Company Filing History:
Years Active: 2022-2025
Title: Innovations of Joshua Neil
Introduction
Joshua Neil is an accomplished inventor based in Redmond, WA. He has made significant contributions to the field of technology, particularly in the area of network security and anomaly detection. With a total of four patents to his name, Neil's work has garnered attention for its innovative approaches to identifying malicious behaviors within enterprises.
Latest Patents
One of Joshua Neil's latest patents is a "Malicious enterprise behavior detection tool." This invention provides systems, methods, and non-transitory computer storage media for identifying malicious enterprise behaviors within a large organization. The tool identifies sub-graphs of behaviors based on probabilistic and deterministic methods. It starts with the node or edge having the highest risk score and iteratively crawls a list of neighbors to identify subsets of behaviors that indicate potentially malicious activity. Another notable patent is focused on "Detecting anomalous network activity." This invention discloses systems and methods for temporal link prediction using generalized random dot product graphs. It utilizes time series of adjacency matrices to predict link probabilities and identify anomalous behavior within networks.
Career Highlights
Joshua Neil is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate and develop new technologies. His work at Microsoft has allowed him to collaborate with some of the brightest minds in the industry, contributing to advancements in network security.
Collaborations
Some of his notable coworkers include Anna Swanson Bertiger and Evan John Argyle. Their collaborative efforts have further enhanced the innovative environment at Microsoft.
Conclusion
Joshua Neil's contributions to technology, particularly in network security, demonstrate his commitment to innovation. His patents reflect a deep understanding of complex systems and a dedication to improving enterprise security measures.