Generative AI for Real-Time Threat Detection and Response
MixMode's AI was created using a foundational model for dynamic threat detection. This model can predict known and novel attacks, including the ability to surface zero-day attacks in real-time with 99%+ alert precision and reduction.
The dynamical foundational model builds upon the methodologies introduced in first-wave (rules-based) and second-wave (machine learning) solutions. It is grounded in the principles of dynamical systems theory, which investigates how systems evolve and how their behavior is influenced by internal and external factors.
When applied effectively, this model provides a comprehensive and adaptable framework for managing and securing enterprise environments, including early detection of threats and timely response to security incidents.
AI That Continuously Evolves and Scales
MixMode's self-learning, context-aware AI tailors itself to an organization's unique infrastructure, creating a continuously evolving baseline without the need for rules, training, or human input, all within a matter of days.
MixMode's AI analyzes patterns of interaction across multiple time scales and compares them with previous patterns. If there is a deviation, the system alerts the user to a potential security risk. By minimizing false positives, the system reduces the number of unnecessary alerts.
MixMode's AI dynamic learning algorithms have an unsupervised nature that enables independent extraction of patterns and trends from the underlying time-stamped data. This allows for the detection of Zero-Day threats and AI-generated attacks.
This distinction is critical because it adds a sophisticated level of cybersecurity that is capable of defending against the modern threatscape, while also increasing the efficiency and productivity of the SOC.
Take a Deep Dive Into the First Patented Third-Wave Generative Artificial Intelligence for Cybersecurity
Backed By Over 20 years of Research and Data
Dr. Igor Mezic - CTO and Chief Scientist
Led by Chief Scientist Dr. Igor Mezic, MixMode's AI was developed due to over 20 years of underlying research, including using proven methodologies applied to projects executed at DARPA, the DoD, and others. The MixMode AI Research team has used its expertise to solve some of the biggest problems inside and outside of cybersecurity, including predicting where an oil spill would spread.
Why Mixmode's Patented Cyber AI is Unique
Most security solutions currently in the market leverage "first or second-wave AI" technology that uses a combination of rules & thresholds or static “training” data to make decisions about your data and can take between 6-24 months of learning to be effective.
MixMode's Generative AI starts learning about your network immediately, unsupervised and without human input, customizing to the specific dynamics of individual networks rather than relying on more generic ML models typically found among competitors.
The result is a truly autonomous defense system that detects threats others miss in real-time and delivers tangible business outcomes in days.
Operates completely independently. Does not require any human operators to deploy, run, or tune.
Independently able to identify context in patterns and trends, independent of historical data or contextual models.
Identifies pre-attack behaviors and anomalies indicative of a potential attack with a continously evolving baseline.
Begins learning immediately without a pre-existing or established baseline. Learns, adapts, and evolves to understand patterns of both normal and anomalous behavior.
Addresses security challenges based solely on historical data clustering and human inputs (labeling, training and rules).
Based only on the clustered, labeled and trained data it is fed by human operators. Incapable of AI insights outside of clustered data context.
Has no predictive capabilities because it is dependent on aggregate, normalized, historical information and rules.
Static baseline cannot evolve without human training and intervention. Takes on average 12-24 months of human training and tuning before it can provide value.