Abstract: An AI firewall engine dynamically manages firewall ports of an enterprise network to increase security. The AI firewall engine may begin with a baseline port profile configuration and then add firewall rules derived from natural language processing and machine learning from vendor recommended port requirements for an application. The AI firewall engine builds a dynamic port profile with rules that are applied to the firewalls. The AI firewall engine may then monitor system changes and dynamically updates the port profile and configurations on the firewalls.

Abstract: Provided is a method, computer program product, and system for performing automated failover and/or failback recovery analysis using predictive analytics. A processor may monitor a disaster recovery (DR) life cycle during a DR scenario. The processor may monitor failover process activities in a DR production environment over a predetermined time period. Based on data collected during monitoring of the DR life cycle and the failover process activities in the DR production environment over the predetermined time period, the processor may generate, using machine learning, a failback blueprint plan to move production to a new production environment.

Abstract: Provided is a method, computer program product, and system for performing automated failover and/or failback recovery analysis using predictive analytics. A processor may monitor a disaster recovery (DR) life cycle during a DR scenario. The processor may monitor failover process activities in a DR production environment over a predetermined time period. Based on data collected during monitoring of the DR life cycle and the failover process activities in the DR production environment over the predetermined time period, the processor may generate, using machine learning, a failback blueprint plan to move production to a new production environment.

Abstract: Systems, methods, and computer program products providing network security leveraging analytics and physical separation between computer systems and a network to prevent threats from infecting network devices. A specialized pluggable dongle like security device is inserted between ports of computer system(s) connecting to the network and port(s) of network hardware facilitating connections between the computer system and computer network. The security device uses a combination of onboard analytics and cloud-based analytic services to detect incoming threats from network traffic and whether to allow network traffic to pass through the security device and/or prevent network traffic from entering the computer system.

Abstract: Manage a request for a computing service through a hub solution available on a network. The underlying network fabric is the communication bus between individual processes that make up a service request. A process orchestrator may publish an Internet Protocol (IP) address for service requests such as printing services, email services, Active Directory (AD) services and similar service requests. The process orchestrator may determine which processes are to be executed to complete the service request and offload the processes to an available computing resources on the network. Examples of computing resources for each process include a virtual machine and a hardware based process engine. The process orchestrator may manage the processes and act as the primary point of interface for an endpoint host requesting the service.

Abstract: An approach is provided for providing disaster recovery, active/active and active/standby workload allocation in a networked computing environment according to aspects of the present invention. Risk factor data is obtained for each component of a plurality of components in a global data center. A resiliency score is calculated for each component of the plurality of components based on a set of risk factors that are applicable to the component gathered from the risk factor data. A set of group resiliency scores are computed by aggregating the resiliency scores for each of the plurality of components included in a component group. In response to a determination that an application's performance can be improved, a datacenter is selected for failover protection based on a group resiliency score corresponding to the datacenter. Moreover, the overall enterprise resiliency score can be improved by moving an application between sites in the enterprise.

Abstract: An AI firewall engine dynamically manages firewall ports of an enterprise network to increase security. The AI firewall engine may begin with a baseline port profile configuration and then add firewall rules derived from natural language processing and machine learning from vendor recommended port requirements for an application. The AI firewall engine builds a dynamic port profile with rules that are applied to the firewalls. The AI firewall engine may then monitor system changes and dynamically updates the port profile and configurations on the firewalls.

Abstract: A method for dynamically modifying quality-of-service tags for multiple data flows is disclosed. In one embodiment, such a method determines current bandwidth utilization for each of multiple data flows passing through a network, and determines acceptable bandwidth utilization for each of the multiple data flows. The method receives external information that, based on one or more rules, is used to adjust quality of service priorities for one or more of the data flows. Based on the external information, the method dynamically adjusts quality-of-service tags for data packets associated with the data flows, such that current bandwidth utilization is altered for at least one data flow of the multiple data flows without violating acceptable bandwidth utilization for each of the multiple data flows. A corresponding system and computer program product are also disclosed.

Abstract: An approach is provided for providing disaster recovery, active/active and active/standby workload allocation in a networked computing environment according to aspects of the present invention. Risk factor data is obtained for each component of a plurality of components in a global data center. A resiliency score is calculated for each component of the plurality of components based on a set of risk factors that are applicable to the component gathered from the risk factor data. A set of group resiliency scores are computed by aggregating the resiliency scores for each of the plurality of components included in a component group. In response to a determination that an application's performance can be improved, a datacenter is selected for failover protection based on a group resiliency score corresponding to the datacenter. Moreover, the overall enterprise resiliency score can be improved by moving an application between sites in the enterprise.

