Saudi Arabian Oil Company

Marek Zidek

Muhammad S Aljuaid

Mazen A Baragaba

Baher Y Al Ramady

Mawada M Felemban

Mohammad Khaled Almunea

Systems and methods include a computer-implemented method for verifying blockchain transaction. A request is received in a blockchain for a user to use an application. A three-blockchain cluster verification process is performed in response to receiving the request. Verification that the application is authorized is performed using a nodes blockchain cluster in the blockchain based on user-application data pre-verified by at least two administrators and stored in the nodes blockchain cluster. Verification that the user exists and is authorized is performed using a users/objects blockchain cluster in the blockchain different from the nodes blockchain cluster, where the verifying is based on the user-application data pre-verified by the at least two administrators and stored in the users/objects blockchain cluster. Verification that credentials for the user exist is performed using a passwords blockchain cluster in the blockchain different from the nodes blockchain cluster and the users/objects blockchain cluster, where the verifying is based on the user-application data pre-verified by the at least two administrators and stored in the passwords blockchain cluster. Access to the application is granted to the user in response to successfully completing the three-blockchain cluster verification process, including verification using the nodes blockchain cluster, the users/objects blockchain cluster, and the passwords blockchain cluster.

Blockchain enhanced identity access management system

A method may include obtaining first cybersecurity data using a hardware probe disposed within a network. The first cybersecurity data may correspond to an analysis of the hardware probe regarding network data that is transmitted through the network. The method may further include obtaining second cybersecurity data using a software probe operating on a network element within the network. The second cybersecurity data may correspond to an analysis of the software probe regarding one or more configuration settings of the network element. The method may further include determining a cybersecurity maturity score using the first cybersecurity data and the second cybersecurity data. The cybersecurity maturity score may be based on a maturity model. The method may further include transmitting, based on the cybersecurity maturity score, a remediation command that adjusts a configuration setting of the network.

Method and system for determining cybersecurity maturity

Systems and methods are disclosed for preventing damage to underground assets caused by earth work or construction equipment and vehicles. The system includes a central data system, which has access to asset location and map data, and a GPS enabled tracking device provided in the vehicle. The system operates by comparing the real-time vehicle location to the stored asset locations, displaying the map, asset information and vehicle location to the vehicle operator and generating alerts when the vehicle breaches a perimeter around an asset. Preferably, both the central data system and the tracking unit are configured to operate together and in parallel, thereby improving the reliability of the system. In addition, the system is also specifically configured to implement various approaches for using and displaying asset location data during monitoring operations while preserving the confidentiality and security of sensitive information.

Systems and methods for preventing damage to unseen utility assets

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improving the connectivity and response speed throughout a network. In one aspect, a method includes receiving network traffic data from an aggregation point on a network, the network traffic data having been sent to or received from one of a plurality of end-point devices on the network, calculating performance metrics for each of the end-point devices based the received network traffic data, for each of the end-point devices, comparing the performance metrics to respective threshold values to determine performance issues for the network, wherein the threshold values are determined based on historical network data, correlating the determined performance issues for the network to an aspect of the end-point devices, and implementing an action to correct the determined performance issues for the network based on the aspect of the at least one end-point devices.

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Dhahran, Saudi Arabia

Marek Zidek