Zscaler, Inc.

Attivio, Inc.

Other

Edgewise Networks, Inc.

Videoserver, Inc.

John E O'Neil

Peter Smith

Thomas Evan Keiser, Jr

Scott Laplante

Peter Nahas

Michael J Melson

Harry Sverdlove

Andriy Kochura

Jonathan Hood Young

William Kimble Johnson, Iii

Suji Suresh

Martin Serrano

Xing Li

Gregory L George

Raymond Brian Liu

Daniel Einspanjer

Sean Lutner

Herman Parfenov

Anthony Gelsomini

Joseph Riopel

Thomas C Hickman

Peter Kahn

Aparna Ayikkara

Nikitha Koppu

Omar Baba

Udayan Das

George W Kajos

A computer system automatically tests a network communication model by predicting whether particular traffic (whether actual or simulated) should be allowed on the network, and then estimating the accuracy of the network communication model based on the prediction. Such an estimate may be generated even before the model has been applied to traffic on the network. For example, steps can include observing positive data associated with a network; generating a network communication model based on the positive data; generating negative data based on the network communication model; calculating a precision of the network communication model based on the network communication model and the negative data; and calculating an accuracy of the network communication model based on one or more of the precision of the network communication model, or the network communication model and the positive data.

Automated estimation of network security policy risk

Embodiments of the present invention generate network communication policies by applying machine learning to existing network communications, and without using information that labels such communications as healthy or unhealthy. The resulting policies may be used to validate communication between applications (or services) over a network.

Statistical network application security policy generation

A system validates the establishment and/or continuation of a connection between two applications over a network. The system uses network application security rules to allow or disallow connections between the two applications. Those rules include definitions of the source and destination applications to which the rules apply. The system automatically updates the application definitions over time to encompass new versions of the applications covered by the security rules, but without encompassing other applications. The system is then capable of applying the updated rules both to the original applications and to the updated versions of those applications. This process enables the security rules to maintain security over time in a way that is consistent with the original intent of the rules even as applications on the network evolve.

Automatic network application security policy expansion

A technique for microsegmentation includes receiving information related to hosts and applications operating in a network where the information was obtained based on a survey of the network; identifying a plurality of microsegments utilizing the information, each microsegment includes a set of hosts similar to one another; for each of the plurality of microsegments, identifying security policies that control access to hosts in each microsegment; and providing the plurality of microsegments and corresponding security policies for approval thereof.

Semi-automatic communication network microsegmentation

A computer system automatically learns which application behavior constitutes 'multi-use' behavior by observing the behavior of applications on a network. The system uses this learned knowledge to automatically identify multi-use behavior in new applications that appear on the network. When the system enforces security policies against applications on the network, it identifies whether particular behavior of such applications violates any of the security policies. In this way, the system adapts automatically to new behavior of applications on the network over time in order to increase network security.

Automated software capabilities classification model that identifies multi-use behavior of new applications on a network

Network application security policy generation

A computer system automatically tests a network communication model by predicting whether particular traffic (whether actual or simulated) should be allowed on the network, and then estimating the accuracy of the network communication model based on the prediction. Such an estimate may be generated even before the model has been applied to traffic on the network. For example, the model may be generated based on a first set of network traffic. The accuracy of the model may then be estimated based on a second set of network traffic. This allows the accuracy of the model to be estimated without first waiting to apply the model to actual network traffic, thereby reducing the risk associated with applying the model before its accuracy is known.

Systems and methods include obtaining network communication information about hosts in a network and applications executed on the hosts; automatically generating one or more microsegments in the network based on analysis of the obtained network communication information, wherein each microsegment of the one or more microsegments is a grouping of resources including the hosts and the applications executed on the hosts that have rules for network communication; automatically generating a meaningful name for the one or more microsegments based on a plurality of techniques applied to information associated with the hosts; and displaying the automatically generated one or more microsegments and the corresponding automatically generated meaningful name.

Automatic segment naming in microsegmentation

A computer system automatically generates a proposal for network application security policies to be applied on a telecommunications network. The system provides output representing the proposed network application security policies to a user. The user provides input either approving or disapproving of the network application security policies. If the user approves, then the system applies the of the proposed microsegmentation. This process may be repeated for a plurality of hosts and subsets thereof within the same network, and may be repeated over time to modify one or more existing network application security policies. The network application security policies govern inbound and outbound connections to the hosts in the network.

Identifying and providing network application security policies governing connections to and from hosts in a network

Computer-implemented systems and methods automatically identify computers that act as load balancers on a digital communications network, using data collected from one or more computers on that network. Once a load balancer has been identified, the communications between two hosts may be connected across the identified load balancer, thereby making it possible to better analyze the behavior of hosts and applications on that network.

Automated load balancer discovery

A computer system processes a plurality of unrelated database tables to create a join graph where each node in the join graph represents a table. The nodes in the join graph are connected by weighted, directed edges, where each directed edge represents a join from a first column in a first table to a second column in a second table and where the weight of the directed edge represents a predicted level of success in performing the join. The edge weights can be based on a likelihood of finding a value from the first column in the second column. A user selects a subset of the tables, and the system creates a join tree with recommended joins between the tables selected by the user. The recommended joins are used to create a structured query language statement which is executed to return a result to the user.

Automated creation of join graphs for unrelated data sets among relational databases

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Framingham, MA, United States of America

John E O'Neil