Patents by Inventor Sandeep Chandana

Sandeep Chandana has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210234902
    Abstract: 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.
    Type: Application
    Filed: April 12, 2021
    Publication date: July 29, 2021
    Inventors: Sandeep Chandana, Sekhar Sarukkai
  • Patent number: 11070572
    Abstract: Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.
    Type: Grant
    Filed: July 9, 2019
    Date of Patent: July 20, 2021
    Assignee: McAfee, LLC
    Inventors: Adam Wosotowsky, Yonghong Huang, Eric Peterson, John Wagener, Joanna Negrete, Armando Rodriguez, Celeste Fralick, Sandeep Chandana
  • Patent number: 10999325
    Abstract: 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.
    Type: Grant
    Filed: October 20, 2017
    Date of Patent: May 4, 2021
    Assignee: Skyhigh Networks, LLC
    Inventors: Sandeep Chandana, Sekhar Sarukkai
  • Publication number: 20210112086
    Abstract: 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.
    Type: Application
    Filed: December 22, 2020
    Publication date: April 15, 2021
    Inventors: Sandeep Chandana, Santosh Raghuram Kumar, Sekhar Sarukkai, Satyanarayana Vummidi, Madhavi Kavathekar, Vinay Gupta
  • Patent number: 10911474
    Abstract: 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.
    Type: Grant
    Filed: May 13, 2019
    Date of Patent: February 2, 2021
    Assignee: Skyhigh Networks, LLC
    Inventors: Sandeep Chandana, Santosh Raghuram Kumar, Sekhar Sarukkai, Satyanarayana Vummidi, Madhavi Kavathekar, Vinay Gupta
  • Publication number: 20210014247
    Abstract: Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.
    Type: Application
    Filed: July 9, 2019
    Publication date: January 14, 2021
    Inventors: Adam Wosotowsky, Yonghong Huang, Eric Peterson, John Wagener, Joanna Negrete, Armando Rodriguez, Celeste Fralick, Sandeep Chandana
  • Publication number: 20190373006
    Abstract: 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.
    Type: Application
    Filed: May 13, 2019
    Publication date: December 5, 2019
    Inventors: Sandeep Chandana, Santosh Raghuram Kumar, Sekhar Sarukkai, Satyanarayana Vummidi, Madhavi Kavathekar, Vinay Gupta
  • Patent number: 10484414
    Abstract: 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.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: November 19, 2019
    Assignee: Skyhigh Networks, LLC
    Inventors: Santosh Raghuram Kumar, Sandeep Chandana, Sekhar Sarukkai, Satyanarayana Vummidi
  • Publication number: 20190230110
    Abstract: 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.
    Type: Application
    Filed: March 29, 2019
    Publication date: July 25, 2019
    Inventors: Santosh Raghuram Kumar, Sandeep Chandana, Sekhar Sarukkai, Satyanarayana Vummidi
  • Patent number: 10291638
    Abstract: 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.
    Type: Grant
    Filed: September 8, 2016
    Date of Patent: May 14, 2019
    Assignee: Skyhigh Networks, LLC
    Inventors: Sandeep Chandana, Santosh Raghuram Kumar, Sekhar Sarukkai, Satyanarayana Vummidi, Madhavi Kavathekar, Vinay Gupta
  • Patent number: 10264006
    Abstract: 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.
    Type: Grant
    Filed: November 21, 2017
    Date of Patent: April 16, 2019
    Assignee: Skyhigh Networks, LLC
    Inventors: Santosh Raghuram Kumar, Sandeep Chandana, Sekhar Sarukkai, Satyanarayana Vummidi
  • Publication number: 20180191760
    Abstract: 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.
    Type: Application
    Filed: November 21, 2017
    Publication date: July 5, 2018
    Inventors: Santosh Raghuram Kumar, Sandeep Chandana, Sekhar Sarukkai, Satyanarayana Vummidi
  • Patent number: 9853992
    Abstract: 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.
    Type: Grant
    Filed: May 2, 2016
    Date of Patent: December 26, 2017
    Assignee: Skyhigh Networks, Inc
    Inventors: Santosh Raghuram Kumar, Sandeep Chandana, Sekhar Sarukkai, Satyanarayana Vummidi