Patent ID: 11968239
Assignee: QOMPLX LLC
Field: Digital communication (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 6:
7. A method for detection and mitigation of data source compromises, comprising the steps of:
storing a reputation relationship graph in a cloud computing platform, the reputation relationship graph comprising nodes representing reputation scores of a plurality of data services, and edges representing relationships between the nodes;
storing a baseline database in the cloud computing platform, the baseline content database comprising baseline ratings for each of the plurality of data services;
using a data extractor operating as a software module stored in an in-memory associative array of a hardware memory of the cloud computing platform:
periodically connecting to, and pulling data from, application programming interfaces (APIs) of the plurality of data services;
for each data pull from each API, extracting metadata included in the data pull that identifies the source and content of data in that data pull;
for each data pull from each API, using the data and the extracted metadata to identify and measure a plurality of data quality metrics;

using a reputation management system operating as a software module stored in the in-memory associative array of the cloud computing platform:
receiving the plurality of measured data quality metrics and the data and its extracted metadata;
establishing a component reputation score for the data in each data pull by:
comparing the extracted metadata identifying the content of the data against a breach content database;
comparing the extracted metadata for identifying the source of the data against a vulnerabilities and exploits database;
comparing the data quality metrics for determining if a data source has been compromised against the baseline database;
generating the component reputation score for that data pull based on the comparisons using weighted averaging;
for each component reputation score generated, creating a new node in the reputation relationship graph representing the component reputation score, and associating the new node via one or more edges with one or more existing nodes in the reputation relationship graph for the data service from which the data was pulled; and
generating a new reputation score for each data service from which data was pulled by analyzing the new nodes and edges of the graph added for each component reputation score associated with that data service, by performing the following steps:
for each data pull from each data service, updating the breach content database with the new reputation score and publishing the update on a first publication and subscription data feed for the breach content database; and
for each data pull from each data service, updating the vulnerabilities and exploits database with the new reputation score and publishing the update on a second publication and subscription data feed for the vulnerabilities and exploits database;

wherein the reputation relationship graph logically organizes the plurality of data services into a distributed collaborative database with a reliability of each data service being indicated by its reputation score.