Preventsys, Inc.

Other

Mcafee, Inc.

John Leslie Williams

John Patrick Ravenel

Brian Costello

John Pelly

John M Payne

Stephen J Ritter

Thomas Paul Walpole

M Celeste Rutherford

Ryan Tadashi Nakawatase

Jonathan M Urdan

Thomas Paul Walpoie

John Payne

Rayan Tadashi Nakawatase

A prevention-based network auditing system includes a central compliance server providing a user interface allowing a user to schedule and configure a network audit. The configured audit is stored in an audit repository until its scheduled time. At such a time, the compliance server automatically invokes one or more audit servers to gather information about the network. The compliance server receives the gathered information and electronically applies a network policy to the information for determining compliance with the policy. A remediation task may be generated if the policy has been violated, and the task monitored until its completion.

System and method for automated policy audit and remediation management

A prevention-based network auditing system includes a plurality of heterogeneous information sources gathering information about the network. An audit server invokes the heterogeneous information sources via a uniform communications interface to gather information about the network, and converts the information gathered by the information sources into a normalized data format such as, for example, into XML (Extensible Markup Language). The converted information is then stored in an audit repository for security and regulatory policy assessment, network vulnerability analysis, report generation, and security improvement recommendations.

System and method for interfacing with heterogeneous network data gathering tools

A method for characterizing website visitors based on visitor passive parameters and using the characterization to select and/or market website content. The passive visitor parameters include data in the browser agent, time of a website visit, IP address, etc. Such visitor passive parameters are available each time a visitor visits a website. In a first step, a first embodiment of the method anonymously compares the visitor passive parameters with known demographics, for example, at financial websites, to create a statistical mapping between the visitor passive parameters and the demographics. In a second step, the mapping is used to estimate demographics data for future website visitors and then site content provided to the future website visitors is based on the estimated demographics.

Passive parameter based demographics generation

A prevention-based network auditing system includes a central compliance server generating network policies and configuring audits of the data communications network. The compliance server presents a graphical user interface (GUI) to describe the specific data gathering parameters, policies to be analyzed, and the schedule of analysis. One or more audit servers strategically deployed around the network employ heterogeneous data-gathering tools to gather information about the network in response to the configured audits, and transmit the gathered information to the compliance server. An audit repository stores the gathered information for use by the compliance server for security and regulatory policy assessment, network vulnerability analysis, report generation, and security improvement recommendations.

Network audit and policy assurance system

A prevention-based network auditing system includes an audit repository storing network information gathered by a plurality of heterogeneous information sources. A semantic normalization module identifies semantic equivalencies in the gathered information, and generates a map listing for each fact gathered by an information source, an equivalent fact or set of facts gathered by each of the other information sources. A network policy is then uniformly applied to the information that is identified as being semantically equivalent.

System and method for security information normalization

A prevention-based network auditing system includes a central compliance server storing both natural language policy documents and machine-processable policy rules in an audit repository. The compliance server provides a client-side user interface allowing a user to easily generate a machine-auditable policy by selecting/generating a natural language policy source document, and linking the applicable machine-processable policy rules to the applicable portions of the source document. The selected machine-processable policy rules are then applied to information gathered about the network during a scheduled network audit session for efficiently and systematically determining whether policy violations and/or vulnerabilities exist.

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San Diego, CA, United States of America

John Leslie Williams