MicroAI Security, says the company, provides a revolutionary approach to mitigate these attacks with an embedded AI algorithm that can detect, alert, and visualize cyber security intrusions in real time, and runs directly on edge and endpoint connected devices. The algorithm teaches a connected device to self-monitor and provide alerts when anomalous behavior is identified.
“Zero Day attacks are operationally crippling, and cost millions of dollars for an organization to fully recover from,” says MicroAI CEO Yasser Khan. “Unfortunately, the spread of these incidents is only increasing, and MicroAI Security provides a truly effective approach to detect these attacks.”
MicroAI Security uses a proprietary AI algorithm that is small enough in both code size and compute requirements to be embedded on almost any microcontroller (MCU) or microprocessor (MPU) of a connected device – such as motors, sensors, pumps, medical devices, inspection equipment and automotive entertainment systems. This device-centric approach, says the company, enables asset protection that is more immediate, more automated, and more reliable than solutions that rely on cloud connectivity.
MicroAI Security builds personalized AI intrusion detection models that are unique for each device and deployment. MicroAI Security trains and develops a model of what is normal operation for the device, and subsequently switches into inferencing mode for real-time detection of anomalies or cyber intrusions.
Both training and inferencing are completed without human intervention, and once activated MicroAI can detect and identify even the most covert cyber security intrusions, including ‘Zero Day Attacks.’ This rapid detection is supported by intelligent workflows that trigger automated alerts and mitigation actions to help minimize exposure and damage.
Multiple types of attack are mitigated by MicroAI Security, including Distributed Denial of Service (DDOS), ransomware, phishing and cloud breaches.