Abstract: This disclosure relates to systems and methods of risk detection in an electronic network. The method may include receiving a first portion of session context information for an interaction of an individual over a limited bandwidth network, the first portion including a session identifier for the interaction. The method may include retrieving a second portion of session context information for the interaction over a cloud data pipe using the session identifier, in response to receiving the first portion. The method may include accessing, a data structure representing connected knowledge of the individual. The method may include receiving, via a distributed system, security reputation data including aggregated information from a plurality of members. The method may include analyzing the session context information using the security reputation. The method may include generating a security risk score for the interaction based on the session context information, data structure, and the security reputation data.

Abstract: This disclosure relates to systems and methods of risk detection in an electronic network. The method may include receiving a first portion of session context information for an interaction of an individual over a limited bandwidth network, the first portion including a session identifier for the interaction. The method may include retrieving a second portion of session context information for the interaction over a cloud data pipe using the session identifier, in response to receiving the first portion. The method may include accessing, a data structure representing connected knowledge of the individual. The method may include receiving, via a distributed system, security reputation data including aggregated information from a plurality of members. The method may include analyzing the session context information using the security reputation. The method may include generating a security risk score for the interaction based on the session context information, data structure, and the security reputation data.

Abstract: Devices and methods for securing electronic transactions in a computing network are configured to receive a transaction, access transaction contextual data for the transaction, and apply one or more authentication decision rules to the transaction contextual data to determine initial authentication assessment information for the transaction. Further, aspects are configured to convert the initial authentication assessment information into a condensed authentication assessment indicator having an assessment value selected from a plurality of assessment values based on an assessment value definition, and transmit the condensed authentication assessment indicator. Also, aspects receive a transaction authentication decision based in part on the condensed authentication assessment indicator, and process or deny processing of the transaction based on the transaction authentication decision.

Abstract: Risk scores are generated by systems that use features or inputs from the current transactions, some summary statistics like velocity and some statistics calculated in batch mode which traverse hierarchical classification levels of entities, including classified attribute levels of known transactions, to identify neighborhoods of related entities and related transactions. Corresponding records of transaction information are extracted from or are otherwise generated from neighborhoods of the related transactions associated with the defined neighborhoods of entities/transactions.

Abstract: This disclosure relates to systems and methods of risk detection in an electronic network. The method may include receiving a first portion of session context information for an interaction of an individual over a limited bandwidth network, the first portion including a session identifier for the interaction. The method may include retrieving a second portion of session context information for the interaction over a cloud data pipe using the session identifier, in response to receiving the first portion. The method may include accessing, a data structure representing connected knowledge of the individual. The method may include receiving, via a distributed system, security reputation data including aggregated information from a plurality of members. The method may include analyzing the session context information using the security reputation. The method may include generating a security risk score for the interaction based on the session context information, data structure, and the security reputation data.

Abstract: A system is described herein for managing digital transactions over a network with incomplete information. The system includes a data collection component and a transaction control component that may employ a prospective control model that is trained with fully matured data as well as partially matured data regarding past digital transactions. The transaction control component is configured to estimate an inauthentic rate of inauthentic digital transactions being wrongly approved for a current time period. A set of future reference values may be determined based on the estimated inauthentic rate. The set of future reference values relate to a predicted future decision made for the digital transaction. A set of current values may be determined based on the set of future reference values. Based on the set of current values, the transaction control component may determine whether the digital transaction should be rejected as inauthentic or approved as authentic.

Abstract: Risk scores are generated by systems that use features or inputs from the current transactions, some summary statistics like velocity and some statistics calculated in batch mode which traverse hierarchical classification levels of entities, including classified attribute levels of known transactions, to identify neighborhoods of related entities and related transactions. Corresponding records of transaction information are extracted from or are otherwise generated from neighborhoods of the related transactions associated with the defined neighborhoods of entities/transactions.

Abstract: This disclosure relates to systems and methods of risk detection in an electronic network. The method may include receiving a first portion of session context information for an interaction of an individual over a limited bandwidth network, the first portion including a session identifier for the interaction. The method may include retrieving a second portion of session context information for the interaction over a cloud data pipe using the session identifier, in response to receiving the first portion. The method may include accessing, a data structure representing connected knowledge of the individual. The method may include receiving, via a distributed system, security reputation data including aggregated information from a plurality of members. The method may include analyzing the session context information using the security reputation. The method may include generating a security risk score for the interaction based on the session context information, data structure, and the security reputation data.

Abstract: Devices and methods for securing electronic transactions in a computing network are configured to receive a transaction, access transaction contextual data for the transaction, and apply one or more authentication decision rules to the transaction contextual data to determine initial authentication assessment information for the transaction. Further, aspects are configured to convert the initial authentication assessment information into a condensed authentication assessment indicator having an assessment value selected from a plurality of assessment values based on an assessment value definition, and transmit the condensed authentication assessment indicator. Also, aspects receive a transaction authentication decision based in part on the condensed authentication assessment indicator, and process or deny processing of the transaction based on the transaction authentication decision.

