Abstract: A method establishes a session between a network service and a user device used by the user having a particular sociometric identity. One or more processors identify an interaction between a user and one or more provider entities. The processor(s) identify profiles for the one or more provider entities, where each profild of the one or more provider entities describes a type of service provided by a respective provider entity of the one or more provider entities, and compute a sociometric identity of the user based on the profiles of the one or more provider entities with which the user has had an interaction. One or more processors transmit the sociometric identity to a network service in order to establish a session between the network service and a user device used by the user having the sociometric identity.

Abstract: A method, system, and non-transitory compute readable medium for a fraud detection including a calendar reading device configured to read calendar data of a calendar for a user, a purchase detection device configured to detect an attempted purchase using a credit-card of the user, and a risk detection device configured to detect fraud by calculating a risk based on the calendar data and data related to the attempted purchase.

Abstract: Mechanisms are provided for implementing a conversation monitoring system. The conversation monitoring system monitors a conversation between at least two participants and extracting, by the conversation monitoring system, key terms present in communications between the at least two participants. The conversation monitoring system generates a provenance graph data structure based on the extraction of the key terms where the provenance graph data structure has speaker nodes representing the at least two participants, term nodes representing the key terms present in the communications, and edges connecting nodes in the provenance graph. The conversation monitoring system analyzes the provenance graph data structure to identify a relative ranking of the key terms within the conversation and generates an output representing content of the conversation based on the relative ranking of the key terms.

Abstract: Mechanisms are provided for implementing a conversation monitoring system. The conversation monitoring system monitors a conversation between at least two participants and extracting, by the conversation monitoring system, key terms present in communications between the at least two participants. The conversation monitoring system generates a provenance graph data structure based on the extraction of the key terms where the provenance graph data structure has speaker nodes representing the at least two participants, term nodes representing the key terms present in the communications, and edges connecting nodes in the provenance graph. The conversation monitoring system analyzes the provenance graph data structure to identify a relative ranking of the key terms within the conversation and generates an output representing content of the conversation based on the relative ranking of the key terms.

Abstract: A computer-implemented method sanitizes memory in a cloud environment. One or more processors in a computer receive a hypercall resulting from a call from an application running in a computer. The hypercall is to a hypervisor that manages a virtual memory. The hypercall directs the hypervisor to sanitize data in the virtual memory, where sanitizing the data applies a data remanence policy that prevents remanence data in the virtual memory from being accessed by an unauthorized user. In response to receiving the hypercall, one or more processors sanitize the data in the virtual memory that is allocated for use by the application.

Abstract: A computer-implemented method generates a random number in a cloud-based random number server. The cloud-based random number server identifies multiple entropy sources. The cloud-based random number server identifies multiple disjointed entropy sources from the multiple entropy sources, which are logically and functionally independent of one another. The cloud-based random number server randomly selects multiple disparate entropy sources from the multiple disjointed entropy sources, and then receives multiple entropic values from the multiple disparate entropy sources, where each of the multiple disparate entropy sources supplies an entropic value that describes a type of entropic event not found in other entropy sources from the multiple disparate entropy sources. The cloud-based random number server mixes the multiple entropic values to create a combined entropic value, which is input into a random number generator to generate a random number for use by a client computer.

Abstract: Provided is a computer-implemented method for automatically preserving privacy in a user interface. The method includes detecting privacy objects that are being presented via a UI of a computing device to a first user. A security status of the UI is evaluated based at least in part on analyzing audio captured by an audio capture device of the computing device. A privacy mode of the UI that executes privacy actions that are associated with the detected privacy objects is activated based on determining that the security status is in an unsecure state. The privacy mode is deactivated based on determining that the security status has changed from the unsecure state to a secure state, in which determining that the security status has changed from unsecure to secure is based on analyzing the audio captured by the audio capture device of the computing device.

Abstract: A computer-implemented method includes monitoring a current location of a mobile robot in a physical space, which includes a first area separated from a second area by a selectively permeable virtual membrane, and a software requirement corresponding to the mobile robot with regard to the second area. The method further includes identifying a software state of the mobile robot that matches the software requirement, determining whether the software state of the mobile robot meets the software requirement, and allowing the mobile robot to move from the first area to the second area through the selectively permeable virtual membrane in response to determining whether the software state of the mobile robot meets the software requirement.

