Abstract: Methods, apparatus, and systems for predicting and controlling communicable diseases are disclosed. In one example aspect, a method for predicting a communicable disease includes receiving, for each member of a community, multiple data streams associated with the member from multiple sensor devices, and computing, based on a social or locational relationship between the member and other entities in the community and a timeline of activities performed by the member according to the timestamp for each data packet, a list of behavioral indicators for the community indicating a current state of the communicable disease using one or more machine learning models.

Abstract: A method of consolidating Internet of Things (IoT) devices connected via an IoT network is disclosed. An IoT integration platform implemented by a computer system can collect data from one or more of IoT devices, IoT solution specific server systems, third-party server systems, general-purpose user computing devices, or any combination thereof. The IoT integration platform can label the data based on entity-specific context. The entity-specific context can correspond to a user account, a device, a location, or any combination thereof. The IoT integration platform can generate an entity-specific profile based on the labeled data. The IoT integration platform can generate, based on the entity-specific profile, a situation forecast associated with a target entity and with a timeframe yet to occur.

Abstract: A method of consolidating Internet of Things (IoT) devices connected via an IoT network is disclosed. An IoT integration platform implemented by a computer system can collect data from one or more of IoT devices, IoT solution specific server systems, third-party server systems, general-purpose user computing devices, or any combination thereof. The IoT integration platform can label the data based on entity-specific context. The entity-specific context can correspond to a user account, a device, a location, or any combination thereof. The IoT integration platform can generate an entity-specific profile based on the labeled data. The IoT integration platform can generate, based on the entity-specific profile, a situation forecast associated with a target entity and with a timeframe yet to occur.

Abstract: A method of maintaining interoperability amongst Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving a selection of a semantic label associated with an IoT device; determining a recommendation of an interoperable rule based on the semantic label, the interoperable rule having a condition trigger and an action policy for execution at satisfaction of the condition trigger; presenting the recommendation on a rule management interface; and receiving a confirmation from a user through the rule management interface to activate the interoperable rule.

Abstract: A method of profiling a physical environment via Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The physical environment includes users, locations, and devices as well as associations between users, locations, and devices. The method includes: receiving data streams from network-capable devices connected to the IoT integration platform; detecting presence of an entity in a physical environment surrounding or interacting with one or more of the network-capable devices from a subset of the data streams; storing an entity profile on a node graph representing the physical environment, wherein each entity profile is associated at least one of the network-capable device from which the presence is detected; and requesting a semantic label of the entity profile from a user of a first user account via one or more user interfaces.

Abstract: An improved technique identifies risky transactions by mapping raw user location data to a particular cell in a fixed grid. Along these lines, when a user initiates a transaction with a service provider over a mobile device, the service provider collects raw location data such as a latitude and longitude for the user and transmits the location data to an adaptive authentication server. The adaptive authentication server then accesses a fixed set of geographical areas overlaid on a map of the Earth. For example, the geographic areas can correspond to square cells whose corners are defined by selected latitudes and longitudes. The adaptive authentication server finds a particular geographical area which contains the latitude and longitude for the user. Based on an identifier of the particular geographical area, the adaptive authentication server assigns a risk score to the transaction.

Abstract: A method of profiling a physical environment via Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving data streams from network-capable devices connected to the IoT integration platform; detecting presence of an entity in a physical environment surrounding or interacting with one or more of the network-capable devices from a subset of the data streams; storing an entity profile on a node graph representing the physical environment, wherein each entity profile is associated at least one of the network-capable device from which the presence is detected; and requesting a semantic label of the entity profile from a user of a first user account via one or more user interfaces.

Abstract: A method of maintaining interoperability amongst Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving a selection of a semantic label associated with an IoT device; determining a recommendation of an interoperable rule based on the semantic label, the interoperable rule having a condition trigger and an action policy for execution at satisfaction of the condition trigger; presenting the recommendation on a rule management interface; and receiving a confirmation from a user through the rule management interface to activate the interoperable rule.

Abstract: A method of profiling a physical environment via Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The physical environment includes users, locations, and devices as well as associations between users, locations, and devices. The method includes: receiving data streams from network-capable devices connected to the IoT integration platform; detecting presence of an entity in a physical environment surrounding or interacting with one or more of the network-capable devices from a subset of the data streams; storing an entity profile on a node graph representing the physical environment, wherein each entity profile is associated at least one of the network-capable device from which the presence is detected; and requesting a semantic label of the entity profile from a user of a first user account via one or more user interfaces.

Abstract: A method of maintaining interoperability amongst Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving a selection of a semantic label associated with an IoT device; determining a recommendation of an interoperable rule based on the semantic label, the interoperable rule having a condition trigger and an action policy for execution at satisfaction of the condition trigger; presenting the recommendation on a rule management interface; and receiving a confirmation from a user through the rule management interface to activate the interoperable rule.

