Cybersecurity Risk: Understanding Probabilities and Possibilities

In cybersecurity, risk is everywhere. From phishing scams and ransomware attacks to insider threats and zero-day vulnerabilities, every organization faces a constantly evolving threat landscape. Risk analysis in this context aims to give decision-makers the most accurate and actionable insights into the likelihood of potential cyber incidents and their impact.

But let’s address the reality: risk analysis in cybersecurity will never be perfect.

Cybersecurity risk models are approximations of reality. They rely on historical data, assumptions about adversary behavior, and system weaknesses—all to simplify an incredibly complex and dynamic environment. Yet despite their imperfections, risk analysis remains indispensable because it enables organizations to shift from reactive measures to proactive decision-making.

At the heart of cybersecurity risk analysis lies a fundamental concept: it’s about probabilities, not possibilities. This distinction is critical for organizations aiming to secure their systems, data, and operations effectively.

Probabilities vs. Possibilities in Cybersecurity

One of the biggest challenges in cybersecurity is balancing what could happen with what’s likely to happen. Let’s explore the difference:

• Probabilities quantify the likelihood of an event occurring.
  For instance, based on data from threat intelligence platforms, your organization might determine that phishing emails targeting employees are highly likely in the next 30 days. These probabilities can be measured, analyzed, and acted upon.
• Possibilities, on the other hand, focus on what might happen, even if we can’t assign a specific likelihood. For example, it’s possible that a sophisticated nation-state actor could target your organization tomorrow. But without evidence or historical data, it’s challenging to determine how likely this is to occur.

In cybersecurity risk analysis, the focus is on probabilities because they allow us to prioritize and mitigate risks. While possibilities remind us of the broader threat landscape, probabilities help us make informed decisions about where to invest our resources.

Risk = Likelihood × Impact: The Formula for Prioritization

Cybersecurity risk analysis often revolves around a simple yet powerful formula: Risk = Likelihood × Impact.

This formula helps organizations quantify and prioritize risks, turning abstract threats into actionable metrics.

1. Likelihood refers to the probability of an event occurring.
   • Example: What is the likelihood that an employee will fall for a phishing email? Historical data, employee training metrics, and industry benchmarks can help estimate this value.
2. Impact represents the potential damage or consequences if the event occurs.
   • Example: If a phishing attack successfully compromises credentials, what’s the financial, operational, or reputational damage to the organization? The impact varies depending on the sensitivity of the data or systems involved.

By multiplying these two factors, organizations can compare and rank risks. For example:

• A low-likelihood event with a catastrophic impact (e.g., a nation-state attack) might be treated with long-term strategic investments, like cyber insurance, incident response plans, multi-country backups, and threat intelligence.
• A high-likelihood event with moderate impact (e.g., phishing or ransomware) could demand immediate attention, such as enhanced employee training or improved email filtering systems.

This formula ensures that cybersecurity teams allocate resources where they matter most, addressing both the probability of incidents and their potential fallout.

Applying Probabilities in Cybersecurity Risk Management

How can this formula be applied to real-world cybersecurity scenarios? Here’s an example:

• Scenario: Ransomware Risk Analysis
  • Likelihood: Based on industry data, ransomware is one of the most common threats organizations face, particularly through phishing attacks or unpatched software.
  • Impact: The impact of a ransomware attack could include encrypted systems, lost productivity, regulatory fines, and reputational damage.
  • Risk Calculation: By combining a high likelihood with a potentially severe impact, ransomware emerges as a top-priority risk.
  • Action: Organizations can prioritize defenses such as regular backups, endpoint detection, employee awareness training, keeping historical security data accessible, and rapid incident response planning.

This structured approach ensures that cybersecurity efforts focus on the risks that pose the greatest threat to the organization.

The Importance of a Multi-Pronged Strategy for Cybersecurity Risk

Of course, no risk analysis in cybersecurity is perfect. Adversaries adapt quickly, and new threats emerge constantly. Many organizations lack access to their historical data, making it difficult to measure the likelihood of certain security events. The Devo Security Data Platform provides 400 days of hot data, ready for analysis at any moment. 

Other limitations in cybersecurity risk models, like biases in data interpretation and lack of additional monitoring for novel attack vectors, highlight the importance of using a multi-pronged strategy to mitigate risk as much as possible. This includes:

1. Continuous monitoring and updates: Threat landscapes change; your risk analysis should, too. 
2. Combining data with human expertise: Threat intelligence platforms and automated tools are invaluable, but experienced analysts are needed to add the necessary context.
3. A layered approach to security: Even with the best risk models, there’s no silver bullet. Defense-in-depth strategies ensure resilience by using multiple layers of security technology to protect assets. 

Get in touch with our experts to learn more about protecting your organization against cybersecurity risks with a security data platform.