Abstract: Methods and systems are provided to determine when a first electronic device is emulating a second electronic device. The first electronic device may be operated through indirect inputs such as through a mouse and keyboard. The second electronic device may be operated through direct inputs such as inputs received through a touchscreen. Interaction data received from the first electronic device may be used to determine that the first electronic device is operating an emulator. Interaction data may include data associated with scrolling on the electronic device and such data may allow a determination that the electronic device received indirect inputs and, thus, is operating an emulator.

Abstract: Techniques are disclosed relating to determining whether geographic locations of a user computing device satisfy a location consensus threshold. A computer system receives results of a plurality of location determination operations, each of which specifies a geographic location of a computing device initiating an action. The computer system then makes a determination whether the received results satisfy a consensus threshold as to geographic location of the computing device. In some embodiments, the determination is usable to select, from a plurality of sets of rules for different geographic regions, a particular set of rules for processing the action. In some cases, the particular set of rules is usable to determine whether to process the action. Such techniques may advantageously allow a processing system to understand how to process actions initiated by a computing device associated with different geographic locations.

Abstract: A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.

Abstract: Methods and systems are presented for assessing a veracity of device attributes obtained from a computer device based on estimating a number of processing cycles used by the computer device to perform a particular function. In response to receiving a transaction request from the computer device, software programming instructions are transmitted to the computer device for obtaining device attributes of the computer device. The software programming instructions may also include code that estimate a number of processing cycles used by the computer to perform a particular function. The particular function may be associated with obtaining at least one of the device attributes of the computer device. The estimated number of processing cycles may be compared against a benchmark profile. A risk associated with the transaction request is determined based on the comparing.

Abstract: A system and method for detecting anomalous access to tables is described. A query for accessing a table from a requesting user is received. A set of users similar to the requesting user is determined. The probability that the requesting user should access the table is calculated. Whether the user should be accessing the table based on the calculated probability is determined.

Abstract: Techniques are disclosed for passively characterizing a type of host or computing device which may be engaged in a transaction between the host and another computing device. Observation data corresponding to one or more sessions of network traffic between an unclassified host and a second system may be passively generated by a device characterization server. The observation data can be processed by the device characterization server using a machine-learning classifier. The machine-learning classifier can be trained with a set of training data that includes multiple sessions of network traffic from multiple training data hosts. Each session of network traffic includes an exchange of multiple packets in various embodiments, including packets sent from, and packets received by, the training data hosts. Based on the processing, the unclassified host may be characterized by the device characterization server as one of a physical computing device, a virtual machine, or a container.

Abstract: Embodiments described herein are directed to determining whether an application executing on a compute instance has been corrupted or compromised by malicious code. This may achieved by statically analyzing an image file from which the application is based to determine characteristics thereof. Such characteristics are representative of the behavior that is expected to be performed by the application during execution. During execution of the application, runtime characteristics of the application are determined, which are determined based on an analysis of the address space in memory allocated for a computing process of the application. The statically-determined characteristics are compared to the determined runtime characteristics to determine discrepancies therebetween. In the event that a discrepancy is found, a determination is made that the application has been compromised or corrupted and an appropriate remedial action is automatically performed.

Abstract: Methods and systems are provided to determine when a first electronic device is emulating a second electronic device. The first electronic device may be operated through indirect inputs such as through a mouse and keyboard. The second electronic device may be operated through direct inputs such as inputs received through a touchscreen. Interaction data received from the first electronic device may be used to determine that the first electronic device is operating an emulator. Interaction data may include data associated with scrolling on the electronic device and such data may allow a determination that the electronic device received indirect inputs and, thus, is operating an emulator.

Abstract: A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.

Abstract: Methods and systems are provided to determine when a first electronic device is emulating a second electronic device. The first electronic device may be operated through indirect inputs such as through a mouse and keyboard. The second electronic device may be operated through direct inputs such as inputs received through a touchscreen. Interaction data received from the first electronic device may be used to determine that the first electronic device is operating an emulator. Interaction data may include data associated with scrolling on the electronic device and such data may allow a determination that the electronic device received indirect inputs and, thus, is operating an emulator.

