Machine Learning

Ventech Solutions Granted Patents for Valholla Methods

Ventech Solutions has been granted two patents for the method and systems offered in its Valholla solution.

Valholla, a Ventech Solutions product, is a development, security and operations (DevSecOps) and governance tool for enterprise visibility, control and intelligence. The solution leverages APIs to integrate with existing continuous integration and continuous delivery (CI/CD) pipelines, so there’s no need to replace existing tools. With Valholla, Ventech Solutions clients can centrally control and manage information technology (IT) deployment automation, security and functional testing, as well as cloud cost optimization from a single interface.

“As a team, we are thrilled to announce the patents awarded to the methods that make up the Valholla solution,” said Steve Veneruso, chief technology officer at Ventech Solutions. “Valholla is a state-of-the-art tool that allows our clients to save time and resources, reduce costs, enhance security and eliminate manual steps and processes across the enterprise.”

Valholla ensures adherence to standards, streamlines deployment processes, consolidates data from numerous tools and intuitively presents the data in a user-friendly interface. This results in greater overall efficiencies and significantly reduces manually induced errors.

U.S. Patent Nos. 11438339 and 11436335 were granted on September 6, 2022, by the United States Patent and Trademark Office (USPTO).

Method and system for neural network based data analytics in software security vulnerability testing
Patent 11438339

A method and system for implementing AI based neural networks for data analytics in dynamic testing of security vulnerability of cloud-based enterprise software applications. The method comprises directing, to a software program under execution, a series of attack vectors; diagnosing an at least a first set of results associated with the software program under execution as comprising one of a security vulnerability and not a security vulnerability, the at least a first set of results produced based at least in part on the attack vectors; and training a machine learning neural network classifier in accordance with a supervised classification that identifies false positive vulnerability defects of the at least a first set of results to produce a trained classifier, the neural network classifier including an input and an output layers connected via at least one intermediate layer that is configured in accordance with an initial matrix of weights.

Method and system for synchronously generated security waiver interface
Patent 11436335

A method and system of rendering security events in execution of a software application in a communication network. The method comprises receiving, at a memory of the server computing device, a waiver parameter specification identifying at least one waiver parameter in association with at least one recipient client device of the plurality of client computing devices, the at least one waiver parameter based at least in part on an expected security event in the software application execution; during concurrent execution, in a processor of the server computing device, of object code of the software application, generating at least one waiver task automaton that monitors for the at least one waiver parameter; and generating, based on the monitoring, at a client interface of the at least one recipient communication device, a waiver notification interface in accordance with concurrent execution.

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