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

Claim 0:
1. A system for detection and mitigation of data source compromises, comprising:
a cloud computing platform;
a reputation relationship graph stored in an in-memory associative array stored in a hardware memory of a cloud computing platform and comprising nodes representing reputation scores associated with a plurality of data services, and edges representing relationships between the nodes;
a baseline database stored in the non-volatile storage device of the cloud computing platform, the baseline database comprising a baseline rating for each of the plurality of data services;
a data extractor and pre-processor comprising a first plurality of programming instructions operating on the cloud computing platform, wherein the first plurality of programming instructions causes the cloud computing platform to:
periodically connect to, and pull data from, application programming interfaces (APIs) of the plurality of data services;
for each data pull from each API, extract metadata included in that data pull that identifies the data service and a content of the data in that data pull;
for each data pull from each API, use the data and the extracted metadata to identify and measure a plurality of data quality metrics;

a reputation management system comprising a second plurality of programming instructions operating on the cloud computing platform, wherein the second plurality of programming instructions causes the cloud computing platform to:
receive the plurality of measured data quality metrics and the data and its extracted metadata;
establish a reputation score for the data in each data pull by:
comparing the extracted metadata for 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; and
generating a component reputation score for that data pull based on the comparisons;

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:
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.