Abstract: Techniques are disclosed relating to determining whether geographic locations of a user computing device satisfy a location consensus threshold. A computer system receives results of a plurality of location determination operations, each of which specifies a geographic location of a computing device initiating an action. The computer system then makes a determination whether the received results satisfy a consensus threshold as to geographic location of the computing device. In some embodiments, the determination is usable to select, from a plurality of sets of rules for different geographic regions, a particular set of rules for processing the action. In some cases, the particular set of rules is usable to determine whether to process the action. Such techniques may advantageously allow a processing system to understand how to process actions initiated by a computing device associated with different geographic locations.

Abstract: Methods and systems for creating and analyzing encoded vector information from user activities relative to one or more services and/or devices are described. Sentiment analysis using natural language processing can be performed on user activity and a determination can be made as to whether the sentiment of a user account has fraudulent or benign sentiment. Should a fraudulent account sentiment be determined, mitigation measures may be taken including flagging and restricting a user account.

Abstract: A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.

Abstract: Techniques are disclosed for passively characterizing a type of host or computing device which may be engaged in a transaction between the host and another computing device. Observation data corresponding to one or more sessions of network traffic between an unclassified host and a second system may be passively generated by a device characterization server. The observation data can be processed by the device characterization server using a machine-learning classifier. The machine-learning classifier can be trained with a set of training data that includes multiple sessions of network traffic from multiple training data hosts. Each session of network traffic includes an exchange of multiple packets in various embodiments, including packets sent from, and packets received by, the training data hosts. Based on the processing, the unclassified host may be characterized by the device characterization server as one of a physical computing device, a virtual machine, or a container.

Abstract: A system and method for detecting anomalous access to tables is described. A query for accessing a table from a requesting user is received. A set of users similar to the requesting user is determined. The probability that the requesting user should access the table is calculated. Whether the user should be accessing the table based on the calculated probability is determined.

Abstract: Techniques are disclosed for passively characterizing a type of host or computing device which may be engaged in a transaction between the host and another computing device. Observation data corresponding to one or more sessions of network traffic between an unclassified host and a second system may be passively generated by a device characterization server. The observation data can be processed by the device characterization server using a machine-learning classifier. The machine-learning classifier can be trained with a set of training data that includes multiple sessions of network traffic from multiple training data hosts. Each session of network traffic includes an exchange of multiple packets in various embodiments, including packets sent from, and packets received by, the training data hosts. Based on the processing, the unclassified host may be characterized by the device characterization server as one of a physical computing device, a virtual machine, or a container.

Abstract: A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.

Abstract: Methods and systems are presented for assessing a veracity of device attributes obtained from a computer device based on estimating a number of processing cycles used by the computer device to perform a particular function. In response to receiving a transaction request from the computer device, software programming instructions are transmitted to the computer device for obtaining device attributes of the computer device. The software programming instructions may also include code that estimate a number of processing cycles used by the computer to perform a particular function. The particular function may be associated with obtaining at least one of the device attributes of the computer device. The estimated number of processing cycles may be compared against a benchmark profile. A risk associated with the transaction request is determined based on the comparing.

Abstract: Methods and systems are provided to determine when a first electronic device is emulating a second electronic device. The first electronic device may be operated through indirect inputs such as through a mouse and keyboard. The second electronic device may be operated through direct inputs such as inputs received through a touchscreen. Interaction data received from the first electronic device may be used to determine that the first electronic device is operating an emulator. Interaction data may include data associated with scrolling on the electronic device and such data may allow a determination that the electronic device received indirect inputs and, thus, is operating an emulator.

Abstract: Techniques are disclosed for passively characterizing a type of host or computing device which may be engaged in a transaction between the host and another computing device. Observation data corresponding to one or more sessions of network traffic between an unclassified host and a second system may be passively generated by a device characterization server. The observation data can be processed by the device characterization server using a machine-learning classifier. The machine-learning classifier can be trained with a set of training data that includes multiple sessions of network traffic from multiple training data hosts. Each session of network traffic includes an exchange of multiple packets in various embodiments, including packets sent from, and packets received by, the training data hosts. Based on the processing, the unclassified host may be characterized by the device characterization server as one of a physical computing device, a virtual machine, or a container.