Abstract: A method establishes a session between a network resource and a user device used by a user having a particular sociometric identity. One or more processors identify an interaction between a user and one or more provider entities. The processor(s) identify profiles for the one or more provider entities, and compute a sociometric identity of the user based on the profiles of the one or more provider entities with which the user has had an interaction. One or more processors transmit the sociometric identity to a network resource in order to establish a session between the network resource and a user device used by the user having the sociometric identity.

Abstract: A processor-implemented method improves security in a blockchain network of devices, which supports a blockchain, by protecting security, privacy, financial fairness, and secure transfer of identity assets. An identity asset provider device creates an identity asset related to an entity. The identity asset provider also creates a provider key, which is composed of multiple bits, and which is needed to decrypt an encrypted version of the identity asset. The identity asset provider device transmits the provider key bit-by-bit to an identity asset consumer device. A price for the provider key depends on how many bits have been transmitted to the identity asset consumer device.

Abstract: A processor-implemented method improves security in a blockchain network of devices by protecting security, privacy and ownership assurance of identity assets, where the blockchain network of devices supports a blockchain. An identity asset provider device establishes co-ownership of an identity asset for an identity asset provider and an entity. The identity asset provider device directs a first member of the blockchain network of devices to associate identities of the identity asset provider and the entity based on their co-ownership of the identity asset by using commitments between the identity asset provider and the entity and based on collaborative proof of ownership of the identity asset using zero knowledge proofs in the blockchain network of devices.

Abstract: A photographic monopod includes an extendable shaft, a bracket for fixing a photographic device at a first end of the extendable shaft, and a grip at a second end of the extendable shaft. The grip is opposite to the first end of the extendable shaft. The photo graphic monopod further includes a shutter control switch for controlling a shutter of the photographic device, and a shaft extension sensor for sensing a degree to which the extendable shaft is extended. The photographic monopod additionally includes a logic circuit for receiving the degree to which the extendable shaft is extended from the shaft extension sensor and disabling a connection between the shutter control switch and the photographic device when the degree to which the extendable shaft is extended exceeds a threshold.

Abstract: A signal transmission control method, system, and computer program product, include an advanced vehicle signal transmission control according to a context of the vehicle where a differential signal transmission action is performed based on the context.

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: 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 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: Using an imaging device of a user device associated with a public user, an image of an autonomous vehicle (AV) operating in an area is captured. The public user associated with the user device is other than an occupant or controller of the AV. Image processing of the image is performed to extract a set of visual characteristics of the AV. A visual characteristic in the set of visual characteristics is insufficient to uniquely identify the AV. From a set of AVs a subset of candidate AVs is selected where each candidate AV in the subset of candidate AVs matches within a tolerance at least one visual characteristic in the set of visual characteristics, the subset of candidate AVs including the AV. A stop command is sent to the AV, causing the AV to execute a stopping operation resulting in a change in a velocity of the AV.

Abstract: Anomalous control and data flow paths in a program are determined by machine learning the program's normal control flow paths and data flow paths. A subset of those paths also may be determined to involve sensitive data and/or computation. Learning involves collecting events as the program executes, and associating those event with metadata related to the flows. This information is used to train the system about normal paths versus anomalous paths, and sensitive paths versus non-sensitive paths. Training leads to development of a baseline “provenance” graph, which is evaluated to determine “sensitive” control or data flows in the “normal” operation. This process is enhanced by analyzing log data collected during runtime execution of the program against a policy to assign confidence values to the control and data flows. Using these confidence values, anomalous edges and/or paths with respect to the policy are identified to generate a “program execution” provenance graph associated with the policy.

Abstract: A method generates and implements a real-time amelioration action for ameliorating an imminent collision between a self-driving vehicle (SDV) and an object. One or more processors detect that an imminent collision by a self-driving vehicle (SDV) is imminent with a confidence C1, and determine whether the SDV has an occupant of occupant type P with a confidence C2. One or more processors identify an object with which the imminent collision by the SDV is imminent with a confidence C3, and then generate and implement, based on C1, C2, C3, and P, a real-time amelioration action for ameliorating the imminent collision between the SDV and the object.