Abstract: A computer-implemented method of obfuscating communication traffic patterns may include detecting, at a first communications device, data communication sessions with a second communications device via the computer server using a network protocol. At the first device, a first traffic pattern is accessed based on the data communication sessions over a first predefined time period. At the first communications device, a second traffic pattern is accessed based on the data communication sessions over a second predefined time period that occurs after the first predefined time period. At the first communications device, based on a randomization process, a dummy data communication pattern is generated for transmission to the second communication devices, whereby the dummy data communication pattern is appended to the second traffic pattern for obfuscating a traffic pattern change between the first and the second traffic pattern at the computer server used to establish the communication sessions.

Abstract: A method of automatic security parameter renewal includes determining if the security parameter satisfies a renewal condition, the determining including automatically detecting a time when a security parameter is going to expire, and automatically updating the security parameter when the renewal condition is satisfied. The automatically updating the security parameter includes modifying a certificate upon receipt of a new certificate.

Abstract: Virtual machines (VMs) and a social networking graph where relationships between VM nodes are based on communications between VM nodes. VMs using social networking graphs to help manage a set of VMs. A system where a VM uses a social networking graph to query other VMs to query regarding “health” issues, problem solutions and/or performance improvements.

Abstract: Disclosed is a system, computer program product, and method for provisioning a new service request. The computer-implemented method begins with receiving a new service request for computational resources in a computing system. The required computational resources are memory usage, storage usage, processor usage, or a combination thereof to fulfill the new service request. Next a sandbox computing environment is used to operate the new service request. The sandbox computing environment is used to isolate the computing system. The sandbox computing environment produces a current computational resources usage data to fulfill the new service request in the sandbox computing environment. The current sandbox computational resources usage data and historical computational resources usage data are both used by a machine learning module to create a prediction of the computational resources that will be required in the computing system to fulfill the new service request.

Abstract: A computer-implemented method, system, and/or computer program product automatically provides spatial separation between a self-driving vehicle (SDV) operating in an autonomous mode and another vehicle on a roadway. One or more processors receive an emotional state descriptor for at least one occupant of the SDV and determine an emotional state of the occupant(s) of the SDV. A vehicle detector on the SDV detects another vehicle and the size of the other vehicle within a predefined proximity of the SDV. A control mechanisms controller determines that a field of view for the occupants in the SDV is blocked by the size of the other vehicle. The processor(s) issue spatial separation instructions to the control mechanisms controller on the SDV to adjust a spacing between the SDV and the other vehicle based on the emotional state descriptor for the occupant(s) in the SDV and the field of view for the occupant(s) in the SDV that is blocked by the size of the other vehicle.

Abstract: Embodiments of the present invention provide systems and methods for thwarting attempts at the unauthorized access to the restricted resources within the target server in a multi-node system. Real-time detection of the user ID and thread ID associated with attempts to access the restricted resources within the target server in a multi-node system is achieved by analyzing causality, message queue, and event-driven patterns.

Abstract: A computer-implemented method of obfuscating communication traffic patterns may include detecting, at a first communications device, data communication sessions with a second communications device via the computer server using a network protocol. At the first device, a first traffic pattern is accessed based on the data communication sessions over a first predefined time period. At the first communications device, a second traffic pattern is accessed based on the data communication sessions over a second predefined time period that occurs after the first predefined time period. At the first communications device, based on a randomization process, a dummy data communication pattern is generated for transmission to the second communication devices, whereby the dummy data communication pattern is appended to the second traffic pattern for obfuscating a traffic pattern change between the first and the second traffic pattern at the computer server used to establish the communication sessions.

Abstract: A system, method and program product for providing cognitive behavior security control (CBSC). A system is disclosed that includes: a repository having a plurality of challenges each including an interactive graphical task; a user interface for graphically presenting challenges to users; an enrollment system for assigning challenges to users and determining an authentic response for each user; an authentication system that collects an observed response from a user presented with an assigned challenge and determines a security control result based on a closeness of the observed response with the authentic response of the user.

Abstract: One embodiment provides a method for ensuring device security via swipe pattern recognition, the method comprising: utilizing at least one processor to execute computer code that performs the steps of: receiving, using a touch device, at least one swipe input of a user; determining, using the at least one processor, if the at least one swipe input matches a known swipe pattern of the user, the match requiring exceeding a match confidence level; and responsive to said determining, executing an action associated with the touch device. Other aspects are described and claimed.

Abstract: A method, computer system, and/or computer program product dynamically adjusts an insurance policy parameter for a self-driving vehicle (SDV) operating in manual mode. One or more processors receive a copy of manual control signals from an SDV, where the SDV is in manual mode during a particular time period. The processor(s) also receive a copy of computer control signals generated by an SDV on-board computer on the SDV during the particular time period, and compare the manual control signals to the computer control signals. In response to the manual control signals matching the computer control signals within a predetermined range, the processor(s) adjust an insurance policy parameter for the SDV while the SDV is being controlled by the particular human operator.

