What are Cybersecurity metrics? Finding the right Cybersecurity metrics can be daunting, especially when you're busy working on your day-to-day tasks. This is why we've curated a list of examples for your inspiration.
Copy these examples into your preferred tool, or adopt Tability to ensure you remain accountable.
Find Cybersecurity metrics with AI While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.
Examples of Cybersecurity metrics and KPIs 1. Accuracy Proportion of overall correct predictions made by the system
What good looks like for this metric: Typical values range from 85% to 92%
Ideas to improve this metric Regularly update training data with new examples of cyberbullying Employ data augmentation techniques to enhance model robustness Refine algorithms to better differentiate between nuanced bullying and benign interactions Invest in powerful computational resources for training Enhance feature selection to include more relevant variables 2. Precision Proportion of identified bullying incidents that were truly bullying (minimises false positives)
What good looks like for this metric: Typical values range from 80% to 89%
Ideas to improve this metric Implement stricter thresholds for classifying messages as bullying Use ensemble methods to improve precision Incorporate more contextual clues from text data Regularly review and analyse false positive cases Enhance algorithm's sensitivity to language nuances 3. Recall Proportion of actual bullying cases that the system successfully detected (minimises false negatives)
What good looks like for this metric: Typical values range from 86% to 93%
Ideas to improve this metric Increase dataset size with more diverse examples of bullying Utilise semi-supervised learning to leverage unlabelled data Adapt models to recognise emerging slang or code words used in bullying Incorporate real-time updates to improve detection speed Conduct regular system audits to identify and correct blind spots 4. F1-Score Harmonic mean of precision and recall, providing a balanced measure of both
What good looks like for this metric: Typical values range from 83% to 91%
Ideas to improve this metric Focus on improving either precision or recall without sacrificing the other Perform cross-validation to identify optimal model parameters Use advanced NLP techniques for better text understanding Regular user feedback to identify missed detection patterns Continuous deployment for quick implementation of improvements 5. AUC-ROC Measures the ability to distinguish between classes across various thresholds
What good looks like for this metric: Typical values range from 0.89 to 0.95
Ideas to improve this metric Optimise feature selection to improve class separation Apply deep learning methods for better pattern recognition Leverage domain expert input to refine classification criteria Regularly update models to adjust to new trends in digital communication Evaluate model performance using different cut-off points for better discrimination
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1. Uptime The percentage of time that the infrastructure is operational and available
What good looks like for this metric: 99.9% or above
Ideas to improve this metric Implement proactive monitoring tools Establish robust disaster recovery protocols Regularly update software and firmware Schedule regular maintenance windows Utilize redundant systems for critical components 2. Mean Time to Resolution (MTTR) The average time taken to resolve a failure or issue
What good looks like for this metric: 1 to 4 hours
Ideas to improve this metric Streamline incident response processes Provide ongoing training for IT staff Utilize automated diagnostics tools Maintain comprehensive documentation Conduct regular post-incident reviews 3. Cost Efficiency The measure of operational costs in relation to infrastructure output
What good looks like for this metric: Cost reduction of 10-20% annually
Ideas to improve this metric Optimize resource allocation Negotiate better vendor contracts Implement energy-efficient technologies Regularly review spending against budget Leverage cloud services where applicable 4. Capacity Utilisation The percentage of total infrastructure capacity being used efficiently
What good looks like for this metric: 75-85%
Ideas to improve this metric Monitor usage trends closely Adjust resources based on demand Implement virtualization strategies Plan for future capacity needs Eliminate underutilized resources 5. Security Incident Frequency The number of security incidents reported over a specific period
What good looks like for this metric: Less than 2 incidents per month
Ideas to improve this metric Enhance security training for employees Regularly update security protocols Utilize advanced threat detection systems Conduct frequent security audits Implement robust access control measures
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Tracking your Cybersecurity metrics Having a plan is one thing, sticking to it is another.
Setting good strategies is only the first challenge. The hard part is to avoid distractions and make sure that you commit to the plan. A simple weekly ritual will greatly increase the chances of success.
A tool like Tability can also help you by combining AI and goal-setting to keep you on track.
More metrics recently published We have more examples to help you below.
Planning resources OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:
Tability's check-ins will save you hours and increase transparency
The best metrics for Infrastructure Productivity Management