IntelliGenesis developed a multiplayer game to accelerate learning and mastery of strategic and tactical urban combat skills for active-duty warfighters, internally called Tactical Analytical Cognitive Training for Interactive Combat Simulation (TACTICS)(SBIR Phase I). TACTICS is a first-person shooter (FPS), developed using the Unity game engine, which places the player in realistic combat situations which test their situational awareness, communication skills, and tactical decision-making. TACTICS provides the ability to train anywhere, even from home. By not requiring advanced hardware or software, TACTICS makes urban combat training readily available. This enables much more training repetition, resulting in increased proficiency in the trained skills over a shorter time period.

IntelliGenesis LLC developed WATCHTOWER (STTR Phase 1), a tool using AI to make suicide risk predictions based on personnel records instead of medical records. These records are readily available for all service members and regularly updated, whereas individuals’ medical records may only exist for issues brought up by the subjects, themselves. Generating accurate predictions based on personnel records would have a dramatic impact on the ability to help potential victims before it is too late. The ability to utilize new data sources in addition to medical records will also drastically expand the breadth of potential indicators that can be detected and addressed.

Technologies

• Suicide Prevention AI: Uses multiple AI models to predict an employee’s level of risk for suicide based on personnel data (demographics, age, salary, leave usage, performance reviews, etc.)
• Dashboard Visualization: Customizable visualization of highest risk employees and employees with largest changes over the last week/month
• Natural Language Processing (NLP): Analyzes plain unstructured text performance reviews for sentiment and incorporates that into the risk assessment.

 Differentiators

• Dr. Craig Bryan, Ohio State University: Dr. Bryan is a worldwide leader on veteran suicide and a veteran himself. He has published over 100 works on the topic. He consulted with us extensively and contributed to algorithm and interface design. Upon completion of the project, he said he was very willing to work with us in the future on this or other related projects.
• Personnel data: Countless studies have been done using medical data as input to the AI models. But medical data tends to be incomplete and is much harder to access legally. Personnel data (especially in the military/DOD use case) is much more abundant, complete, and accessible making it a potentially stronger data set.
• Multiple models combined: Rather than just one AI model, our system is designed to be flexible and work with multiple models as plug and play modules that can be changed based on the data available to any particular customer.

Customers

• DOD
• Reserves
• Law Enforcement

Technologies

• Network Traffic Analysis: Captures and analyzes all traffic on the user’s network. o Unsupervised Anomaly Detection: CYBERSPAN learns what’s normal for your network without being told. Then it will alert users to anomalous traffic that doesn’t match its learned norms.
• Malicious Attack Identification: Traffic and anomalies matching known malicious patterns are mapped to MITRE ATT&CK Framework Tactics, Techniques, and Procedures (TTPs)
• Integration with Other Intrusion Detection Systems: Generates events and adjusts priority based on enrichment data from other IDS’s such as Suricata.

Differentiators

• Agent-less Setup: CYBERSPAN does not require agents installed on every system. It operates at the network switch. This reduces maintenance and system administration burden while also providing results for networks where administrators do not control all the devices (such as open Wi-Fi at airports or hospitals).
• Does not decrypt traffic: Users’ privacy is preserved as CYBERSPAN does not decrypt or view the content of network traffic. It operates only on metadata such as to/from IPs, ports, and packet sizes.
• Detects anomalous traffic on non-traditional network devices: Devices such as Smart TVs, Alexas, and Google Homes generate network traffic, but can’t be monitored by traditional agent-based network security systems. CYBERSPAN is able to collect and analyze this traffic and highlight anomalies.

Customers

• Small to Medium size businesses without cybersecurity expertise on staff
• DOD/DC3
  
• Locations which provide free and open Wi-Fi
  • Airports
  • Hospitals
  • Hotels