Abstract: A computer-implemented method, according to one embodiment, includes determining whether a predetermined sequence of knocks has been performed by a requesting node to other nodes of a network along existing paths between the requesting node and the other nodes. In response to a determination that the predetermined sequence of knocks has been performed, a connection is established between the requesting node and a first of the other nodes. A computer program product, according to another embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method. A system, according to another embodiment, includes a processor, and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor. The logic is configured to perform the foregoing method.

Abstract: Computer-implemented methods for repairing a software of a computing system are provided. Aspects include receiving a request to diagnose the software, the software including a plurality of software components configured to communicate with each other via application programing interfaces and creating a representation of the software in a virtual reality environment. Aspects also include identifying an error in the software based on error logs generated by the software and identifying one or more of the plurality of software components and the application programing interfaces that correspond to the error. Aspects further include displaying a visual indication of the error in the virtual reality environment, wherein the visual indication is determined based on a type of the error, receiving, via the virtual reality environment, a corrective action from a user, and performing a task in the software based on the corrective action, wherein the task is configured to address the error.

Abstract: Embodiments related to using a foundational model for network packet traces. A technique includes receiving network traffic of a network and extracting features from the network traffic, the features having a function related to communications in the network. The technique includes generating tokens from the features, each of the features corresponding to a respective one of the tokens, training a machine learning model by inputting the tokens, the machine learning model being trained to output contextual embeddings for the tokens, and using the contextual embeddings to determine an anomaly in the network traffic.

Abstract: An example operation may include one or more of receiving, via a proxy located in a first geographic jurisdiction, a request for data from a software program, wherein the data is stored in a database located in a second geographic jurisdiction, identifying a regulatory constraint that must be enforced on the data stored in the database in the second geographic jurisdiction based on a policy associated with the second geographic jurisdiction, retrieving, via the proxy in the first geographic jurisdiction, the data requested from a proxy located in the second geographic jurisdiction, delivering the data received from the proxy located in the second geographic jurisdiction to the software program, and executing, via the proxy in the first geographic jurisdiction, an additional action on the data to comply with the regulatory constraint of the second geographic jurisdiction.

Abstract: Techniques for non-iterative federated learning include receiving local models from agents, generating synthetic datasets for the local models, and producing outputs using the local models and the synthetic datasets. A global model is trained based on the synthetic datasets and the outputs.

Abstract: A computer-implemented method, according to one embodiment, includes determining a plurality of downstream task models of a foundation model, and arranging the downstream task models into a logical tree structure. Each node of the logical tree structure represents a sequence of layers of an associated one of the downstream task models. In response to a determination that a request for inferencing on a target model has resulted in a cache miss occurring, the logical tree structure is used to identify an inferencing server that satisfies at least a first predetermined prerequisite for fulfilling the inferencing request. The method further includes causing the identified inferencing server to fulfill the inferencing request. A computer program product, according to one embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: A method, computer system, and a computer program product is provided for establishing a dynamically adaptive network firewall. A firewall model is established that identifies resources that can be used and a plurality of nodes that connect to one another to form a network. A set of external rules and policies are provided to each resource. The firewall implemented using the firewall model upon receiving of incoming data and upon traffic flow. The firewall expands or contracts the network by adding or removing resources according to work that needs to be performed. The work includes both tasks to be completed and efforts that has to be taken by the firewall to ensure security by preventing unauthorized access into the network.

Abstract: Embodiments related to using a foundational model for network packet traces. A technique includes receiving network traffic of a network and extracting features from the network traffic, the features having a function related to communications in the network. The technique includes generating tokens from the features, each of the features corresponding to a respective one of the tokens, training a machine learning model by inputting the tokens, the machine learning model being trained to output contextual embeddings for the tokens, and using the contextual embeddings to determine an anomaly in the network traffic.

Abstract: Methods are provided. A method includes announcing to a network meta information describing each of a plurality of distributed data sources. The method further includes propagating the meta information amongst routing elements in the network. The method also includes inserting into the network a description of distributed datasets that match a set of requirements of the analytics task. The method additionally includes delivering, by the routing elements, a copy of the analytics task to locations of respective ones of the plurality of distributed data sources that include the distributed datasets that match the set of requirements of the analytics task.

Abstract: A computer-implemented method for grouping devices in a massive multiple-input and multiple-output (MIMO)-based cellular network, in accordance with one embodiment, includes determining movement states of end devices in a cell of the massive MIMO-based cellular network, estimating payload requirements of the end devices, and grouping the end devices in a group based on the determined movement states and the estimated payload requirements.

