H04L67/104

MECHANISM TO IDENTIFY LINK DOWN REASONS
20230231906 · 2023-07-20 ·

Methods, systems, and devices are provided herein for a mechanism to identify link down reasons. As described herein, a first port of a first peer device may be determined to have unexpectedly changed to a port down state. Subsequently, a topology file may be referenced to identify a second port of a second peer device with which the first peer device is intended to have a link if not for the first port being in a port down state. In some examples, port settings of the first port may be compared with port settings of the second port. If a port setting for the first port mismatches an associated port setting for the second port, an alert message may be transmitted to a network administrator indicating this mismatch as a possible reason for the first port being in the port down state.

Methods and system for auditing batch jobs using blockchain
11706280 · 2023-07-18 · ·

Systems and methods for auditing batch jobs with blockchain transactions are provided. In one embodiment, a method is provided that includes running a batch job on a client machine to download one or more files from a server machine to the client machine and determining a batch job result of the batch job. The method may further include generating a batch result transaction at the client machine. The batch result transaction may include the batch job result. In certain embodiments, the method may proceed with adding the batch result transaction to the blockchain.

Methods and system for auditing batch jobs using blockchain
11706280 · 2023-07-18 · ·

Systems and methods for auditing batch jobs with blockchain transactions are provided. In one embodiment, a method is provided that includes running a batch job on a client machine to download one or more files from a server machine to the client machine and determining a batch job result of the batch job. The method may further include generating a batch result transaction at the client machine. The batch result transaction may include the batch job result. In certain embodiments, the method may proceed with adding the batch result transaction to the blockchain.

MACHINE LEARNING TECHNIQUES FOR DETECTING SURGES IN CONTENT CONSUMPTION

The present disclosure describes a content consumption monitor (CCM) that determines surges in content consumption based on changes in content consumptions scores. The CCM determines the content consumptions scores for domains and/or organizations (orgs) based on session events generated by different devices/users from the org and/or domain, a number of events generated by the org/domain, content and/or user interactions with the content indicated by the events, relevancy scores of the content to one or more topics, and/or other criteria. The CCM detects surges in consumption or interest in a topic for the domain/org when the consumption score reaches a threshold and/or within a period of time. The CCM may adjust the consumption score based on the changes in the relevancy, number of events and/or the number of users over different time periods. Other embodiments may be described and/or claimed.

Apparatuses and methods for evaluation of proffered machine intelligence in predictive modelling using cryptographic token staking

A method of improving performance of machine learning models by leveraging crowdsourced artificial intelligence includes sending first data to a plurality of data source compute nodes and receiving indications of stakes and estimates based on the first data from the plurality of data source compute nodes. Each data source compute node is ranked based on the received indications of stakes, to generate a plurality of ranked data source compute nodes. An accuracy of each received estimate is calculated by comparing the received estimates to second data. Until a predefined resource is depleted, and in order of rank, if the accuracy of the estimate associated with a ranked data source compute node exceeds a predefined threshold, the predefined resource is decremented and a token augmentation can be assigned to the ranked data source compute node.

Group-based communication apparatus configured to implement operational sequence sets and render workflow interface objects within a group-based communication system

Various embodiments of the present invention are directed to an improved group-based communication apparatus that is configured to render one or more workflow interface objects to a group-based communication apparatus in association with an operational sequence set returned by a query. The group-based communication apparatus is configured to detect a workflow trigger event associated with a workflow identifier, retrieve an operational sequence set based upon at least the workflow identifier from a group-based communication workflow repository, initiate the operational sequence set, and cause rendering of one or more workflow interface objects to the group-based communication interface. In some embodiments, the operational sequence sets are associated with a group-defined template.

Method and a system for retrieving and applying dynamic policy rules in a network

A system and method for publishing and updating policy rules in a network can be based on predictive algorithms and blockchain techniques for network systems (e.g. next generation emergency systems).

TRUSTED LIGHTWEIGHT COMMUNICATION IN CLOUD ROBOTICS
20230020169 · 2023-01-19 ·

System and techniques for trusted lightweight communication in cloud robotics are described herein. A device for trusted lightweight communication in cloud robotics can include a memory having instructions and processing circuitry. When in operation, the processing circuitry can be configured by the instructions to receive a first report from a first device after the first device runs a first algorithm and a second report from a second device after the second device runs the first algorithm with an edge controller. The first algorithm can be stored on a distributed ledger. Consensus between the first device and the second device can be determined by agreement between the first report and the second report. An entry, indicative of consensus between the first device and the second device, can be added to the distributed ledger.

LOCALIZED MACHINE LEARNING OF USER BEHAVIORS IN NETWORK OPERATING SYSTEM FOR ENHANCED SECURE SERVICES IN SECURE DATA NETWORK
20230020504 · 2023-01-19 · ·

In one embodiment, a method comprises: initiating, by an executable agent within a secure executable container executed by a network device, a monitoring of a network-based service between the network device and a second network device having a two-way trusted relationship with the network device within a secure peer-to-peer data network, the network-based service based on a securely-stored secure data structure or a securely-transmitted secure data structure in the secure peer-to-peer data network; executing, by the executable agent, a secure machine learning operation based on one or more user actions associated with the network-based service, wherein the secure executable container prevents any access of any unencrypted data structure, or accessing the secure peer-to-peer data network, without authorized access via a prescribed Application Programming Interface (API); and autonomically executing, by the executable agent, an improved operation for the network-based service based on the machine learning.

Block chain permission control method, device, and node apparatus
11558177 · 2023-01-17 · ·

The present disclosure discloses a method, device and node apparatus for blockchain permission control. The method comprises: receiving target information sent by a node apparatus; acquiring an account address of a configured account of the node apparatus; acquiring, according to the account address, from a predetermined block stored with the account address and an account permission corresponding to the account address, the account permission corresponding to the account address; and processing the target information according to the account permission accordingly. In the present disclosure, node apparatuses are configured with corresponding accounts, and performing permission control on the accounts can restrict permissions of different node apparatuses so as to ensure security and privacy of blockchain data.