Patents by Inventor Anil Gathala
Anil Gathala 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).
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Patent number: 9898602Abstract: Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources. Various aspects may correct suspicious or performance-degrading mobile device behaviors. Various aspects may prevent identified suspicious or performance-degrading mobile device behaviors from degrading the performance and power utilization levels of a mobile device over time. Various aspects may restore an aging mobile device to its original performance and power utilization levels.Type: GrantFiled: January 29, 2015Date of Patent: February 20, 2018Assignee: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Sudha Anil Gathala, Soorgoli Ashok Halambi
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Patent number: 9495537Abstract: Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources.Type: GrantFiled: June 21, 2013Date of Patent: November 15, 2016Assignee: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Vinay Sridhara, Anil Gathala, Xuetao Wei
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Patent number: 9324034Abstract: Methods, systems and devices for generating data models in a communication system may include applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors. Such behavior vectors may be used to compute a weight value for one or more nodes of the boosted decision tree. Classifier models factors having a high probably of determining whether a mobile device behavior is benign or not benign based on the computed weight values may be identified. Computing weight values for boosted decision tree nodes may include computing an exclusive answer ratio for generated boosted decision tree nodes. The identified factors may be applied to the corpus of behavior vectors to generate a second family of classifier models identifying fewer factors and data points relevant for enabling the mobile device to determine whether a behavior is benign or not benign.Type: GrantFiled: February 21, 2013Date of Patent: April 26, 2016Assignee: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Xuetao Wei, Anil Gathala, Vinay Sridhara
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Patent number: 9298494Abstract: Methods, systems and devices for classifying mobile device behaviors of a first mobile device may include the first mobile device monitoring mobile device behaviors to generate a behavior vector, and applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign. The first mobile device may also send the behavior vector to a second mobile device, which may receive and apply the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign. The second mobile device may send the second determination to the first mobile device, which may receive the second determination, collate the first determination and the second determination to generate collated results, and determine whether the mobile device behavior is benign or not benign based on the collated results.Type: GrantFiled: March 14, 2013Date of Patent: March 29, 2016Assignee: QUALCOMM IncorporatedInventors: Anil Gathala, Rajarshi Gupta
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Patent number: 9202047Abstract: Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources. Various aspects may correct suspicious or performance-degrading mobile device behaviors. Various aspects may prevent identified suspicious or performance-degrading mobile device behaviors from degrading the performance and power utilization levels of a mobile device over time. Various aspects may restore an aging mobile device to its original performance and power utilization levels.Type: GrantFiled: September 26, 2012Date of Patent: December 1, 2015Assignee: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Sudha Anil Gathala, Soorgoli Ashok Halambi
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Patent number: 9189624Abstract: Methods, devices and systems for monitoring behaviors of a mobile computing device include observing in a non-master processing core a portion of a mobile device behavior that is relevant to the non-master processing core, generating a behavior signature that describes the observed portion of the mobile device behavior, and sending the generated behavior signature to a master processing core. The master processing core combines two or more behavior signatures received from the non-master processing cores to generate a global behavior vector, which may be used by an analyzer module to determine whether a distributed software application is not benign.Type: GrantFiled: May 2, 2014Date of Patent: November 17, 2015Assignee: QUALCOMM IncorporatedInventors: Anil Gathala, Rajarshi Gupta
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Patent number: 9152787Abstract: Methods, devices and systems for monitoring behaviors of a mobile computing device include observing in a non-master processing core a portion of a mobile device behavior that is relevant to the non-master processing core, generating a behavior signature that describes the observed portion of the mobile device behavior, and sending the generated behavior signature to a master processing core. The master processing core combines two or more behavior signatures received from the non-master processing cores to generate a global behavior vector, which may be used by an analyzer module to determine whether a distributed software application is benign or not benign.Type: GrantFiled: February 22, 2013Date of Patent: October 6, 2015Assignee: QUALCOMM IncorporatedInventors: Anil Gathala, Rajarshi Paul Gupta
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Publication number: 20150148109Abstract: Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources. Various aspects may correct suspicious or performance-degrading mobile device behaviors. Various aspects may prevent identified suspicious or performance-degrading mobile device behaviors from degrading the performance and power utilization levels of a mobile device over time. Various aspects may restore an aging mobile device to its original performance and power utilization levels.Type: ApplicationFiled: January 29, 2015Publication date: May 28, 2015Inventors: Rajarshi Gupta, Sudha Anil Gathala, Soorgoli Ashok Halambi
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Publication number: 20150046661Abstract: Mobile computing devices may be configured to compile and execute portions of a general purpose software application in an auxiliary processor (e.g., a DSP) of a multiprocessor system by reading and writing information to a shared memory. A first process (P1) on the applications processor may request address negotiation with a second process (P2) on the auxiliary processor, obtain a first address map from a first operating system, and send the first address map to the auxiliary processor. The second process (P2) may receive the first address map, obtain a second address map from a second operating system, identify matching addresses in the first and second address maps, store the matching addresses as common virtual addresses, and send the common virtual addresses back to the applications processor. The first and second processes (i.e., P1 and P2) may each use the common virtual addresses to map physical pages to the memory.Type: ApplicationFiled: August 7, 2013Publication date: February 12, 2015Applicant: QUALCOMM IncorporatedInventors: Anil Gathala, Andrey Ermolinskiy, Christopher A. Vick