Abstract: Systems, methods, and computer program products providing network security leveraging analytics and physical separation between computer systems and a network to prevent threats from infecting network devices. A specialized pluggable dongle like security device is inserted between ports of computer system(s) connecting to the network and port(s) of network hardware facilitating connections between the computer system and computer network. The security device uses a combination of onboard analytics and cloud-based analytic services to detect incoming threats from network traffic and whether to allow network traffic to pass through the security device and/or prevent network traffic from entering the computer system.

Abstract: Embodiments for managing drones by one or more processors are described. A condition related to the operation of a drone in a selected area is detected. A set of drone operating parameters associated with the operation of the drone in the selected area is changed based on the detecting of the condition. A signal representative of the changing of the set of drone operating parameters is generated.

Abstract: Manage a request for a computing service through a hub solution available on a network. The underlying network fabric is the communication bus between individual processes that make up a service request. A process orchestrator may publish an Internet Protocol (IP) address for service requests such as printing services, email services, Active Directory (AD) services and similar service requests. The process orchestrator may determine which processes are to be executed to complete the service request and offload the processes to an available computing resources on the network. Examples of computing resources for each process include a virtual machine and a hardware based process engine. The process orchestrator may manage the processes and act as the primary point of interface for an endpoint host requesting the service.

Abstract: Embodiments for managing drones by one or more processors are described. A condition related to the operation of a drone in a selected area is detected. A set of drone operating parameters associated with the operation of the drone in the selected area is changed based on the detecting of the condition. A signal representative of the changing of the set of drone operating parameters is generated.

Abstract: A system and method to predict future legislation using sentiment and analytics. The method includes capturing analytics based on factors that drive a new piece of legislation such that a voting prediction can be determined. The method applies analytics across a large population of politicians (e.g., Senate, House of Representatives) for predetermining how legislation will pass or fail. The method performs: generating a sentiment score, a sentiment momentum value for a topic; generating a correlation between a new legislation topic and previous associated topics and their outcomes; generating a sentiment score and a sentiment momentum of politicians to vote on the new legislation; generating a correlation between a politician's likely vote on new legislation based on previous voting record for that politician; and using analytics to correlate between sentiment and voting correlations between topics and politicians and predict a potential vote of a politician on a given legislative topic.

Abstract: An article of manufacture includes a substrate, a first patterned layer deposited on the substrate in a first region, and a second patterned layer deposited on the substrate in a second region. The first patterned layer encodes first information in first symbols that are detectable by an optical sensor. The second patterned layer encodes second information in second symbols that are detectable by a non-optical sensor. The second information is distinct from the first information and the second region at least partially overlaps the first region.

Abstract: An article of manufacture includes a substrate, a first patterned layer deposited on the substrate in a first region, and a second patterned layer deposited on the substrate in a second region. The first patterned layer encodes first information in first symbols that are detectable by an optical sensor. The second patterned layer encodes second information in second symbols that are detectable by a non-optical sensor. The second information is distinct from the first information and the second region at least partially overlaps the first region.

Abstract: An article of manufacture includes a substrate, a first patterned layer deposited on the substrate in a first region, and a second patterned layer deposited on the substrate in a second region. The first patterned layer encodes first information in first symbols that are detectable by an optical sensor. The second patterned layer encodes second information in second symbols that are detectable by a non-optical sensor. The second information is distinct from the first information and the second region at least partially overlaps the first region.

Abstract: An article of manufacture includes a substrate, a first patterned layer deposited on the substrate in a first region, and a second patterned layer deposited on the substrate in a second region. The first patterned layer encodes first information in first symbols that are detectable by an optical sensor. The second patterned layer encodes second information in second symbols that are detectable by a non-optical sensor. The second information is distinct from the first information and the second region at least partially overlaps the first region.

Abstract: Detecting crowds is provided. A location is selected in a set of locations a user of a client device wants to go to based on data within a profile associated with the user. A set of data inputs is monitored to determine a number of people currently at the selected location. Then, in response to determining that the number of people currently at the selected location is not greater than a user-defined threshold level of people for the selected location, a mapped route to the selected location is sent to the client device of the user.

Abstract: Detecting crowds is provided. A location is selected in a set of locations a user of a client device wants to go to based on data within a profile associated with the user. A set of data inputs is monitored to determine a number of people currently at the selected location. Then, in response to determining that the number of people currently at the selected location is not greater than a user-defined threshold level of people for the selected location, a mapped route to the selected location is sent to the client device of the user.