$GTCH the company is enhancing its qTerm device cybersecurity technology in order to ensure robust privacy and sensitive data protection for its potential users. Due to the rise of sensitive data breach cases in the past few years, GBT decided to add another layer of data protection, developing breakthrough techniques to prevent potential data theft. The enhancements will be performed within the device’s AI computer programs to increase data security for its machine learning and computing environments. GBT's qTerm, a human vitals intelligence device is targeted to measure human vitals with a touch of a finger, and includes AI technology for personal health monitoring. The device is accompanied by a smartphone app and a synchronized widget web application to keep a history and provide health related analytics.

GBT will be implementing Homomorphic Encryption (HE) techniques within its AI environment to enable encrypted data processing without decrypting it first. The qTerm algorithms send data back and forth over encrypted channels. The AI needs to perform computations and analysis and typically the system decrypts the information first, working on it, and re-encrypting it again before sharing it. This creates a potential security risk. HE technology enables robust data protection since the processing is always done with the encrypted data. HE techniques were known to have one major disadvantage, which is a very long processing time compared to decrypted data processing runtime. GBT developed new algorithms that operate with much higher performance enabling fast computations using HE methods. The company plans to implement HE technology within qTerm’s Machine Learning components, mobile and web interface computing environments.