Christopher C Valentino

US Patent:

20130321458, Dec 5, 2013

Filed:

May 30, 2013

Appl. No.:

13/905960

Inventors:

SCOTT B. MISERENDINO - BALTIMORE MD, US
DAVID MORSBERGER - DAVIDSONVILLE MD, US
WILLIAM E. FREEMAN - SYKESVILLE MD, US
CHRISTOPHER CHARLES VALENTINO - STEVENSVILLE MD, US

Assignee:

NORTHROP GRUMMAN SYSTEMS CORPORATION - FALLS CHURCH VA

International Classification:

G06T 11/60

US Classification:

345629

Abstract:

In one embodiment, a method includes generating a treemap for a network space having an array of network addresses. The treemap includes a hierarchical network map with a plurality of leaf nodes, and each leaf node in the treemap characterizes a proper subset of the array of network addresses. The method includes overlaying an organizational schema for an organization on to the hierarchical network map to identify a plurality of nodes of the network space employed by the organization. The method includes generating a visualization for a graphical user interface (GUI) of the hierarchical network map with the organizational schema overlaid thereon that includes a visual indicia of network events that occur within the network space.

US Patent:

20160149943, May 26, 2016

Filed:

Nov 16, 2015

Appl. No.:

14/941999

Inventors:

- Falls Church VA, US
Michael P. Boyle - Ellicott City MD, US
Christopher C. Valentino - Stevensville MD, US

International Classification:

H04L 29/06
G06N 99/00
G06N 7/00

Abstract:

Described herein are embodiments of a system and method for network data characterization and/or classification that overcome the defects of the prior art. These and other advantages are achieved by a method for network data characterization. The method includes receiving network events, wherein at least some of the events include content, converting the received content into data messages, in which at least some of the data messages include the content and metadata describing an event and the content, routing the data messages to a plurality of analyzers based on specified message criteria to which each analyzer subscribes, each of one or more analyzers that received the routed data messages analyzing the content within the data messages in order to characterize the content, in which the one or more analyzers include at least one machine-learning analyzer that classifies the content with a confidence percentage that indicates the probability that the content is malign or the confidence that a prediction that the content is malign is correct, outputting the characterization results of the one or more analyzers, and comparing the output characterization results against a plurality of criteria to determine subsequent action to take based on the characterization results.