner.
Understanding cyber risk quantification models
Broadly speaking, commonly used CRQ models tend to use quantitative, qualitative, probabilistic, or scenario-based modeling approaches. Certain models also use adaptive risk assessment frameworks.
Cyber risks come in all forms and sizes. This is why selection of the right CRQ model that addresses different organizational needs proves essential. Many of these models continuously analyze inputs from sources like open-source Intelligence (OSINT), historical data, threat intelligence feeds, and vulnerability trackers. Suitable modeling techniques are then used to determine events or repercussions.
For instance, quantifying financial risks due to a security incident might call for use of the FAIR model. On the other hand, Web application security assessments are better served by models like the OWASP risk rating. If your risk quantification objectives prioritize the need to predict possible financial losses, simulations that leverage Monte Carlo models might be a good fit.
Popular CRQ models in use today leverage the following methodologies:
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Figure: Selection of CRQ models based on usage scenarios presents a quick overview of the differences between popular CRQ models and their applications.
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One stop CRQ model management
Optimal usage of CRQ models calls for significant levels of integration and orchestration. Automation along with comprehensive tools and governance mechanisms goes a long way on this front. These must be backed by periodic monitoring, reviews, calibration, and validation.
As we have discussed earlier, integration of CRQ with Enterprise Risk Management (ERM) delivers rich dividends. These initiatives ensure holistic risk management across the organization. Such synergies significantly advance data privacy and regulatory compliance objectives, especially in sensitive verticals like healthcare. Other advantages include better decision-making capabilities and infosec investment prioritization.
End-to-end Cyber Asset Risk Management (CARM) platforms like Culinda complete the CRQ-ERM equation. These are especially nifty when it comes to management of insider threats like BYOD, shadow IT, or even threats from third parties like contractors. These platforms integrate seamlessly with existing security processes and tools for higher levels of operational efficiency.
Modern CARM platforms include extensive CRQ features like threat intelligence, advanced risk models, and advanced analytics. Single pane of glass management overview streamlines documentation, reviews, and updates of potential threat vectors.??
Boost your risk management posture exponentially with optimal CRQ models. Contact us now to know more about 360-degree cyber risk quantification possibilities.
Chief Medical Informatics Officer | Healthcare Executive | Board Advisor | Entrepreneur | Consultant | KOL
4 个月Risk Stratification using objective data is the only way to give real visibility to your network and connected devices. For me, it is unimaginable to go without tools such as Culinda. Understand your vulnerabilities and address them accordingly. With the threats of bad actors attacking our most sensitive data, such as healthcare and banking, how can we ever leave ourselves exposed?