Skyhigh Networks, Inc.

Skyhigh Security LLC

Sandeep Chandana

Sekhar R Sarukkai

Satyanarayana Vummidi

Santosh Raghuram Kumar

Vinay Gupta

Madhavi Kavathekar

A cloud security system and method implements cloud activity threat detection using analysis of cloud usage user behavior. In particular, the cloud security system and method implements threat detection for users, cloud service providers, or tenants (enterprises) of the cloud security system who are new or unknown to the cloud security system and therefore lacking sufficient cloud activity data to generate an accurate behavior model for effective threat detection. In accordance with embodiments of the present invention, the cloud security system and method performs user behavior analysis to generate generalized user behavior models for user groups, where each user group includes users with similar cloud usage behavior. The user behavior models of the user groups are assigned to users with sparse cloud activity data. In this manner, the cloud security system and method of the present invention ensures effective threat detection by using accurate and reliable user behavior models.

Cloud activity threat detection for sparse and limited user behavior data

A service action category based cloud security system and method implement cloud security by categorizing service actions of cloud service providers into a set of service action categories. The service action categorization is performed agnostic to the applications or functions provided by the cloud service providers and also agnostic to the cloud service providers. With the service actions of cloud service providers thus categorized, cloud security monitoring and threat detection can be performed based on service action categories. Thus, cloud security can be implemented without requiring knowledge of the applications supported by the cloud service providers and without knowing all of the individual service actions supported by the cloud service providers.

Cloud security system implementing service action categorization

A system and method for filtering detected anomalies in cloud service usage activities associated with an enterprise uses a trusted location analysis to filter detected anomalies. The locations from which the cloud usage activities are made are analyzed and designated as trusted or non-trusted. The trusted location determination is used to filter the detected anomalies that are associated with trusted locations and therefore may be of low risk. In this manner, actions can be taken only on detected anomalies that are associated with non-trusted locations and therefore may be high risk. The system and method of the present invention enable security incidents, anomalies and threats from cloud activity to be detected, filtered and annotated based on the location heuristics. The trusted location analysis identifies trusted locations automatically using cloud activity usage data and does not rely on potentially unreliable location data from user input.

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Fremont, CA, United States of America

Sandeep Chandana