Security Norm Contagion: Threshold Adoption Model (2D) |…

What Security Norm Contagion Is

Security norm contagion refers to the process by which a new security practice or standard spreads through an organization. This model is based on the Granovetter-Watts threshold-contagion theory, where individuals adopt a behavior if a certain fraction of their neighbors have already adopted it.

The 2D network graph in this simulation represents members of an organization as nodes and connections between them as edges. Each node has a risk-appetite threshold that determines when they will adopt the security practice.

Why It Happens

Adoption occurs based on the principle that individuals are influenced by their social network. In this model, if enough of a person’s neighbors have adopted a new security practice, they will be motivated to do so as well.

The threshold-contagion theory captures how norms can spread through a population, and it is particularly relevant in cybersecurity where secure practices need to be widely adopted to protect against threats.

live demo · related simulation● LIVE

Key Factors Influencing Adoption

Several factors influence the rate and extent of security norm contagion. These include the initial percentage of adopters, the mean risk-appetite threshold, threshold diversity among individuals, and the number of neighbors each member has.

The model also considers weak-tie rewiring, which simulates how new connections can bring in different perspectives and potentially lower thresholds for adopting new practices.

Real-World Applications

Understanding these dynamics is crucial for organizations to effectively implement security measures. For instance, a company might use this model to predict how quickly employees will adopt multi-factor authentication (MFA) or secure coding practices.

By adjusting parameters such as the initial adoption rate and risk-appetite thresholds, organizations can tailor their strategies to maximize the spread of effective security norms.

Frequently asked questions

How does threshold diversity affect norm contagion?

Threshold diversity means that individuals have different risk appetites. This can slow down or speed up the adoption process, as some people may require a higher number of adopters before they decide to follow suit.

What role do weak-tie rewirings play in security norm contagion?

Weak-tie rewirings represent new connections that can introduce individuals with different risk appetites and thresholds, potentially lowering the overall threshold for adopting a security practice across the network.

How does initial adopter percentage impact the model's outcome?

A higher initial adopter percentage generally leads to faster adoption rates as more people are exposed to the new norm early on. However, too high an initial rate can saturate the network and slow down further spread.

Why is it important to consider cascade speed in this model?

Cascade speed determines how quickly the security practice spreads through the network. Faster cascades can lead to quicker implementation of security measures, which is critical for timely response to emerging threats.

Try it live

Everything above runs in your browser — open Security Norm Contagion: Threshold Adoption Model (2D) and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Security Norm Contagion: Threshold Adoption Model (2D) simulation