Cisco Technology, Inc.

Kai Zhu

Navindra Yadav

Umamaheswaran Arumugam

Aiyesha Ma

Supreeth Rao

Darshan Shrinath Purandare

Prasannakumar Jobigenahally Malleshaiah

Tapan Shrikrishna Patwardhan

Hai Trong Vu

Michael Standish Watts

Shashi Gandham

Jothi Prakash Prabakaran

Duy Nguyen

Supreeth Hosur Nagesh Rao

Ashok K Kumar

Robert Bukofser

Hanlin He

Hongyang Zhang

Micheal Watts

Systems, methods, and computer-readable media for determine a neighborhood graph can include the following processes. A neighborhood graph system generates a neighborhood graph for a plurality of nodes in an enterprise network, the neighborhood graph representing a multi-hop connections between any two nodes of the plurality of nodes. A security score service determines a security score for each of the plurality of nodes to yield a plurality of scores. The neighborhood graph system updates the neighborhood graph of the plurality of nodes using the plurality of scores to provide a visual representation of securities of the plurality of nodes relative to each other.

Secure neighborhoods assessment in enterprise networks

The present disclosure relates to securing workloads of a network by identifying compromised elements in communication with the network and preventing their access to network resources. In one aspect, a method includes monitoring network traffic at network elements of a network; detecting a compromised element in communication with one or more of the network elements, the compromised element being associated with at least one network threat; and based on a defined network policy, applying one of a number of different access prevention schemes to the compromised element to prevent access to the network by the compromised element.

Securing network resources from known threats

Aspects of the disclosed technology provide methods for automatically tuning load-balancer configurations in a network environment. In some implementations, a process of the disclosed technology includes steps for collecting flow records of traffic flow segments at a middle box in a network environment, the traffic flow segments corresponding to one or more traffic flows passing through the middle box, analyzing the flow records to identify one or more traffic patterns in the network environment, and automatically updating a load balancer configuration based on the one or more traffic patterns, wherein updating the load balancer configuration improves at least one traffic flow parameter for at least one of the traffic flows passing through the middle box. Systems and machine-readable media are also provided.

Load balancing configuration based on traffic flow telemetry

Systems, methods, and computer-readable media for flow stitching network traffic flow segments at a middlebox in a network environment. In some embodiments, flow records of traffic flow segments at a middlebox in a network environment are collected. The flow records can include transaction identifiers assigned to the traffic flow segments. Sources and destinations of the traffic flow segments with respect to the middlebox can be identified using the flow records. Further, the traffic flow segments can be stitched together to form a plurality of stitched traffic flows at the middlebox based on the transaction identifiers and the sources and destinations of the traffic flow segments in the network environment with respect to the middlebox. A configuration of the middlebox operating in the network environment can be identified based on the stitched traffic flows at the middlebox in the network environment.

Automatic configuration discovery based on traffic flow data

Systems, methods, and computer-readable media for flow stitching network traffic flow segments across middleboxes. A method can include collecting flow records of traffic flow segments at a first middlebox and a second middlebox in a network environment including one or more transaction identifiers assigned to the traffic flow segments. Sources and destinations of the traffic flow segments can be identified with respect to the first middlebox and the second middlebox. Corresponding subsets of the traffic flow segments can be stitched together to from a first stitched traffic flow at the first middlebox and a second stitched traffic flow at the second middlebox. The first and second stitched traffic flows can be stitched together to form a cross-middlebox stitched traffic flow across the first middlebox and the second middlebox. The cross-middlebox stitched traffic flow can be incorporated as part of network traffic data for the network environment.

Discovery of middleboxes using traffic flow stitching

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San Jose, CA, United States of America

Kai Zhu