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Publication number: 20140283024Abstract: Disclosed is a method for efficient behavioral analysis on a mobile station. In the method, one or more first behavioral characteristics associated with a first state of a finite state machine are observed. The one or more first behavioral characteristics may comprise a first subset of observable behavioral characteristics. The mobile station transitions from the first state to a second state. One or more second behavioral characteristics associated with the second state of the finite state machine are observed. The one or more second behavioral characteristics may comprise a second subset of the observable behavioral characteristics.Type: ApplicationFiled: March 13, 2013Publication date: September 18, 2014Applicant: Qualcomm IncorporatedInventors: Sudha Anil GATHALA, Rajarshi Gupta
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Publication number: 20140245306Abstract: Methods, devices and systems for monitoring behaviors of a mobile computing device include observing in a non-master processing core a portion of a mobile device behavior that is relevant to the non-master processing core, generating a behavior signature that describes the observed portion of the mobile device behavior, and sending the generated behavior signature to a master processing core. The master processing core combines two or more behavior signatures received from the non-master processing cores to generate a global behavior vector, which may be used by an analyzer module to determine whether a distributed software application is not benign.Type: ApplicationFiled: May 2, 2014Publication date: August 28, 2014Applicant: QUALCOMM IncorporatedInventors: Anil GATHALA, Rajarshi Gupta
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Publication number: 20140053260Abstract: Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources.Type: ApplicationFiled: June 21, 2013Publication date: February 20, 2014Inventors: Rajarshi Gupta, Vinay Sridhara, Anil Gathala, Xuetao Wei
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Publication number: 20130305359Abstract: Methods, devices and systems for monitoring behaviors of a mobile computing device include observing in a non-master processing core a portion of a mobile device behavior that is relevant to the non-master processing core, generating a behavior signature that describes the observed portion of the mobile device behavior, and sending the generated behavior signature to a master processing core. The master processing core combines two or more behavior signatures received from the non-master processing cores to generate a global behavior vector, which may be used by an analyzer module to determine whether a distributed software application is benign or not benign.Type: ApplicationFiled: February 22, 2013Publication date: November 14, 2013Applicant: Qualcomm IncorporatedInventors: Anil Gathala, Rajarshi Paul Gupta
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Publication number: 20130304677Abstract: Methods, systems and devices for generating data models in a client-cloud communication system may include applying machine learning techniques to generate a first family of classifier models that describe a cloud corpus of behavior vectors. Such vectors may be analyzed to identify factors in the first family of classifier models that have the highest probably of enabling a mobile device to conclusively determine whether a mobile device behavior is malicious or benign. Based on this analysis, a a second family of classifier models may be generated that identify significantly fewer factors and data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is malicious or benign based on the determined factors. A mobile device classifier module based on the second family of classifier models may be generated and made available for download by mobile devices, including devices contributing behavior vectors.Type: ApplicationFiled: February 25, 2013Publication date: November 14, 2013Applicant: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Xuetao Wei, Anil Gathala, Vinay Srishara
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Publication number: 20130303159Abstract: Methods, systems and devices for classifying mobile device behaviors of a first mobile device may include the first mobile device monitoring mobile device behaviors to generate a behavior vector, and applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign. The first mobile device may also send the behavior vector to a second mobile device, which may receive and apply the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign. The second mobile device may send the second determination to the first mobile device, which may receive the second determination, collate the first determination and the second determination to generate collated results, and determine whether the mobile device behavior is benign or not benign based on the collated results.Type: ApplicationFiled: March 14, 2013Publication date: November 14, 2013Applicant: Qualcomm IncorporatedInventors: Anil Gathala, Rajarshi Gupta
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Publication number: 20130304676Abstract: Methods, systems and devices for generating data models in a communication system may include applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors. Such behavior vectors may be used to compute a weight value for one or more nodes of the boosted decision tree. Classifier models factors having a high probably of determining whether a mobile device behavior is benign or not benign based on the computed weight values may be identified. Computing weight values for boosted decision tree nodes may include computing an exclusive answer ratio for generated boosted decision tree nodes. The identified factors may be applied to the corpus of behavior vectors to generate a second family of classifier models identifying fewer factors and data points relevant for enabling the mobile device to determine whether a behavior is benign or not benign.Type: ApplicationFiled: February 21, 2013Publication date: November 14, 2013Applicant: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Xuetao Wei, Anil Gathala, Vinay Sridhara
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Publication number: 20130305358Abstract: The various aspects include methods, systems, and devices configured to make use of caching techniques and behavior signature caches to improve processor performance and/or reduce the amount of power consumed by the computing device by reducing analyzer latency. The signature caching system may be configured to adapt to rapid and frequent changes in behavioral specifications and models and provide a multi-fold improvement in the scalability of behavioral analysis operations performed on the mobile device.Type: ApplicationFiled: January 25, 2013Publication date: November 14, 2013Applicant: QUALCOMM IncorporatedInventors: Anil Gathala, Rajarshi Gupta, Saumitra Das
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Publication number: 20130303154Abstract: Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources. Various aspects may correct suspicious or performance-degrading mobile device behaviors. Various aspects may prevent identified suspicious or performance-degrading mobile device behaviors from degrading the performance and power utilization levels of a mobile device over time. Various aspects may restore an aging mobile device to its original performance and power utilization levels.Type: ApplicationFiled: September 26, 2012Publication date: November 14, 2013Applicant: QUALCOMM IncorporatedInventors: Rajarshi Gupta, Sudha Anil Gathala, Soorgoli Ashok Halambi