Abstract: Methods and systems are disclosed for encoding and decoding data from genetic traits. In one embodiment, the invention provides a method of encoding data from genetic traits. The method comprises encoding genetic traits information, including using quantum dot wavelengths to identify distinct genetic traits, and using numbers of the quantum dots to represent probabilities associated with the traits. In an embodiment, the invention provides a genetic characteristics decoding system for decoding genetic information encoded using quantum dots in a carrier. The decoding system comprises a light source for charging the quantum dots in the carrier; a scanner for scanning the carrier to retrieve information from the charged quantum dots; and a processing system for processing the retrieved information to determine quantum dot wavelengths to identify distinct genetic traits, and to determine numbers of the quantum dots to identify probabilities associated with the genetic traits.

Abstract: An object approaching a wearable device of a user is identified. In response to determining that the approaching object is a previously identified target of the user, one or more applications displayed in a user interface of the wearable device, and how said one or more applications are organized on the user interface of the wearable device, are modified based on the identified approaching object. The modified user interface is displayed to the user.

Abstract: In an approach, a processor receives from a network device a request. A processor obtains from a database a device profile for the network device. A processor determines whether the device profile of the network device has a data usage pattern related to data identified by a data identifier. In response to determining the device profile has a related data usage pattern, a processor receives the related data usage pattern from the database. In response to determining the device profile does not have a related data usage pattern, a processor obtains a device type profile from the database. A processor classifies the data usage request based on at least one of the device profile and the device type profile. A processor executes a security action based on the classification of the data usage request. A processor stores the data usage request and executed security action to the database.

Abstract: In an approach to automatic device enrollment in an IoT network, responsive to receiving a request to add a new device to an IoT network, device metadata is requested from the new device. Responsive to receiving the device metadata, the device metadata is confirmed with the device manufacturer using secure information services. Responsive to confirming the device metadata with the device manufacturer, configuration data for the new device is gathered from a repository, where the configuration data is gathered from devices with a same context type in the repository. Responsive to gathering the configuration data for the new device from the repository, the new device is enrolled in the IoT network using the configuration data.

Abstract: An object approaching a wearable device of a user is identified. In response to determining that the approaching object is a previously identified target of the user, one or more applications displayed in a user interface of the wearable device, and how said one or more applications are organized on the user interface of the wearable device, are modified based on the identified approaching object. The modified user interface is displayed to the user.

Abstract: The disclosure describes techniques for generating device recommendations. The techniques include registering a plurality of Internet of Things (IoT) devices in a social IoT network, where each device performs one or more tasks and the one or more tasks include a first task. The techniques include periodically receiving, with the social IoT network, a work profile from one or more of the registered devices. The work profile includes device information associated with the one or more device tasks performed by the respective registered device. The techniques include grouping devices performing the first task into groups of similar devices, identifying, based on the device information in the work profile received from one or more of the registered devices, at least one device from the group of devices for which recommendations are to be provided, generating the recommendations for the identified device, and providing the recommendations for the identified device.

Abstract: Embodiments are disclosed for preventing network attacks. The techniques include generating a usage profile for a computing device that accesses a network. The techniques also include determining a plurality of actual use real-time indicators for a network connection on the network. The techniques further include determining a plurality of expected use real-time indicators for the network connection. Additionally, the techniques include calculating a risk assessment value for the network connection based on the actual use real-time indicators and the expected use real-time indicators. Further, the techniques include performing a security action for the network connection based on the calculated risk assessment value.

Abstract: A method and system for improving shared hardware and software resource system is provided. The method includes detecting and registering an Internet of things (IOT) device connected to a network. Hardware/software resources and sensors associated with hardware and software operations executed by the IOT device are identified and all available data and associated metadata associated with the hardware/software resources and the sensors are stored in a database. Additional available hardware/software resources and sensors associated with a plurality of IOT devices connected to the network are displayed and a command signal for assigning a specified hardware/software resource or sensor to the IOT device is executed. A network identification code associated with a location of the specified hardware/software resource or sensor is retrieved and enabled with respect to said IOT device.

Abstract: A method and system of dynamically generating computerized dialog. Natural language input previously from a user and cognitive context are analyzed. A dictionary is selected as a function of the natural language input and stored information previously known about the user. A corpus including knowledge of the topics of interest is further selected. One or more expressions are extracted from a network accessible data source. The one or more expressions extracted from the network accessible data source are filtered through the dictionary and the corpus. Dialog is generated in response to the natural language input, as a function of the cognitive context and topic of interest by integrating the one or more expressions filtered through the dictionary and corpus.

Abstract: The disclosure describes techniques for generating device recommendations. The techniques include registering a plurality of Internet of Things (IoT) devices in a social IoT network, where each device performs one or more tasks and the one or more tasks include a first task. The techniques include periodically receiving, with the social IoT network, a work profile from one or more of the registered devices. The work profile includes device information associated with the one or more device tasks performed by the respective registered device. The techniques include grouping devices performing the first task into groups of similar devices, identifying, based on the device information in the work profile received from one or more of the registered devices, at least one device from the group of devices for which recommendations are to be provided, generating the recommendations for the identified device, and providing the recommendations for the identified device.

