Abstract: A method, a computer system, and a computer program product for security risk analysis is provided. Embodiments of the present invention may include collecting operational data. Embodiments of the present invention may include building pipelines. Embodiments of the present invention may include localizing security issues using the operational data on an unsupervised model. Embodiments of the present invention may include constructing a semantic graph using shift-left data. Embodiments of the present invention may include constructing a mapping between the operational data and the shift-left data. Embodiments of the present invention may include clustering collected datasets. Embodiments of the present invention may include creating an active learning cycle using ground truth.

Abstract: A method, system and apparatus for protecting against out-of-bounds references, including storing an address of a buffer in a general register and storing bounds information (BI) for the buffer in a bounds information register, and when a content of the general register is used as an address in a load or store operation, using a content of the bounds information register to determine if the load or store is out of bounds.

Abstract: A method, system, and computer program product for managing communication privacy in a conversation system are provided. The method detects an utterance on a public channel by a user of a computing device. A privacy nature of the utterance is determined. Based on the privacy nature, a classification confidence is determined for the utterance. The method generates a privacy question to be presented to the user based on the privacy nature and the classification confidence. In response to a confirmation response, a privacy channel is established. The method switches from the public channel to the privacy channel.

Abstract: One or more computer processors receive a domain name system (DNS) request in response to a client connecting to a compute resource. The one or more computer processors decoding the DNS request into one or more provision parameters. The one or more computer processors determining that the compute resource is unavailable for a connection with the client utilizing the identified IP address. The one or more computer processors, responsive to determining that the compute resource is not available or not ready, provisioning and deploying a new compute resource according to the one or more decoded provision parameters, wherein the new compute resource is available to the client under the identified IP address.

Abstract: A computer-implemented method and a computer system for detecting and preventing distributed data exfiltration attacks. The computer system calculates historical usage statistics for a service, instances of the service, and clients requesting the instances, generates a baseline of normal usage activities for the clients and the instances based on the historical usage statistics, monitors current activities of the clients to build signatures of queries by the clients and signatures of the instances, and correlates the signatures to determine whether a data exfiltration attack is in progress. In response to determining that the data exfiltration attack is in progress, the computer system increases one or more risk scores corresponding to the data exfiltration attack. In response to determining that the one or more risk scores and an overall risk score of the service exceed a predetermined threshold, the computer system generates an alert of the data exfiltration attack.

Abstract: Embodiments for providing intelligent land use planning recommendations using heterogeneous temporal datasets in a computing environment. One or more positive land-use interventions, one or more negative land-use interventions, or a combination thereof may be recommended for a selected geographical region from heterogeneous chronological data.

Abstract: In an approach for compressing a neural network, a processor receives a neural network, wherein the neural network has been trained on a set of training data. A processor receives a compression ratio. A processor compresses the neural network based on the compression ratio using an optimization model to solve for sparse weights. A processor re-trains the compressed neural network with the sparse weights. A processor outputs the re-trained neural network.

Abstract: An electronic printed circuit board structure for mitigating conductive anodic filament growth. The structure includes at least two conductive layers and a dielectric layer sandwiched between the conductive layers. At least one hole extends through the dielectric layer, and a layer of nonconductive material covers the at least one hole, wherein the nonconductive material is glass-free. A conductive plate layer is disposed over the nonconductive material layer to form a via connection in the structure.

Abstract: A computer-implemented method for correcting muffled speech caused by facial coverings is disclosed. The computer-implemented method includes monitoring a user's speech for speech distortion. The computer-implemented method further includes determining that the user's speech is distorted. The computer-implemented method further includes determining that a cause of the user's speech distortion is based, at least in part, on a presence of a particular type of facial covering. The computer-implemented method further includes automatically correcting the speech distortion of the user based, at least in part, on the particular type of facial covering causing the speech distortion.

