Abstract: According to one embodiment, a method, computer system, and computer program product for population density approximation is provided. The embodiment may include identifying a device as entering a preconfigured distance of a preconfigured area, whereby the preconfigured area is one of a plurality of preconfigured areas. The embodiment may also include gathering device-identifying information corresponding to the device. The embodiment may further include creating a profile for each device using the device-identifying data. The embodiment may also include correlating device movements across the plurality of preconfigured areas using the profile associated with each device. The embodiment may further include calculating a population density based on the correlated device movements.

Abstract: According to one embodiment, a method, computer system, and computer program product for preventing intrusions on a network is provided. The present invention may include generating a sandbox environment responsive to detecting an attacker in the network, wherein the sandbox environment comprises dynamically generated data tailored to the target of the attacker; and moving the attacker to the sandbox environment.

Abstract: According to one embodiment, a method, computer system, and computer program product for intrusion movement prediction is provided. The embodiment may include receiving environmental sensor data corresponding to a monitored space as captured by a plurality of sensors affixed to an airflow component. The embodiment may also include generating a three-dimensional model of the monitored space using the received environmental data. The method may further include, in response to determining a disturbance is present in the three-dimensional model, performing a security action.

Abstract: According to one embodiment, a method, computer system, and computer program product for crowd density analysis with multiple regions is provided. The embodiment may include identifying three or more local measurement nodes. The embodiment may also include defining one or more bins, each bin comprising at least three local measurement nodes from the three or more local measurement nodes. The embodiment may further include mapping one or more regions corresponding to a bin from the one or more bins. The embodiment may also include identifying a device in a region. The embodiment may further creating a profile corresponding to the identified device. The embodiment may also include calculating a population density based on a number of created profiles in a region from the one or more regions.

Abstract: Examples described herein provide a computer-implemented method that includes, in response to receiving a request against the workload in an environment comprising predetermined cloud-based containers, searching predetermined container runtime interface metadata across a plurality of compute nodes in the environment to locate runtime processes. The method further includes selecting, for each runtime process located, a respective applicable profiler from a set of predetermined profilers sharing a transactional database. The method further includes injecting, for each runtime process located, predetermined code libraries for each respective applicable profiler. The method further includes re-linking the predetermined code libraries for each respective applicable profiler. The method further includes executing, for each runtime process located, each respective applicable profiler to produce a set of results.

Abstract: According to one embodiment, a method, computer system, and computer program product for intrusion movement prediction is provided. The embodiment may include receiving environmental sensor data corresponding to a monitored space as captured by a plurality of sensors affixed to an airflow component. The embodiment may also include generating a three-dimensional model of the monitored space using the received environmental data. The method may further include, in response to determining a disturbance is present in the three-dimensional model, performing a security action.

Abstract: According to one embodiment, a method, computer system, and computer program product for preventing intrusions on a network is provided. The present invention may include generating a sandbox environment responsive to detecting an attacker in the network, wherein the sandbox environment comprises dynamically generated data tailored to the target of the attacker; and moving the attacker to the sandbox environment.

Abstract: A computer-implemented method for detecting and obstructing skimmer devices is disclosed. The computer-implemented method includes monitoring wireless communications within a network environment. The computer-implemented method further includes identifying information associated with one or more wireless communications within the network environment transmitted by an unknown wireless device. The computer-implemented method further includes selecting an obstruction rule based, at least in part, on the information associated with the one or more wireless communications transmitted by the unknown wireless device. The computer-implemented method further includes executing an obstruction action corresponding to the selected obstruction rule.

Abstract: According to one embodiment, a method, computer system, and computer program product for intrusion movement prediction is provided. The embodiment may include receiving environmental sensor data corresponding to a monitored space as captured by a plurality of sensors affixed to an airflow component. The embodiment may also include generating a three-dimensional model of the monitored space using the received environmental data. The method may further include, in response to determining a disturbance is present in the three-dimensional model, performing a security action.

Abstract: According to one embodiment, a method, computer system, and computer program product for intrusion movement prediction is provided. The embodiment may include receiving environmental sensor data corresponding to a monitored space as captured by a plurality of sensors affixed to an airflow component. The embodiment may also include generating a three-dimensional model of the monitored space using the received environmental data. The method may further include, in response to determining a disturbance is present in the three-dimensional model, performing a security action.

Abstract: A computer-implemented method, a system, and a computer program product for detecting objects are disclosed. The method can include receiving, by a computer communicatively connected to a plurality of anemometers positioned throughout the space, first sensor data from the plurality of anemometers, creating a baseline profile of airflow in the space based on the first sensor data, and receiving second sensor data from the plurality of anemometers at a different time than the first sensor data. The method can include comparing the second sensor data with the first sensor data to determine first different data, rendering, in response to determining that the second sensor data is different from the first sensor data, a representation of the object using the first different data and first location data related to the first different data, and calculating a vector associated with the object using the first different data and the first location data.