Abstract: A computer-implemented method of obfuscating communication traffic patterns may include detecting, at a first communications device, data communication sessions with a second communications device via the computer server using a network protocol. At the first device, a first traffic pattern is accessed based on the data communication sessions over a first predefined time period. At the first communications device, a second traffic pattern is accessed based on the data communication sessions over a second predefined time period that occurs after the first predefined time period. At the first communications device, based on a randomization process, a dummy data communication pattern is generated for transmission to the second communication devices, whereby the dummy data communication pattern is appended to the second traffic pattern for obfuscating a traffic pattern change between the first and the second traffic pattern at the computer server used to establish the communication sessions.

Abstract: A computer-implemented method, system, and/or computer program product automatically provides spatial separation between a self-driving vehicle (SDV) operating in an autonomous mode and another vehicle on a roadway. One or more processors receive an emotional state descriptor for at least one occupant of the SDV and determine an emotional state of the occupant(s) of the SDV. A vehicle detector on the SDV detects another vehicle within a predefined proximity of the SDV. The processor(s) determine the braking abilities of the SDV and issue spatial separation instructions to a control mechanisms controller on the SDV to adjust a spacing between the SDV and the other vehicle based on the emotional state of the occupant(s) in the SDV.

Abstract: A method, system, and/or computer program product controls movement and adjusts operations of an aerial drone. A drone camera observes an aerial maneuver physical gesture by a user. The aerial drone then performs an aerial maneuver that correlates to the aerial maneuver physical gesture. The drone camera observes the user performing a physical action. One or more processors associate the physical action with a particular type of activity. A drone on-board computer adjusts an operation of an aerial drone based on the particular type of activity.

Abstract: Embodiments of the invention are directed to a computer-implemented method for monitoring game activity of a game system. A non-limiting example of the method includes monitoring, by a processing device, game activity of the game system. The processing device determines characteristics of the game activity, along with expected characteristics of the game activity. The processing device analyzes the characteristics of the game activity and the expected characteristics of the game activity. Based at least in part on analyzing the characteristics of the game activity and the expected characteristics of the game activity, an entity that is controlling the game system is determined.

Abstract: Embodiments of the invention are directed to a computer-implemented method for monitoring game activity of a game system. A non-limiting example of the method includes monitoring, by a processing device, game activity of the game system. The processing device determines characteristics of the game activity, along with expected characteristics of the game activity. The processing device analyzes the characteristics of the game activity and the expected characteristics of the game activity. Based at least in part on analyzing the characteristics of the game activity and the expected characteristics of the game activity, an entity that is controlling the game system is determined.

Abstract: A method reduces a risk exposure to an item being transported by a self-driving vehicle (SDV). One or more processors determine a risk-level R for contents of a smart vault that is being transported by the SDV, where R describes a real-time risk of the contents being stolen from the smart vault while being transported by the SDV. In response to determining that R is greater than a predefined risk value, one or more processors electronically communicate an executable instruction to a SDV on-board computer to take a risk-lowering action that will reduce the level of R.

Abstract: A context-sensitive soundscape is generated by receiving a first identifier for identifying a target cognitive state for a user, and a second identifier for identifying a user cohort for the user. A present context is determined for the user. A machine-learning procedure is performed to map the target cognitive state to a set of audio output characteristics based upon the identified user cohort and the determined present context. An audio output is generated to create the context-sensitive soundscape that includes the set of audio output characteristics.

Abstract: A vehicular alert system includes an autonomous aerial vehicle and a central computer. The autonomous aerial vehicle includes a processor, a display, and a detector. The processor controls a data transceiver. The detector detects one or more vehicular condition. The central computer communicates with the autonomous aerial vehicle via the data transceiver. The central computer includes a memory device. The memory device stores vehicular condition data and road condition data. The central computer communicates one of a vehicular condition or a road condition to the autonomous aerial vehicle. The processor of the autonomous aerial vehicle displays the received condition on the display.

Abstract: Generating an attack graph to protect sensitive data objects from attack is provided. The attack graph that includes nodes representing components in a set of components of a regulated service and edges between nodes representing relationships between related components in the set of components is generated based on vulnerability and risk metrics corresponding to each component. A risk score is calculated for each component represented by a node in the attack graph based on sensitivity rank and criticality rank corresponding to each respective component. Risk scores are aggregated for each component along each edge path connecting a node of a particular component to a node of a related component. In response to determining that an aggregated risk score of a component is greater than or equal to a risk threshold, an action is performed to mitigate a risk to sensitive data corresponding to the component posed by an attack.

Abstract: A hearing aid method, system, and non-transitory computer readable medium, include a cognitive state analysis circuit configured to analyze a cognitive state of a user, a context analysis circuit configured to analyze a context of the user, and an audio characteristic controller configures to control an audio characteristic of a hearing aid based on a joint assessment of the cognitive state of the user and the context of the user.