What is cyber risk modeling

Cyber risk modeling - why it's important

As malicious actors continue refining their attack methods, the average cost of a data breach is rising. Consequently, companies must devise cyber risk mitigation strategies and implement the required security controls to better protect their networks and infrastructure with an appropriate sense of urgency.  

Unfortunately, the technical nature of cyber security means that IT personnel often have difficulty accurately conveying the danger posed by cyber threats to senior management. Boosting the company’s cyber security costs money, after all. So. as they attempt to balance the overall needs of the business, it’s common for company stakeholders to underestimate the importance of cyber security – and not allocate enough funding as a result. This is where cyber risk modeling comes in.  

Cyber risk, or cyber security risk modeling, is a method of risk identification and assessment. Cyber security models enable security and risk teams to quantify the potential impact of the various cyber threats faced by their company and present them in clear, financial terms that their senior managers and decision-makers will understand.  

With this in mind, Let’s take a closer look at cyber risk modeling and how companies can benefit from it. 

How does cyber risk modeling work? 

Cyber risk modeling involves using software to create a comprehensive data model representing the company’s cyber risk factors, i.e., all the potential cyber threats it faces. A typical cyber security model could include thousands, if not tens of thousands, of probable cyber attack and data breach scenarios, to create an as realistic and accurate picture of a company’s risk profile as possible. 

Cyber modeling solutions allow companies to capture and quantify a wide range of potential cyber incidents, accounting for varying frequency and severity. Ideally, cyber security models should also calculate risk aggregation, i.e., how individual cyber risks interact and compound, to get a more precise picture of a company’s risk exposure. 

When modeling risk, a company should incorporate threat intelligence data from several places, including: 

Cyber risk analytics  

Carrying out security assessments of a company’s risk factors by drawing real-time data and metrics from its own applications, systems, and network. Consistently obtaining accurate analytics requires integrating the cyber risk modeling solution with the right cyber security tools, namely continuous monitoring applications that constantly scan a company’s IT ecosystems and, subsequently, collect actionable data.  

Historical data 

Robust cyber security models should also incorporate as much relevant data on past cyber incidents as a company can acquire. This includes the company’s own historical data, such as log files, and third-party data sets. Externally-sourced historical data could consist of in-depth analytics on major, global-scale malware attacks, like WannaCry or SolarWinds, allowing companies to integrate them into their cyber security models.  

Current cyber security trends 

A company’s cyber risk model must be continuously updated with real-time threat intelligence from external sources to reveal the full extent of its risk factors. To this end, some risk modeling solutions grant companies access to an expansive threat intelligence database, which collates data from millions of organisations worldwide. Subsequently, this enables data enrichment, whereby a company combines its data with that collected externally to improve its model’s accuracy. 

How does cyber risk modeling benefit your company? 

Here are some of the main benefits that cyber risk modeling offers companies: 

  • They enable companies to determine the cost of particular cyber risks. This allows for better threat prioritisation, which enhances the company’s overall cyber risk mitigation strategy and aids in its decision-making. 
  • They translate the technical terminology of cyber security into business language, i.e., financial impact, helping to get company management and their IT and security teams on the same page. 
  • Subsequently, cyber security models help IT and security managers sell their proposed cyber security initiatives to stakeholders, as they have the concrete data to justify their requested budget. 
  • The threat intelligence provided by cyber modeling software makes security teams more aware of their IT security gaps, allowing for more effective risk mitigation. 
  • Similarly, increased awareness of its risk profile allows a company to develop more comprehensive disaster recovery plans.  

An example of cyber risk modeling  

To better illustrate how cyber modeling works let’s consider a brief example. 

So the company uses a modeling solution to create a cyber security model, drawing threat intelligence data from: 

  • Its own infrastructure: data and metrics from firewalls, antivirus software, vulnerability scanners, intrusion detection systems, penetration tests, etc. 
  • Third-party real-time data, i.e., up-to-date, global threat intelligence databases. 
  •  Third-party historical data (where available). 

By analysing the quantifiable data from these sources, the company determines that the risk factors with the highest likelihood, severity, and, consequently, most considerable financial impact are:  

  1. Ransomware attacks 
  1. Supply chain risk 
  1. Unpatched software vulnerabilities 
  1. Phishing attacks and subsequent data exfiltration 
  1. Botnet attacks 

Starting with the top priority, the company’s security and risk teams calculate that the average cost of a ransomware attack in the last 12 months was £5 million. Meanwhile, a proposed IT infrastructure project to implement the required cyber security controls to better protect the company against ransomware will cost £1 million. Armed with these financial loss projections and the threat intelligence data to back them up, a security or risk manager has a more compelling argument for proceeding with the proposed cyber risk mitigation strategy and has a better chance of securing the backing of (and funding from) non-technical stakeholders.  

How does a data-led approach help fix cyber risk exposure?  

Quantitative, data-led risk analysis, like cyber risk modeling, offers a more effective alternative to companies’ qualitative methods. This includes the use of risk matrices, which assign risks rating of “low”, “medium”, and “high” or something similar. While these ratings may be reasonably accurate, they’re often based on opinion rather than hard data. However, this is inherently flawed as people can become too invested in their perceptions, despite evidence pointing to the contrary.  

In contrast, threat intelligence data is more reliable and accurate because it’s verifiable, often by multiple sources, and unbiased. You can always rely on data to change immediately to accurately reflect a company’s risk exposure – while opinions can be slow to shift. Additionally, as detailed earlier, data can be drawn from several places, including various third-party sources, to gain greater insight into risks and their potential impact.  

Plus, a data-driven approach leads to quantitative insights and conclusions that can be explained in financial terms to a company’s key decision-makers. Because cyber risk modeling translates the dangers posed by cyber threats into a language they can understand, it’s more likely that the cyber risk mitigation strategies proposed by the IT department are green-lit and funded.   

Cyber risk modeling vs cyber threat modeling  

Although the two terms are often used interchangeably, there’s a difference between cyber risk modeling and cyber threat modeling.   

Cyber risk modeling involves identifying and assessing a broad range of risk scenarios to quantify a company’s overall risk exposure. This information is used to estimate the potential financial impact of cyber attacks, so company executives and other stakeholders better understand the importance of implementing cyber risk mitigation measures – and approve the necessary expenditure.  

So, what is threat modeling in cyber security, and how does it differ? A cyber threat model identifies different cyber threats, malicious actors’ possible attack vectors, and how well the company can mitigate them at present. Now, while cyber threat modeling measures the costs and benefits of mitigating particular cyber threats, its primary aim isn’t to present this information in financial terms, like cyber risk modeling. In contrast, the information presented by a cyber threat model is mainly for the benefit of a company’s various IT, security, and risk teams.  

How RiskXchange can help you manage risk  

The first essential step in managing your company’s risk is identifying it. Through our comprehensive attack surface assessment, we’ll help you identify, assess, and prioritise your company’s risk and show you the direct impact that a wide range of cyberattacks could have on your bottom line. 

Contact RiskXchange to get your company’s free attack surface score.