Abstract: An application programming interface (API) analysis system includes a data network and an API Carbon Footprint Analyzer (ACFA). The data network is configured to receive a call from a remote to onboard an application programming interface (API) in the data network and to obtain the API corresponding to the call. The ACFA is configured to scan the API to determine actual payload attributes and to compare the actual payload attributes to expected payload attributes of the API to determine a payload difference. The ACFA calculates an amount of data wastage based on the payload difference and causes a modification to the data network to reduce the amount of data wastage.

Abstract: A method for detecting a fake keypad includes: monitoring outputs of plural magnetic field sensors connected to a keypad; detecting the output of at least one of the magnetic field sensors indicates the presence of a magnetic field; starting, in response to the detecting, a timer; determining the first timer reaches a first threshold while the output of the at least one of the magnetic field sensors still indicates the presence of a magnetic field; in response to the timer reaching the first threshold, determining a number of the magnetic field sensors whose output indicates the presence of a magnetic field equals or exceeds a second threshold; in response to the number of the magnetic field sensors equaling or exceeding the second threshold, determining a security action; and initiating the security action.

Abstract: Embodiments receive a plurality of historical risk assessments and a plurality of quantum readiness levels; calculate a plurality of risk dimension metrics based on the plurality of historical risk assessments and the plurality of quantum readiness levels; calculate a plurality of risk assessment attributes dimension metrics based on the plurality of historical risk assessments and the plurality of quantum readiness levels; generate nearest neighbors nomination based on the calculated plurality of risk dimension metrics and the calculated plurality of risk assessment attributes dimension metrics; calculate a confidence of quality metric based on the generated nearest neighbors nomination; and determine that the confidence of quality metric is below a threshold; and execute a cryptography algorithm based on a determination that the confidence of quality metric is below the threshold.

Abstract: An approach is disclosed for training an artificial intelligence (AI) model to recommend services for a complex composite service chain in a cloud computing platform. The training uses metadata from various services provided by different service providers. The method involves inputting a first service into the trained AI model, which then suggests recommended services. These recommendations are displayed to a user, who selects one of the suggested services. The selected service is displayed as part of the service chain. The AI model then processes metadata from the selected service to provide additional service recommendations. This iterative process continues, with the AI model being further trained based on user selections to improve its recommendations.

Abstract: A computer-implemented method may include querying a centralized patch repository for new patch data; receiving a confirmation that there is new patch data in the centralized patch repository; spinning-up a proxy in an isolated computing environment in response to the receiving the confirmation; disabling an air-gap of the isolated computing environment configured to receive the new patch data; and receiving the new patch data at the isolated computing environment from the centralized patch repository.

Abstract: Computer software that stores information relating to a planned in-person meeting between a first user and a second user. The information includes a meeting time, a meeting location, and, for each of the first user and the second user: (i) a communications identifier associated with a device of the respective user, and (ii) a token identified by the respective user for the meeting. The computer software, in response to receiving an indication that the device of the first user is located at the meeting location at the meeting time, sends, to the device of the first user: (i) the communications identifier associated with the device of the second user, and (ii) the token identified by the second user for the meeting.

Abstract: A method includes identifying, by a computing device, activities of a machine using a digital twin of a machine; running, by the computing device, simulations of the activities on the digital twin; determining, by the computing device, a performance issue in the machine using the simulations; and deploying, by the computing device, a capability to address the performance issue.

Abstract: A computer-implemented method for model building with explainability is provided. The method includes receiving, by a hardware processor, a first metric and a second metric of minimum model performance. The first metric relates to data modeling quality and the second metric relates to model to business rule correlations. The method further includes performing, by the hardware processor, auto Artificial Intelligence model generation responsive to training data and a combination of the first and the second metrics of minimum model performance to obtain a model that is trained and meets model prediction accuracy and model prediction explainability requirements represented by the combination of the first and the second metrics of minimum model performance.

Abstract: One or more embodiments relate to protecting data stored by a non-volatile memory of a memory device installed in a computing device. A technique includes in response to a power-up of the memory device, incrementing a memory power cycle count, and receiving a host power cycle count indicating a number of power-ups of the computing device. The technique includes, if the memory power cycle count is not equal to the host power cycle count, applying a security reaction to the memory, the security reaction being adapted for preventing a readout of the data.

