Zscaler, Inc.

Karthikeyan Thamilarasu

Narinder Paul

Balakrishna Bhat Bayar

Julien Sobrier

Michael Andrew William Sutton

Sriram Natarajan

Chakkaravarthy Periyasamy Balaiah

Deepen Desai

Rubin Azad

Jithin Prajeev Nair

Shanghao Chen

Tejveer Singh

Systems and methods are provided for evaluating the effectiveness of network security tools for mitigating network security risks. According to one implementation, a method includes the step of analyzing a network to measure security parameters associated with the use of one or more network security tools that are configured for mitigating risk with respect to network compromise, data loss, lateral movement, and asset exposure. Based on the measured security parameters, the method further includes the step of quantifying the one or more network security tools to determine an effectiveness score defining an ability of the one or more network security tools, in combination, to counteract the network compromise, data loss, lateral movement, and asset exposure.

Risk mitigation effectiveness score of network security services

A cloud-based method, a behavioral analysis system, and a cloud-based security system can include a plurality of nodes communicatively coupled to one or more users, wherein the plurality of nodes each perform inline monitoring for one of the one or more users for security comprising malware detection and preclusion; and a behavioral analysis system communicatively coupled to the plurality of nodes, wherein the behavioral analysis system performs offline analysis for any suspicious content from the one or more users which is flagged by the plurality of nodes; wherein the plurality of nodes each comprise a set of known malware signatures for the inline monitoring that is periodically updated by the behavioral analysis system based on the offline analysis for the suspicious content.

Systems and methods for dynamic cloud-based malware behavior analysis

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Atlanta, GA, United States of America

Karthikeyan Thamilarasu