Abstract: Mechanisms are provided to receive encoded header information stored on a tape of a tape drive, wherein the encoded header information has been generated by: generating, for a plurality of tracks of the tape of the tape drive, a header information in a plurality of symbols, wherein the plurality of symbols is comprised of a first set of symbols and a second set of symbols, wherein the first set of symbols include identical information across all tracks of the plurality of tracks, and wherein the second set of symbols are configurable to include different information across all tracks of the plurality of tracks; and modifying, for writing to the tape of the tape drive, the first set of symbols of the plurality of tracks to include parity information corresponding to information included in the second set of symbols of the plurality of tracks. The received encoded header information is decoded.

Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

Abstract: Tasks of directed acyclic graphs (DAGs) may be dynamically scheduled based on a plurality of constraints and conditions, task prioritization policies, task execution estimates, and configurations of a heterogenous system. A machine learning component may be initialized to dynamically schedule the tasks of the DAGs.

Abstract: Within a database table being replicated from a source database to a target database, a first logged database operation on a database column holding large object (LOB) data is identified. The source database is queried for a plurality of rows of LOB data, each row in the plurality of rows of LOB data comprising LOB data stored in the database column holding LOB data. Responsive to determining that a first row of LOB data in the plurality of rows of LOB data is smaller than a message size threshold, the first row of LOB data is sent to the target database, the sending performed in a first message.

Abstract: Using labelled training content, a content classification model is trained. Using the trained content classification model, a label describing a first content is determined. The first content is classified into a category in a set of categories using the label. Responsive to the first content being classified into a category of inappropriate content, the first content is removed from a storage location.

Abstract: An embodiment includes detecting a set of anomalies recorded during a first predefined window of time in log entries for a computer environment. The embodiment also includes generating cluster data representative of a cluster of anomalies from among the set of anomalies, where the cluster is formed using a lattice clustering algorithm that spatially distinguishes the cluster of anomalies from other anomalies in the set of anomalies. The embodiment also includes composing an explanation using log templates generated from log entries associated with the cluster of anomalies.

Abstract: A method for managing a battery to perform a final action, the method includes determining a battery supplying power to an electronic device is discharging and receiving battery specification information for the battery. The method includes receiving environmental condition information for the battery and determining an open circuit voltage for the battery. The method includes determining a base capacity for the battery, a first capacity reduction for the battery based on the battery specification, and a second capacity reduction for the battery based on the environmental condition information. The method includes determining an overall expected capacity for the battery based on the first capacity reduction and the second capacity reduction, where the overall expected capacity represents available energy. Responsive to determining the available energy for the battery is less than a required energy to perform an action prior to battery depletion, the method includes sending a warning notification.

Abstract: A processor may analyze one or more unread messages. The one or more unread messages may be from one or more respective conversations. The processor may generate, from the analyzing, an ambiguous strings model. The processor may summarize, via utilization of the ambiguous strings model, the one or more unread messages. The processor may genericize the ambiguous strings model.

Abstract: Embodiments of the present invention can be used to in response to receiving information, dynamically detecting an event associated with a user. Embodiments of the present invention can then, in response to dynamically detecting an event associated with the user, creating a visual simulation of the detected event.

Abstract: According to one embodiment, a method, computer system, and computer program product for using mobile devices for anomaly detection in a vehicle. The present invention may include a computer receives sensor data from at least one mobile device associated with the vehicle, where the mobile device having one or more sensors. The computer analyzes data from the one or more sensors to identify an anomaly associated with the vehicle. The computer identifies a message associated with the anomaly. The computer determines an urgency value of the message based on the anomaly. The computer transfers the message with the urgency value to the vehicle and causes the vehicle to notify the message using a vehicle notification device.

Abstract: For a first server virtual machine (VM) virtualizing a logical volume in a read/write mode for a client VM, a second server VM virtualizing the logical volume in an off mode is instantiated. The logical volume comprises a virtualization of a portion of physical storage. At the first server VM, the logical volume is deactivated, the deactivating disallowing the first server VM from performing a storage request from the client VM. At the second server VM, the logical volume is activated, the activating performed by causing the second VM to virtualize the logical volume in the read/write mode, the activating allowing the second server VM to perform the storage request.