Abstract: A device in a data processing system for training machine learning models receives a transaction and forwards it to at least one of a plurality of integrated control action models that use outputs of one model as inputs to other models. The models are machine learning models jointly trained for taking each control action of a plurality of control actions on the transaction to maximize an objective function based on probabilities of the control actions matching corresponding target control actions. The machine learning models include a risk model that outputs risk prediction information for a first control action that indicates whether or not to initiate processing of the transaction. The device further receives the risk prediction information from the risk model, and executes at least the first control action based on the risk prediction information.

Abstract: A device in a data processing system for training machine learning models receives a transaction and forwards it to at least one of a plurality of integrated control action models that use outputs of one model as inputs to other models. The models are machine learning models jointly trained for taking each control action of a plurality of control actions on the transaction to maximize an objective function based on probabilities of the control actions matching corresponding target control actions. The machine learning models include a risk model that outputs risk prediction information for a first control action that indicates whether or not to initiate processing of the transaction. The device further receives the risk prediction information from the risk model, and executes at least the first control action based on the risk prediction information.

Abstract: This disclosure relates to systems and methods of risk detection in an electronic network. The method may include receiving a first portion of session context information for an interaction of an individual over a limited bandwidth network, the first portion including a session identifier for the interaction. The method may include retrieving a second portion of session context information for the interaction over a cloud data pipe using the session identifier, in response to receiving the first portion. The method may include accessing, a data structure representing connected knowledge of the individual. The method may include receiving, via a distributed system, security reputation data including aggregated information from a plurality of members. The method may include analyzing the session context information using the security reputation. The method may include generating a security risk score for the interaction based on the session context information, data structure, and the security reputation data.

Abstract: A method performed on an electronic device for migrating tags across entities. The migration of the tags is performed following an analysis of one or more personal electronically encoded items associated with a previously created perspective or album associated with the previously created perspective, responsive to a user decision the creation of a new perspective, a new album associated with one of the previously created perspectives, or a new perspective and a new album associated with the new perspective, responsive to a user decision to treat the previously created perspective or album as an individual entity, and association of the previously created perspective or album with the new perspective or new album. The tags are respectively migrated from the new perspective or the new album to the associated previously created perspective or the previously created album and to associated ones of the one or more personal electronically encoded items.

Abstract: A method, computing device and computer readable memory for cooperative localization of a portable electronic device is provided. Location identification messages are received each providing a known location of a respective portable electronic device and an associated transmitter identification (ID) of the respective portable electronic device and stored. Location request messages providing one or more transmitter IDs in communication range with a query portable electronic device and a transmitter ID of the query portable electronic device are received and location information from the stored location information associated with the one or more transmitter IDs received in the location request message is retrieved. A location of the query portable electronic device is estimated based on the retrieved location information and stored with the associated transmitter ID of the query portable electronic device.

Abstract: Improved location estimates for transceivers is described. The location estimate of transceivers can be improved for sector transceivers that are co-located at a sectored cell site. The location estimate for each individual co-located sector transceiver can be updated as a centroid of all of the co-located sector transceivers. The location information of the transceivers can be used to provide network location estimation to mobile devices which do not have accurate positioning estimates.

Abstract: Determining a geo-location estimate of a mobile device determined based on detected radio transmitters needs to uniquely identify at least one of the visible cellular towers. The estimate may be improved if multiple cellular towers can be uniquely identified. However, mobile devices may not determine unique identifiers for each visible cellular tower based upon configuration of the cellular radio protocol stack implementation. It is possible to disambiguate non-unique parameters detected at a mobile device to unique IDs of the cellular towers to aid in geo-location. The disambiguation is accomplished using disambiguation information that is associated with the cellular tower the mobile device is currently camped on.

Abstract: Techniques for estimating a location of a portable electronic device are provided. The techniques represent radio scene information detected by a portable electronic device as a vector. The vector may then be used to retrieve similar vectors associated with known locations from a corpus. The known locations may then be used to estimate the location of the portable electronic device.

Abstract: According to one aspect, a method of determining an attitude matrix on a portable electronic device. The method includes determining a first attitude matrix gradient using data from at least one of an accelerometer and a magnetometer, determining a second attitude matrix gradient using data from a gyroscope, fusing the first attitude matrix gradient and the second attitude matrix gradient based on a mixing coefficient to generate a fused gradient, and based on the fused gradient, updating a fine attitude matrix for the portable electronic device.

Abstract: A method, computing device and computer readable memory for cooperative localization of a portable electronic device is provided. Location identification messages are received each providing a known location of a respective portable electronic device and an associated transmitter identification (ID) of the respective portable electronic device and stored. Location request messages providing one or more transmitter IDs in communication range with a query portable electronic device and a transmitter ID of the query portable electronic device are received and location information from the stored location information associated with the one or more transmitter IDs received in the location request message is retrieved. A location of the query portable electronic device is estimated based on the retrieved location information and stored with the associated transmitter ID of the query portable electronic device.

Abstract: A system and method for generating an m-dimensional signature vector with aliasing across synonyms in a computing device is provided. Data representable by a plurality of key-value pairs, each comprising a unique identifier and an associated non-zero value of n-dimensional data is received at the computing device. Elements of the m-dimensional aliased signature vector are generated using synonym information of keys from the plurality of key-value pairs.