Abstract: A method for a testing system to perform fuzzy testing of a software system, wherein the software system comprises a plurality of callable units and is arranged to receive input for the software system to process, the method comprising: determining, for each callable unit of the plurality of callable units, based on one or more security vulnerability metrics, a target number of times that callable unit is to be tested; initializing a ranked plurality of queues, each queue for storing one or more seeds, said initializing comprising storing one or more initial seeds in a corresponding queue of the ranked plurality of queues; performing a sequence of tests, wherein performing each test comprises: obtaining a seed from the highest ranked non-empty queue; performing a mutation process on the obtained seed to generate a test seed, wherein the mutation process is configured, at least in part, by mutation guidance information; providing the test seed as input to the software system for the software system to process;

Abstract: Methods and systems for continuing authenticating a user of a device based on external conditions. A likelihood value, indicating the likelihood that the external conditions have been satisfied, is generated and the user is permitted to continue the authenticated use when the value is determined to be acceptable.

Abstract: A method for a testing system to perform fuzzy testing of a software system, wherein the software system comprises a plurality of callable units and is arranged to receive input for the software system to process, the method comprising: determining, for each callable unit of the plurality of callable units, based on one or more security vulnerability metrics, a target number of times that callable unit is to be tested; initializing a ranked plurality of queues, each queue for storing one or more seeds, said initializing comprising storing one or more initial seeds in a corresponding queue of the ranked plurality of queues; performing a sequence of tests, wherein performing each test comprises: obtaining a seed from the highest ranked non-empty queue; performing a mutation process on the obtained seed to generate a test seed, wherein the mutation process is configured, at least in part, by mutation guidance information; providing the test seed as input to the software system for the software system to process;

Abstract: Methods and systems for providing secure digital access to services are described. Embodiments include user behavior tracking, learning, and updating one or more contextual access algorithms and thereafter can act as multi-factor authentications. The method may include receiving data for a group of users and initializing a machine learning algorithm with the group data. The method may also collect individual user data and context data periodically, including characteristic behavior data, and update the machine learning algorithm with the individual user data. The method may further calculate a threshold for tolerance based on the updated algorithm, and verify user requests for access to the service. A multi-factor authentication may be presented to the user when the verifications are not acceptable, such as by being below a threshold. A permissions data structure can be generated and used to control access to the service.

Abstract: Methods and systems for continuously authenticating a user of a device by comparing current sensor data of the device being used with a fingerprint generated from sensor data collected from the device during use by an authorized user. A likelihood value, indicating the likelihood that the user is an authorized user of the device, is generated and the user is authenticated when the likelihood value is determined to be acceptable.

Abstract: Methods and systems for providing secure digital access to services are described. Embodiments include user behavior tracking, learning, and updating one or more contextual access algorithms and thereafter can act as multi-factor authentications. The method may include receiving data for a group of users and initializing a machine learning algorithm with the group data. The method may also collect individual user data and context data periodically, including characteristic behavior data, and update the machine learning algorithm with the individual user data. The method may further calculate a threshold for tolerance based on the updated algorithm, and verify user requests for access to the service. A multi-factor authentication may be presented to the user when the verifications are not acceptable, such as by being below a threshold. A permissions data structure can be generated and used to control access to the service.

Abstract: A method and system for watermarking content utilizing a user device GPU. Embodiments include receiving on a processing server a request from a video server for a video to be played on the user's device. The processing server may extract a set of identifying information, such as user information, from the request for the video. The processing server may further prepare shader software code which is to be executed on a GPU present on the user's device. The code preparation may include creating a watermarking procedure to be executed during playback on the user device. The processing server may further transmit the shader software code to the streaming video server to be transmitted to the user device for execution during video playback.

Abstract: A method and system for watermarking content utilizing a user device GPU. Embodiments include receiving on a processing server a request from a video server for a video to be played on the user's device. The processing server may extract a set of identifying information, such as user information, from the request for the video. The processing server may further prepare shader software code which is to be executed on a GPU present on the user's device. The code preparation may include creating a watermarking procedure to be executed during playback on the user device. The processing server may further transmit the shader software code to the streaming video server to be transmitted to the user device for execution during video playback.

Abstract: A method and system for watermarking content utilizing a user device GPU. Embodiments include receiving on a processing server a request from a video server for a video to be played on the user's device. The processing server may extract a set of identifying information, such as user information, from the request for the video. The processing server may further prepare shader software code which is to be executed on a GPU present on the user's device. The code preparation may include creating a watermarking procedure to be executed during playback on the user device. The processing server may further transmit the shader software code to the streaming video server to be transmitted to the user device for execution during video playback.

Abstract: A method of protecting the execution of a cryptographic hash function, such as SHA-256, in a computing environment where inputs, outputs and intermediate values can be observed. The method consists of encoding input messages so that hash function inputs are placed in a transformed domain, and then applying a transformed cryptographic hash function to produce an encoded output digest; the transformed cryptographic hash function implements the cryptographic hash function in the transformed domain.

Abstract: A method of protecting the execution of a cryptographic hash function, such as SHA-256, in a computing environment where inputs, outputs and intermediate values can be observed. The method consists of encoding input messages so that hash function inputs are placed in a transformed domain, and then applying a transformed cryptographic hash function to produce an encoded output digest; the transformed cryptographic hash function implements the cryptographic hash function in the transformed domain.