Abstract: Aspects of the present disclosure relate to identifying a driving mode of an autonomous vehicle. A driving mode of an autonomous vehicle is determined by one or more processing circuits of the autonomous vehicle, the driving mode representing an amount of autonomy of the autonomous vehicle at a particular time. A request for the driving mode of the autonomous vehicle is received from a requesting device. The driving mode is then transmitted to the requesting device.

Abstract: Embodiments are disclosed for preventing network attacks. The techniques include generating a usage profile for a computing device that accesses a network. The techniques also include determining a plurality of actual use real-time indicators for a network connection on the network. The techniques further include determining a plurality of expected use real-time indicators for the network connection. Additionally, the techniques include calculating a risk assessment value for the network connection based on the actual use real-time indicators and the expected use real-time indicators. Further, the techniques include performing a security action for the network connection based on the calculated risk assessment value.

Abstract: In an approach, a processor receives from a network device a request. A processor obtains from a database a device profile for the network device. A processor determines whether the device profile of the network device has a data usage pattern related to data identified by a data identifier. In response to determining the device profile has a related data usage pattern, a processor receives the related data usage pattern from the database. In response to determining the device profile does not have a related data usage pattern, a processor obtains a device type profile from the database. A processor classifies the data usage request based on at least one of the device profile and the device type profile. A processor executes a security action based on the classification of the data usage request. A processor stores the data usage request and executed security action to the database.

Abstract: Aspects of the present disclosure relate to identifying a driving mode of an autonomous vehicle. A driving mode of an autonomous vehicle is determined by one or more processing circuits of the autonomous vehicle, the driving mode representing an amount of autonomy of the autonomous vehicle at a particular time. A request for the driving mode of the autonomous vehicle is received from a requesting device. The driving mode is then transmitted to the requesting device.

Abstract: Data indicating current driving characteristics of a driver driving a vehicle can be received in real time. A driving profile for the driver can be determined based on the data. The driving profile can be categorized into a driving pattern category. A plurality of candidate travel routes for the driver to reach an intended destination can be identified and, for each of the candidate travel routes, a plurality of route segments can be identified. Based on the driving pattern category, a probability that the current driving characteristics of the driver will cause a traffic accident can be determined for each of the plurality of route segments. Route segments for which the probability that the current driving characteristics of the driver will cause the traffic accident exceeds a threshold value can be determined. A notification can be communicated to the driver or vehicle indicating such probability.

Abstract: A method and system for improving shared hardware and software resource system is provided. The method includes detecting and registering an Internet of things (IOT) device connected to a network. Hardware/software resources and sensors associated with hardware and software operations executed by the IOT device are identified and all available data and associated metadata associated with the hardware/software resources and the sensors are stored in a database. Additional available hardware/software resources and sensors associated with a plurality of IOT devices connected to the network are displayed and a command signal for assigning a specified hardware/software resource or sensor to the IOT device is executed. A network identification code associated with a location of the specified hardware/software resource or sensor is retrieved and enabled with respect to said IOT device.

Abstract: Systems, methods and platforms for generating and improving conversational dialogs between a computer system and a user to create more intelligent, realistic human-like conversations. The systems, methods and platforms achieve a realistic human conversation by identify parameters such as the user's culture, age and known interests, identify a corpus that contains the knowledge appropriate for achieving conversational goals to a perceived topic of interest and generate expressions into dialog that may be extracted from human generated sources. The system appropriately matches the targeted user's parameters and topic based on the input of the user initiating the dialog interaction. The system may analyze and/or record the emotion of the user, cognitive context, gestures and the user's expressions, which may be performed using one or more recording systems to increase the accuracy of topic identification and the appropriate dialog responses.

Abstract: A method and system for improving shared hardware and software resource system is provided. The method includes detecting and registering an Internet of things (IOT) device connected to a network. Hardware/software resources and sensors associated with hardware and software operations executed by the IOT device are identified and all available data and associated metadata associated with the hardware/software resources and the sensors are stored in a database. Additional available hardware/software resources and sensors associated with a plurality of IOT devices connected to the network are displayed and a command signal for assigning a specified hardware/software resource or sensor to the IOT device is executed. A network identification code associated with a location of the specified hardware/software resource or sensor is retrieved and enabled with respect to said IOT device.

Abstract: A method and system or dynamically generating computerized dialog. oth natural language input previously from a user and cognitive context are analyzed. A dictionary is selected as a function of the natural language input and stored information previously known about the user. A corpus including knowledge of the topics of interest is further selected. One or more expressions are extracted from a network accessible data source. The one or more expressions extracted from the network accessible data source are filtered through the dictionary and the corpus. Dialog is generated in response to the natural language input, as a function of the cognitive context and topic of interest by integrating the one or more expressions filtered through the dictionary and corpus.

Abstract: A method and system for extracting information from a surface coated with a coating containing quantum dots are disclosed. In embodiments, the method comprises charging the quantum dots in the surface coating, scanning the surface to retrieve information from the quantum dots, and processing the retrieved information to identify data encoded in the quantum dots. In embodiments of the invention, the processing includes filtering the retrieved information to adjust the received information based on defined effects of the coating. In embodiments of the invention, the filtering includes filtering the retrieved information to account for chromatic deviation due to the color of the coated surface. In embodiments of the invention, the quantum dots include a plurality of different types of quantum dots, and the processing the retrieved information includes processing the retrieved information to distinguish between the information retrieved from the different types of quantum dots.