GBT Technologies is working to secure its Apollo, an RF-based motion detection system. The Apollo system uses AI technology to control radio waves transmissions and analyze the reflected information to construct 3D cinematic media in real-time. Apollo transmits and receives data using radio waves, operating within low frequencies RF Spectrum. The security system is targeted to prevent intruders from listening to Apollo’s RF traffic, stealing data, or blocking its operation. Another topic of concern is the ability to replace data with bogus information by jamming it.
The system will be governed by an AI mechanism to quantify RF devices that interact with Apollo, assessing its RF waves characteristics, monitoring network traffic, and ultimately, detecting unauthorized RF devices. These devices will be categorized as intruding nodes and will be immediately isolated upon detection. We design a cognitive security mechanism to constantly learn about Apollo’s communication characteristics, providing an adaptive RF communication feature to ensure robust, secured operations. In case of malicious activity detection, the AI system will immediately modify the RF propagation characteristics to the new conditions, activating new encryption keys, and ultimately changing the entire radio system attributes. The system’s main advantage is the fact that it will take the necessary precautions before attacks occur, which we call a preventative approach. The main aim will be to protect against data theft and damage due to the wireless signal’s vulnerabilities. Apollo system could be implemented within major domains like health monitoring, security, and computer vision applications. The company already filed a provisional patent and will be filing a non-provisional patent during the next few months.
"Apollo system is based on wireless technology and broadcasts RF signals in the open. Radio communication by its nature is exposed to intruders’ attacks and suffers from serious security vulnerabilities. To protect the wireless signals from malicious attacks, data theft, and jamming, we decided to invest in the development of an application-specific cybersecurity measure for the Apollo system. We are currently designing a comprehensive cyber solution to protect Apollo’s wireless system, creating adaptive security methods from various perspectives. Our AI system is targeting to manage the RF communication adaptively modifying radio propagation characteristics according to security analysis. The intelligent system will quantify the network’s radio devices, identify unauthorized members, and supervise encryption/decryption operations. In case of unknown RF devices interference, the system will isolate and unauthorized nodes, change RF characteristics, encryption/decryption keys, and additional features to provide immediate breach prevention. A deep learning mechanism will be constantly learning about the system’s RF communication properties while monitoring any suspicious activities.
Apollo system enables an RF-based, motion computer vision, and can be implemented within essential technologies among them are autonomous vehicles, medical apparatus, and security. Such a system needs to be equipped with top-notch cyber protection against data theft, interference, and jamming. We truly believe that this type of technology can offer an innovative wireless solution in many domains as the system will be capable of seeing underground, water, and through walls. Its deep learning capability enables rapid analysis of the RF data, identifying living entities and objects, constructing a computerized cinematic media in real-time. The Apollo system can be a significant technological advancement enabling a healthier lifestyle, smarter cities, and intelligent transportation. As wireless systems are becoming an essential component in our modern life, new cybersecurity vulnerabilities are introduced and we have to ensure comprehensive protection, reliability, and secured operation,” said Danny Rittman, the Company’s CTO.
Click here to learn more about the Apollo System.