Abstract: A method includes: detecting, by a computing device, connection of a universal serial bus device to a computer; determining, by the computing device, that the computer is in a locked mode; detecting, by the computer device, input to the computer within a predetermined time of detecting the connection; determining, by the computing device as a result of the computer being locked and detecting the input, that the input is a threat to the computer; creating, by the computing device, a temporary virtual environment; receiving, by the computing device, the input into the temporary virtual environment; processing, by the computing device, the input in the temporary virtual environment; and recording, by the computing device, information related to the input.

Abstract: A system can evaluate multiple candidate scripts. The system receives a problem statement and a sample solution script. The system selects an additional script based on the sample solution script, and compiles a list of candidates including the sample and additional scripts. Then, for each of the candidates, the system simulates execution of the script and scores performance of the script. The system then presents results of the execution.

Abstract: A computer-implemented method for receiving, at a database, an analytics request associated with a selected data line from a database and reading a set of additional bytes from the database corresponding to the selected data line. The method may further include parsing and formatting the set of additional bytes read from the database to generate, at the database, an analytics reply to the analytics request, where each of a plurality of data lines in the database represents a search query and where the analytics data comprises a number of search query requests on a subject matter and a number of search query requests for private data.

Abstract: A computer-implemented method includes: obtaining, by a computing device, data items from data sources; classifying, by the computing device, the data items into categories using a first machine learning (ML) model; generating, by the computing device, a risk score of a first data center based on the classified data items and using a second machine learning (ML) model; determining, by the computing device, the risk score of the first data center exceeds a threshold; and in response to the determining the risk score of the first data center exceeds the threshold, initiating, by the computing device, a migration of the first data center to a second data center.

Abstract: The present disclosure relates generally to cybersecurity and, more particularly, to a system and method to detect and prevent login attacks. A computer-implemented method includes: gathering, by a computing device, a login window from a display of a user device; determining, by the computing device, that the login window is invalid; flagging, by the computing device, the login window as an attack on the user device upon determining that the login window is invalid; and executing, by the computing device, a security action on the user device.

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: Aspects of the present disclosure include: detecting, by a computing device, an avatar is chatting within a virtual environment; detecting, by the computing device, the avatar is idle for a predetermined amount of time; providing, by the computer device, a challenge to the idled avatar, determining, by the computer device, that the challenge has not been executed; and executing, by the computer device, a security action associated with the idled avatar.

Abstract: Embodiments relate to preventing deep fake voicemail scams. In response to receiving a voice message, an intent of the voice message is determined. The intent is determined to relate to a persuasion technique. A warning is provided about the voice message.

Abstract: This disclosure presents an approach for identifying obfuscation patterns within system log files to enhance cybersecurity. The method involves two key stages: first, detecting tampering in a primary set of log entries; and second, monitoring a secondary set of log files for the presence of these tampering patterns. By comparing the identified obfuscation patterns in the primary log entries with those detected in the secondary set, the system can effectively identify potential system intrusions. This innovative approach provides an advanced and proactive means of bolstering system security by uncovering and responding to malicious activities that attempt to obscure their tracks within log files, ultimately enhancing the defense against cyber threats.

Abstract: A data governance system includes a signet template generator engine, a signet specification enforcement, and a pattern based signet controller. The signet template generator engine generates a signet template by applying at least one signet to raw data received from a data producer. The at least one signet is designated with a consent level and includes at least one data field designated with a consent identifier. The signet specification enforcement engine analyzes the consent level of the at least one signet and the consent identifier of the at least one data field, and outputs first filtered data based on the consent identifier of the at least one data field. The pattern based signet controller generates second filtered data based on the consent level of the at least one signet, and outputs a combination of the first filter data and the second filtered data as final data.

Abstract: An example operation may include one or more of storing a hash of a service set identifier (SSID) of a wireless network via an apparatus, receiving a probe request message transmitted from a network device, wherein the probe request message comprises a hash value, determining that the hash value within the probe request is a valid SSID based on the hash of the SSID of the wireless network stored in the storage device, and controlling the network interface to transmit a probe response with a plain text name of the SSID to the network device in response to the determination.