Abstract: A provenance method, system, and non-transitory computer readable medium for a plurality of eidetic systems having logs, include crawling the logs of each node of a plurality of nodes of the eidetic systems to cluster segments across the logs of temporally correlated events into clustered segments and analyzing the correlated segments to interleave an order of processes in the logs and assign a probability to the order of the processes occurring.

Abstract: A system may receive an existing base set of knowledge, train a neural network on the base set of knowledge, deploy the neural network on a new data set, generate, using the deployment, instances of new knowledge, and validate the instances of new knowledge.

Abstract: Computer-implemented methods for drone-assisted communications networks are provided. Aspects include collecting, from one or more sensing drones, signal strength information for a communications network in a geographic area and creating, based at least in part on the signal strength information, a signal strength map for the geographic area. Aspects also include deploying one or more networking drones into the geographic area, wherein a location of the one or more drones in the geographic area is determined based at least in part on the signal strength map. The one or more networking drones are configured to provide access to the communications network.

Abstract: Computer-implemented methods for autonomous identification of rouge devices in a communications network are provided. Aspects include collecting connection trace data including connection characteristics for each of a plurality of mobile devices in communication with a communications network and aggregating the connection trace data. Aspects also include determining performance characteristics for each of a plurality of groups of the plurality of mobile devices, wherein each of the plurality of groups corresponds to mobile devices having a type approval code and comparing the performance characteristics for each of the plurality of groups. Based on a determination that the performance characteristics of one of the plurality of groups deviate from the performance characteristics of a remaining set of the plurality of groups by more than a first threshold amount, aspects include designating the type approval code associated with the one of the plurality of groups as a rogue type approval code.

Abstract: A computer-implemented method and a computer system establish network slices within a physical network having a plurality of network elements. The method includes receiving a request to instantiate a network slice at a network element. The method also includes determining a performance metric of the network element. The method further includes delaying instantiation of the requested network slice within the network element in response to determining that the performance metric of the network element is below a threshold. The method also includes instantiating the requested network slice within the network element in response to determining that the performance metric of the network element is at or above the threshold. Finally, the method includes deactivating the requested network slice in response to determining that the performance metric of the network element is below the threshold at a time subsequent to instantiating the requested network slice.

Abstract: A method, computer system, and a computer program product managing data usage integrity is provided. In one embodiment, the method comprises receiving data connected with data usage of at least one user in a computer environment. The pricing information is then for the user relating to the data usage. The computer embodiment is segmented into a plurality of segment areas and a payment price is calculated for each segment area. An anomaly is detected by comparing the data usage and the associated pricing for each of segmented areas according to a preselected value. If an anomaly is selected, an end-to-end simulation check is performed for the computer environment to ascertain whether the payment price for the segment may be inconsistent with a resource usage affecting an end-to-end flow for the computer environment.

Abstract: A cloud-enterprise resource management system enables sharing of computing resources belonging to different datacenters by one or more clients of a resource pooling and sharing service. Each datacenter of includes a first partition of computing resources and a second partition of computing resources. The first partition is designated as reserved for use by an enterprise operating the datacenter. The second partition is designated as available for use by one or more clients of the resource pooling and sharing service. A workload manager in each datacenter predicts workload and transfers (i) a first computing resource from the first partition to the second partition wherein when the predicted workload is below a first threshold and (ii) a second computing resource from the second partition to the first partition when the predicted workload is above a second threshold.

Abstract: Personalization with on-device privacy preservation is provided by receiving, at a user device, a generalized recommendation from a remote provider backend, which include a plurality of candidate items responsive to a request from an application running on the user device; generating a plurality of candidate vectors corresponding to the plurality of candidate items representing a corresponding candidate item in a binary format across a plurality of metrics associated with the plurality of candidate items; generating a user vector based on personal data stored on the user device, the user vector representing a user in a binary format across one or more metrics associated with the personal data; determining interaction propensities based on the user vector and the plurality of candidate vectors according to a global model run on the user device; and displaying, on the user device, the plurality of candidate items according to the interaction propensities.

Abstract: Embodiments are disclosed for a method for a wearable secure data device. The method includes setting an operational mode for the wearable secure data device that stores a plurality of secure data items. The method also includes receiving a request for at least one of the secure data items from a client device that is communicating with a third-party device. Additionally, the method includes determining if the operational mode is associated with allowing access to the secure data items. Further, the method includes providing a response based on the determination.

Abstract: Disclosed are methods method, systems, and computer program products for automatic management of a data processing system (DPS). One embodiment of the method may comprise receiving, at a computer processor, operations data associated with a DPS; and generating, by a Question-Answer (QA) system executing on the computer processor, a Question sentence from the operations data. The method may further comprise sampling a window of the operations data, extracting a plurality of key performance indicators (KPI) from the operations data in the sampled window, and providing the plurality of KPI to the QA system.