Abstract: A method, a computer program product, and a system for server provisioning and deployment. The method includes receiving a deployment configuration for a server. The deployment configuration includes a requested software build and a requested installation of an application and configuration for the server. The method also includes reconfiguring hardware on the server based on the deployment configuration and via an out-of-band management card on the server and pushing a boot loader on to the server for installation of an operating system. The method further includes performing an installation of the operating system on the server, transmitting an auto configuration file to the server. The auto configuration file provides installation properties relating to the application. The method also includes monitoring a status of the server during the installation of the application using a serial terminal output on the server.

Abstract: A computer-implemented method includes: monitoring an operating system of a server that serves content to client computing devices, wherein the server maintains log files; determining, based on the monitoring, whether commands received at the operating system are indicative of tampering with one or more of the log files; responsive to determining the commands are indicative of tampering with one or more of the log files, performing a predefined security action; and responsive to determining the commands of the user are not indicative of tampering with one or more of the log files, sending the commands to a kernel of the operating system for execution.

Abstract: Capturing data in a drone enabled environmental for testing soil and ecological decision making includes initiating, using a computer, collection of data from multiple sources using a drone. The data includes information about soil at a specified soil location, in response to the drone flying over air space of a physical or geographical location respective to the soil location and/or landing at the soil location. Soil data is received, as part of the data, from the drone in response to testing the soil. The testing of the soil can include conducting a ground conductivity test using two or more probes coupled to respective landing pads of the drone, and positioning the drone over the soil location such that the two or more probes contact the soil. The data is analyzed to determine a best location for seeding and growing a plant in the soil.

Abstract: Capturing data in a drone enabled environmental for testing soil and ecological decision making includes initiating, using a computer, collection of data from multiple sources using a drone. The data includes information about soil at a specified soil location, in response to the drone flying over air space of a physical or geographical location respective to the soil location and/or landing at the soil location. Soil data is received, as part of the data, from the drone in response to testing the soil. The testing of the soil can include conducting a ground soil density test using a frangible probe. The data is analyzed to determine a best location for seeding and growing a plant in the soil.

Abstract: A method for a multi-factor authentication, the method receives results of an initial authentication of a user. Responsive to confirming the initial authentication, an image of a secondary set of authentication options is presented. An option selection is received from the user, wherein the selection is determined by tracking eye movement of the user over the image that includes the set of second factor authentication options. User facial activity is tracked corresponding to the selection made from the secondary set of authentication options. The monitored facial activity is compared to a pre-established authentication condition to determine whether a match exists with the selected secondary set of authentication options, and responsive to facial activity monitored matching the authentication condition pre-established by the user and corresponding to the selection made from the secondary set of authentication options, authentication of the user is confirmed.

Abstract: According to one embodiment, a method, computer system, and computer program product for population density approximation is provided. The embodiment may include identifying a device as entering a preconfigured distance of a preconfigured area, whereby the preconfigured area is one of a plurality of preconfigured areas. The embodiment may also include gathering device-identifying information corresponding to the device. The embodiment may further include creating a profile for each device using the device-identifying data. The embodiment may also include correlating device movements across the plurality of preconfigured areas using the profile associated with each device. The embodiment may further include calculating a population density based on the correlated device movements.

Abstract: A computer-implemented method for anomaly detection in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor. The method includes receiving a plurality of real-time airflow patterns acquired by a plurality of airflow alerters, wherein each real-time airflow pattern corresponds to a different airflow alerter; comparing each real-time airflow pattern with a predetermined airflow pattern, wherein each real-time airflow pattern corresponds to a different predetermined airflow pattern; when there is any real-time airflow pattern different from the corresponding predetermined airflow pattern, identifying a group of airflow alerters among the plurality of airflow alerters, wherein a real-time airflow pattern of each airflow alerter in the group is different from the corresponding predetermined airflow pattern; and identifying a location of an anomaly based on the group of airflow alerters.

Abstract: A computer-implemented method, a system, and a computer program product for detecting objects are disclosed. The method can include receiving, by a computer communicatively connected to a plurality of anemometers positioned throughout the space, first sensor data from the plurality of anemometers, creating a baseline profile of airflow in the space based on the first sensor data, and receiving second sensor data from the plurality of anemometers at a different time than the first sensor data. The method can include comparing the second sensor data with the first sensor data to determine first different data, rendering, in response to determining that the second sensor data is different from the first sensor data, a representation of the object using the first different data and first location data related to the first different data, and calculating a vector associated with the object using the first different data and the first location data.

Abstract: A computer-implemented method for anomaly detection in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor, the method including: receiving, by the processor, a real-time airflow pattern detected from an airflow alerter, wherein the real-time airflow pattern is generated by a heating, ventilation, and air conditioning (HVAC) system in a particular facility; comparing, by the processor, the real-time airflow pattern to a predetermined airflow pattern for the HVAC system; and when the real-time airflow pattern is different from the predetermined airflow pattern, receiving, by the processor, an alert message indicating an anomaly from the airflow alerter.