Protect Operations with Smarter Risk Identification
Cyber Criminals are Using AI–So Should You
Cyber criminals are using AI and machine learning to find vulnerabilities to exploit and if you’re not doing the same to keep them out, you’re playing a losing game. With endless possibilities for ingress, you need to be able to detect the one real threat among billions of signals of normal activity. You need to quickly spot the outliers, find the vulnerabilities, and predict the risk to create an agile response plan.
Keep Your Operations Secure
Quickly uncover deep insight in your datasets by leveraging no-code data science techniques.
Validate your insight, and revisit it if necessary. Once you’ve confirmed its value, prepare your data story.
Review insight and potential options with stakeholders; select device and deploy the right solution.
Spot Vulnerabilities Before the Breach
90% of all security breaches originate from phishing scams making them–and your employees’ response to them–the greatest risk to your organization’s security. You won’t stop every malicious email but you can proactively identify who might click on them and stop the breach before it happens.
Get the Whole Picture for Network Defense
A single data source won’t give you enough information to plan or prioritize network defense. Cyber risk is a function of multiple factors, including the criticality of a vulnerability, network activity, network topology, and a threat’s ability and willingness to exploit vulnerabilities. Only by merging data sources and leveraging AI analysis can you get the insight necessary to mount an agile defense.
Explore with AI
Find threats in user communities
When analysts can do the early work to identify predictive signal, your entire cyber team is more effective.
Analysts can uncover which attributes drive phishing vulnerability using Smart Mapping, but they can go even deeper to discover an even more powerful predictor.
Virtualitics’ Network Extractor detects and visualizes communities within a dataset and, using Statistical Insights, analysts can determine if there are communities with a significantly higher likelihood of falling for a phishing email.
Explore with AI
Visualize & prioritize vulnerabilities
Using Virtualitics’ Intelligent Exploration capabilities, analysts can monitor a number of areas to quickly identify points of risk. From identifying categorical and thematic commonalities across network activity data, including vulnerability data and infrastructure criticality, and reviewing threat actor data, analysts can identify communities of similar vulnerabilities, anomalies, and attack vectors.
Virtualitics’ network graphs and no-code Explainable AI ensure that network defenders can quickly and effectively characterize the attack surface. The plain language insight provides insight into the relationships and enables the analyst to prioritize the risk mitigation and cyber defense strategies.
Define your Approach
Collaborate easily with data scientists
Virtualitics allows the analyst to save their work and pass the saved workflow to a data scientist to confirm the results, stepping through the entire analysis in seconds without time-consuming rework.
The data scientist confirms both the predictive value of the drivers and that community membership in one of the network communities was also a valuable feature for the model. The community definition can be exported as a new feature to leverage in the insider threat predictive model.
The model results are then visualized using Virtualitics to confirm accuracy.
Define the Approach
Power proactive decision-making
The deep exploration of threat, criticality, and vulnerability (TCV) data exposes the key relationships that Virtualitics transforms into a scoring algorithm configured to your needs to power cyber risk workflows.
The Cyber Risk workflows also integrate the TCV data with network activity data (PCAP) and network topology data to create a robust, holistic picture of the environment that powers proactive, defensive decision-making. Model results are validated with stakeholders to confirm results and ensure that the model workings are understood prior to deployment.
Solve with Confidence
Increase model accuracy and reduce risk
Including community membership as a feature in the model increased the model’s accuracy. This means that the teams taking action on the predictions were focusing their attention where it needed to be, and not spreading themselves too thin on false positives.
Data scientists can illustrate how the model works for the business so the teams can identify the most effective way to use it.
Options include powering proactive measures, such as automated enrollment in cyber training or a dashboard that identifies high-risk employees for personal outreach.
Solve with Confidence
Enhance situational awareness
Following stakeholder buy-in, the AI-powered workflow is deployed to provide enhanced network situational awareness to all cyber defenders through a portal that is available in even the most remote deployments. Defenders can run the workflow continuously to characterize, categorize, and prioritize threats, vulnerabilities, and anomalous network activity.
The insights are displayed in dynamic, interactive dashboards providing network overviews, threat actor assessment, and network activity anomaly analyses.
Protect Your Organization
Accurate predictions let you focus efforts and stop threats. With a clear view of the risk profiles of your employees and easy attribute identification and creation, you can create accurate risk prediction models and put them to work fortifying your most important line of defense–your people.
Protect Our Networks
Power analyses with AI for a streamlined view of threat, criticality, and vulnerability that allow cyber defenders to respond quickly and confidently to threats on our networks.