ZitoVault announced on Tuesday that the company has been granted a new patent for predicting impending cybersecurity events. The patent covers ZitoVault’s new system and method for prediction using multi-channel behavioral analysis in a distributed computing environment.
As existing approaches address real-time detection of threats or anomalies based on a limited set of pre-established data points, ZitoVault’s latest patent defines a new approach to predicting cybersecurity threats.
The new patent has already been licensed by CyberSight, the creators of RansomStopper, a next-generation anti-ransomware solution. CyberSight has licensed this patent and others, including CryptoScale, from ZitoVault to enable the company to better fulfill its mission of predicting and proactively remediating cyberattacks before they materialize.
ZitoVaults’s CryptoScale patent protected software provides a secure end-to-end communications fabric, for devices to connect to servers, and cloud based applications. CryptoScale, also referred to as CryptoScaler, is comprised of CryptoScale Manager, CryptoScale Engines, and CryptoScale Clients.
These components are integrated into ZitoVault’s Z1 Agent and Ignite Security Platform. They provide users, connected devices, and the network with dynamic secure connections that are established and maintained between connected devices and the cloud; built-in intelligence that scales to accommodate the massively growing numbers of connected devices such as PCs, servers and IoT. CryptoScale also works with a range of transport services and VPN protocols, and optimizes throughput in environments with low Internet bandwidth.
Most current approaches primarily use source and log data from IT and security systems. ZitoVault’s behavioral analysis patent defines how to correlate a broader array of disparate channels of behavioral data, including third party data, social media, phone, text and email activity, context of searches within and outside of corporate domains, financial data, travel history and changes in HR status.
The system provides a software architecture for linking users to events and to other users by partitioning the data into working units that can be processed across a distributed network of virtual hosts without losing associative context.
The patent also defines how to automate many of the aspects that a human investigator would use to collect independent data points. This differs from anomaly-based detection systems in that it is based on threat storylines and actor profiles instead of on detecting the variance from predetermined data points. It offers a graph-based approach via semantic networks to compare event inputs from multiple log channels against threat profiles and game theory to predict future outcomes.
“ZitoVault’s patent for behavioral analysis is a huge milestone and an excellent addition to our growing portfolio of patented cybersecurity solutions,” said Tim McElwee, CEO and founder, ZitoVault. “We’ve seen growth in both the use of cloud-based infrastructure and in the number of endpoints accessible to hackers, which is why we’re continuing to innovate outside of our existing technology and patents to offer best-in-class threat prediction and security.”
“As the methods hackers use have become increasingly more complex and varied, it’s no longer enough to detect and block a ransomware attack in real-time. The ability to predict attacks before they happen has become crucial,” said Hyder Rabbani, COO, CyberSight. “We’re excited to add ZitoVault’s patented behavioral analysis method for predicting impending security threats to our next generation threat detection platform.”