Centripetal Networks, Inc.

Wake Forest University

Great Wall Systems

Centripetal LLC

David K Ahn

Sean A Moore

Peter P Geremia

Pierre Mallett, Iii

Robert T Perry

Steven Rogers

David J Vining

Yaorong Ge

David R Stelts

Jonathan R Rogers

Keith A George

Douglas M DiSabello

Gordon W Hunt

Paul F Hemler

Tiffany W Salido

Jess P Parnell

John W Fenton

Cody Michael Baker

Travis Duane Camechis

Jared Holmberg

Daniel Rogers

Tyler J Wendell

Hansaka A Kodituwakku

Pierre Mallett Iii

Douglas Disabello

Douglas M Disabello

Iii Pierre Mallett

Sean Moore

A packet-filtering system configured to filter packets in accordance with packet-filtering rules may receive data indicating network-threat indicators and may configure the packet-filtering rules to cause the packet-filtering system to identify packets comprising unencrypted data, and packets comprising encrypted data. A portion of the unencrypted data may correspond to one or more of the network-threat indicators, and the packet-filtering rules may be configured to cause the packet-filtering system to determine, based on the portion of the unencrypted data, that the packets comprising encrypted data correspond to the one or more network-threat indicators.

Rule-based network-threat detection for encrypted communications

In some variations, first and second rule sets may be received by a network protection device. The first and second rule sets may be preprocessed. The network protection device may be configured to process packets in accordance with the first rule set. Packets may be received by the network protection device. A first portion of the packets may be processed in accordance with the first rule set. The network protection device may be reconfigured to process packets in accordance with the second rule set. A second portion of the packets may be processed in accordance with the second rule set.

Rule swapping in a packet network

Aspects described herein may relate to cyber threat detection based on threat context and/or threat changes. Cyber threat intelligence (CTI) data may be received from a CTI provider. Endpoint data that indicates evidence that endpoints are cyber threats may be determined based on the CTI data. The endpoint data may be analyzed and/or compared to stored data associated with the endpoint. The analysis and/or comparison may be performed to determine whether evidence that the endpoint is a cyber threat has changed. Based on any changes, dispositions for the endpoint may be determined and sent. The dispositions may change how devices filter network traffic associated with the endpoint. Alternatives to default dispositions may be determined based on a impact of blocking potentially legitimate network traffic to and/or from the endpoints. Machine-learning models may assist in processing and analyzing CTI data, performing threat monitoring, and/or determining feeds that include the dispositions.

Cyber threat detection based on threat context, threat changes, and/or impact status

SSL/TLS certificate filtering devices, systems and processes may filter packets based on risk associated with each packet. A risk score may be determined for each packet based on associated threats and risks. Risk scores may be determined based on certificates, certificate authorities, and/or end users associated with each packet. The certificates may be scored and/or categorized by threats and risk.

Methods and systems for certificate filtering

Methods, systems, and computer-readable media for efficiently detecting threat incidents for cyber threat analysis are described herein. In various embodiments, a computing device, which may be located at a boundary between a protected network associated with the enterprise and an unprotected network, may combine one or more threat indicators received from one or more threat intelligence providers; may generate one or more packet capture and packet filtering rules based on the combined threat indicators; and, may capture or filter, on a packet-by-packet basis, at least one packet based on the generated rules. In other embodiments, a computing device may generate a packet capture file comprising raw packet content and corresponding threat context information, wherein the threat context information may comprise a filtering rule and an associated threat indicator that caused the packet to be captured.

Efficient packet capture for cyber threat analysis

Methods and systems for protecting a secured network are presented. For example, one or more packet security gateways may be associated with a security policy management server. At each packet security gateway, a dynamic security policy may be received from the security policy management server, packets associated with a network protected by the packet security gateway may be received, and at least one of multiple packet transformation functions specified by the dynamic security policy may be performed on the packets.

Methods and systems for protecting a secured network

Aspects of the disclosure relate to identity-based DNS-traffic routing and monitoring. A computing platform may establish, using an encrypted DNS process, a secure DNS session by executing an encrypted session handshake with a client device, which may include receiving a security certificate for the encrypted DNS process that identifies a user of the client device. The computing platform may receive an encrypted DNS query request comprising a request for an IP address for a specified domain name. The computing platform may determine, based on the security certificate, an identity of the user. The computing platform may determine, based on the identity of the user, a security policy indicating domain matching criteria and corresponding actions to take on matching domain names. The computing platform may determine a first action corresponding to the domain name, and may send, based on the first action, an encrypted DNS query response.

Identity-based application of domain filtering rules using domain name system (DNS) platform

A packet-filtering device may receive packet-filtering rules configured to cause the packet-filtering device to identify packets corresponding to network-threat indicators. The packet-filtering device may receive packets and, for each packet, may determine that the packet corresponds to criteria specified by a packet-filtering rule. The criteria may correspond to one or more of the network-threat indicators. The packet-filtering device may apply an operator specified by the packet-filtering rule. The operator may be configured to cause the packet-filtering device to either prevent the packet from continuing toward its destination or allow the packet to continue toward its destination. The packet-filtering device may generate a log entry comprising information from the packet-filtering rule that identifies the one or more network-threat indicators and indicating whether the packet-filtering device prevented the packet from continuing toward its destination or allowed the packet to continue toward its destination.

Rule-based network-threat detection

A computing system may identify packets received by a network device from a host located in a first network and may generate log entries corresponding to the packets received by the network device. The computing system may identify packets transmitted by the network device to a host located in a second network and may generate log entries corresponding to the packets transmitted by the network device. Utilizing the log entries corresponding to the packets received by the network device and the log entries corresponding to the packets transmitted by the network device, the computing system may correlate the packets transmitted by the network device with the packets received by the network device.

Correlating packets in communications networks

Rule-based network threat detection for encrypted communications

Growing community of inventors

Winston-Salem, NC, United States of America

David K Ahn