Unisys Corporation

Robert Buckwalter

Robert A Johnson

Jane Campbell Mazzagatti

Eugene J Gretter

Sarah K Inforzato

Michael C Leap

Michael J Saunders

Diane E Schaefer

Jared Poetter

George Karian

Steven L Rajcan

A network model includes nodes, node property sets, authorization groups and authorization servers. The node property sets define how the nodes operate and authenticate. The nodes are member of the node property sets. The authorization groups are associated with the node property set. And, authorization servers are member of the authorization groups. In addition, a network model in a secure network environment has at least one community of interest. The network model includes at least one node being a member of a node property set that defines how the node operates and authenticates.

Network model utilizing property sets

A method of creating secure endpoints on a network includes registering by a node using a random selection algorithm to choose which server to register to; receiving by the node a property set ID of a property set that the node is a member of; and authorizing by the node using the property set ID to look up its authorization details in the property set. A method of creating secure endpoints on a secure network having at least one community of interest, includes registering by a node using a random selection algorithm to choose which server to register to; receiving by the node a property set ID of a property set that the node is a member of; and authorizing by the node through an authorization server using the property set ID to look up its authorization details in the property set; wherein the node and the authorization server are a member of the at least one community of interest.

Method of creating secure endpoints on a network

Aggregation of data in an interlocking trees datastore, especially when the interlocking datastore is a KStore is described. It details consolidating data into a summary or aggregation so that some particular desired analytic type of operation may easily be performed on the data. It uses a set of data constraints across the entire data set. This redefines the data set, which may be for example, individual receipts granular by week or month. When data is learned into a KStore, aggregation parameters may be collected and these parameters may be used to constrain the dataset recorded in K, and direct performance of an analytic on a particular a field value(s). Additional features and details are provided within.

Data aggregation user interface and analytic adapted for a KStore

A method for providing a display of data from an interlocking trees datastore in a graphical display system having a graphic display device is disclosed, the method including the steps of collecting display requirements for defining a value and at least one display characteristic to be displayed on the graphic display device and querying an interlocking trees datastore in accordance with the display requirements to determine the value to be displayed. At least one graphical display parameter is determined in accordance with the display requirements and the value to be displayed and the graphical display parameter are transmitted to the graphical display device for display of the value by the graphic display device.

Method and apparatus for interface for graphic display of data from a Kstore

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West Chester, PA, United States of America

Robert Buckwalter