Interconnected network of businesses with shield and security gaps.

Cybersecurity's Crystal Ball: Predicting Risks with Peer Data

"Unlock the secrets to stronger cybersecurity by learning how industry benchmarks and collaborative data sharing are revolutionizing risk prediction."


For years, organizations have grappled with two fundamental cybersecurity questions: What's our true risk exposure, and how do our defenses stack up against others? Historically, the data needed to answer these questions—security posture details, incident reports, and financial losses—was too sensitive to share. The advent of privacy-enhancing technologies (PETs) is changing the game, enabling secure computation of aggregate cyber risk metrics without revealing sensitive, individual data.

The ability to benchmark cyber posture against peers and estimate risk within specific economic sectors is now within reach. Recent research introduces a framework that uses industry-wide data, securely computed, to give organizations a clearer picture of their cyber risk landscape. The core innovation is the "Defense Gap Index," a measure of the weighted security gap between an organization and its peers, forecasting security risk based on historical industry data.

This approach has been applied in a specific sector, using data from 25 large firms in partnership with an industry Information Sharing and Analysis Organization (ISAO). The resulting industry risk model provides participants with tools to estimate their risk exposure and confidentially compare their security posture against their peers, promising a more secure and resilient future.

Decoding the Defense Gap Index: A New Metric for Cyber Risk

Interconnected network of businesses with shield and security gaps.

The "Defense Gap Index" is a critical component of this new framework. It quantifies the disparity between an organization's security measures and the average security posture of its peers. By securely aggregating data on security controls, incident frequencies, and financial losses, the index provides a benchmark for assessing relative risk.

Here’s how the Defense Gap Index is built:

  • Secure Data Aggregation: Privacy-enhancing technologies (PETs) securely compile data on security posture, control failures, incident rates, and losses from participating organizations.
  • Weighted Security Posture Deviations: The index calculates how an organization's security controls deviate from the peer group average, weighting these deviations based on the financial losses attributed to specific control failures. Controls that, when failed, led to larger losses have a greater impact on the index.
  • Risk Forecasting: The index uses historical industry data to forecast an organization's security risk based on its Defense Gap Index score. This allows firms to empirically predict future risk, supporting investment decisions and helping regulators set reasonable security expectations.
The goal is to understand how shifts in security posture influence cyber risk predictions, making the Defense Gap Index a central element alongside traditional probability and loss calculations. P (probability of an incident) and L (average financial loss) are derived from secure computation as averages, while the gap index captures the relationship between deviations in security control maturities and changes in risk outcomes.

The Future of Cyber Risk Modeling: Collaborative, Data-Driven, and Secure

The research highlights the potential for secure, collaborative approaches to revolutionize cyber risk management. By leveraging privacy-enhancing technologies and industry-wide data, organizations can gain unprecedented insights into their risk profiles and benchmark their security posture against their peers. As governments and industry groups promote data sharing and standardization, the future of cybersecurity will be more data-driven, proactive, and resilient.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2402.04166,

Title: Mind The Gap: Securely Modeling Cyber Risk Based On Security Deviations From A Peer Group

Subject: cs.cr cs.cy econ.gn q-fin.ec stat.ap

Authors: Taylor Reynolds, Sarah Scheffler, Daniel J. Weitzner, Angelina Wu

Published: 06-02-2024

Everything You Need To Know

1

What is the Defense Gap Index and how does it work in the context of cybersecurity?

The Defense Gap Index is a metric designed to quantify the difference between an organization's security measures and the average security posture of its peers. It works by securely aggregating data on security controls, incident frequencies, and financial losses from participating organizations using Privacy-Enhancing Technologies (PETs). The index then calculates deviations in an organization's security controls from the peer group average, weighting these deviations based on the financial losses associated with specific control failures. Ultimately, it forecasts an organization's security risk based on its Defense Gap Index score, using historical industry data.

2

How do Privacy-Enhancing Technologies (PETs) enable secure data sharing in cybersecurity?

Privacy-Enhancing Technologies (PETs) play a crucial role by allowing the secure computation of aggregate cyber risk metrics without revealing sensitive, individual data. They enable organizations to share security posture details, incident reports, and financial losses confidentially. This is achieved through secure data aggregation, where data from different organizations is combined and processed in a way that protects the privacy of each individual organization's data, allowing for industry-wide analysis and benchmarking.

3

What are the key benefits of benchmarking a company's cybersecurity posture against its peers?

Benchmarking a company's cybersecurity posture against its peers offers several key benefits. Firstly, it provides a clearer picture of an organization's cyber risk landscape by comparing its security measures to industry standards. Secondly, it enables the estimation of risk exposure within specific economic sectors. Thirdly, it allows organizations to proactively strengthen their security posture by identifying areas where they lag behind their peers. Finally, it facilitates more informed investment decisions and supports regulators in setting reasonable security expectations.

4

How is the Defense Gap Index used to forecast an organization's security risk?

The Defense Gap Index is used to forecast an organization's security risk by leveraging historical industry data. The index calculates an organization's score based on deviations in their security controls compared to the peer group average. This score is then used to predict future risk. The index considers weighted security posture deviations, where the impact of control failures on the index is weighted based on the financial losses they have historically caused. This approach allows organizations to empirically predict future risks, supporting investment decisions and security expectations.

5

In the context of cyber risk modeling, what role do P (probability of an incident) and L (average financial loss) play alongside the Defense Gap Index?

In cyber risk modeling, P (probability of an incident) and L (average financial loss) are crucial components. They are derived from secure computation as averages, providing a foundational understanding of incident likelihood and financial impact. The Defense Gap Index complements these by capturing the relationship between deviations in security control maturities and changes in risk outcomes. While P and L provide insights into the basic risk factors, the index adds the dimension of how an organization's relative security posture affects its risk profile. The index highlights the effect of security control gaps, making it a central element alongside traditional probability and loss calculations.

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