Abstract: A technique provides malicious identity profiles. The technique involves storing unsuccessful authentication entries in a database, the unsuccessful authentication entries including (i) descriptions of failed attempts to authenticate users and (ii) biometric records captured from the users during the failed attempts to authenticate the users. The technique further involves generating a set of malicious identity profiles based on the descriptions and the biometric records of the unsuccessful authentication entries stored in the database. Each malicious identity profile includes a profile biometric record for comparison with new biometric records during new authentication attempts. The technique further involves outputting the set of malicious identity profiles. Such a set of malicious identity profiles is well suited for use in future authentication operations, i.e., well suited for predicting intruder attacks and fraud attempts, and for sharing risky identities among authentication systems (e.g.

Abstract: A method of consolidating Internet of Things (IoT) devices connected via an IoT network is disclosed. An IoT integration platform implemented by a computer system can collect data from one or more of IoT devices, IoT solution specific server systems, third-party server systems, general-purpose user computing devices, or any combination thereof. The IoT integration platform can label the data based on entity-specific context. The entity-specific context can correspond to a user account, a device, a location, or any combination thereof. The IoT integration platform can generate an entity-specific profile based on the labeled data. The IoT integration platform can generate, based on the entity-specific profile, a situation forecast associated with a target entity and with a timeframe yet to occur.

Abstract: A method of consolidating Internet of Things (IoT) devices connected via an IoT network is disclosed. The method includes extracting a first data record from a data source connected to the IoT integration platform; analyzing the first data record to generate a derivative record relevant to a user context; aggregating the first data record and the derivative record to a contextually grouped data cluster; and presenting the derivative record on an integration interface along with other data records in the data cluster.

Abstract: An authentication technique involves obtaining, by processing circuitry, a set of suitability factors from a user device of a user. The authentication technique further involves performing, based on the set of suitability factors and by the processing circuitry, a selection operation which selects a set of suitable biometric methods to apply during authentication from available biometric methods which are available to the processing circuitry for use in authentication. The authentication technique further involves applying, after the set of suitable biometric methods is selected and by the processing circuitry, the set of suitable biometric methods during an authentication operation to determine whether the user is authentic. Accordingly, poorly suited biometric methods can be ruled out (i.e., made unavailable for use by authentication).

Abstract: Authentication systems are provided that select an authentication method to be applied to a given transaction from among a plurality of available authentication methods based on risk reasoning. An authentication request from an authentication requestor for a given transaction is processed by receiving the authentication request from the authentication requester and selecting an authentication method to be applied to the given transaction from among a plurality of available authentication methods based on an evaluation of one or more predefined risk reasons with respect to the available authentication methods. The predefined risk reasons associated with a given transaction comprise, for example, a set of risk reasons that contribute to a risk score that has been assigned to the given transaction. The evaluation may employ one or more of rule-based, heuristic and Bayesian techniques.

Abstract: A technique is described that determines if a request for authentication is made on the mobile device belonging to the authorized user by examining non confidential memory parameters of the mobile device, for example a total free memory, or a number of stored phone numbers. The technique examines past authorized user values for the memory parameters and performs a statistical analysis and projects a current memory range for each of the parameters for the authorized user. The projection may include factors such as the amount of time elapsed since the mobile device was acquired, the normal variation over a day, a week, a month or a year, and cyclic variations such as many new applications during a specific month each year. The projection may also include baseline variations which may be provided by analysis of a large number of different people. If the device used for the authorization request has memory parameters different from the projected range of authorized user values, then authorization may be refused.

Abstract: A method of maintaining interoperability amongst Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving a selection of a semantic label associated with an IoT device; determining a recommendation of an interoperable rule based on the semantic label, the interoperable rule having a condition trigger and an action policy for execution at satisfaction of the condition trigger; presenting the recommendation on a rule management interface; and receiving a confirmation from a user through the rule management interface to activate the interoperable rule.

Abstract: A method of consolidating Internet of Things (IoT) devices connected via an IoT network is disclosed. The method includes extracting a first data record from a data source connected to the IoT integration platform; analyzing the first data record to generate a derivative record relevant to a user context; aggregating the first data record and the derivative record to a contextually grouped data cluster; and presenting the derivative record on an integration interface along with other data records in the data cluster.

Abstract: A method of profiling a physical environment via Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving data streams from network-capable devices connected to the IoT integration platform; detecting presence of an entity in a physical environment surrounding or interacting with one or more of the network-capable devices from a subset of the data streams; storing an entity profile on a node graph representing the physical environment, wherein each entity profile is associated at least one of the network-capable device from which the presence is detected; and requesting a semantic label of the entity profile from a user of a first user account via one or more user interfaces.

Abstract: An improved technique tracks errors in collecting geolocation data associated with a transaction. Along these lines, an adaptive authentication engine stores information indicative of a failure to collect geolocation data associated with the transaction. In particular, this information takes the form of a geolocation collection state; the adaptive authentication engine stores such a state in a field of a database that contains historical transaction information. If a service provider failed to collect geolocation information for a transaction, the adaptive authentication engine stores a “Fail” value in the geolocation collection state field of the database entry associated with the transaction. Adaptive authentication techniques may then correlate such “Fail” values with other field values such as time of submission and device type. The result of such a correlation is to build a risk model based on geolocation collection error which the risk engine may then use to compute risk score.