US 12,218,978 B2
Method and system for policy management, testing, simulation, decentralization and analysis
Ulrich Lang, San Diego, CA (US); and Rudolf Schreiner, Falkensee (DE)
Filed by Ulrich Lang, San Diego, CA (US); and Rudolf Schreiner, Falkensee (DE)
Filed on Jul. 13, 2022, as Appl. No. 17/864,146.
Application 17/864,146 is a continuation of application No. 16/845,893, filed on Apr. 10, 2020, granted, now 11,405,428.
Application 16/845,893 is a continuation of application No. 15/645,639, filed on Jul. 10, 2017, granted, now 10,623,443, issued on Apr. 14, 2020.
Claims priority of provisional application 62/430,590, filed on Dec. 6, 2016.
Claims priority of provisional application 62/408,829, filed on Oct. 16, 2016.
Claims priority of provisional application 62/360,309, filed on Jul. 8, 2016.
Prior Publication US 2022/0353300 A1, Nov. 3, 2022
Int. Cl. H04L 9/40 (2022.01); G06F 3/04817 (2022.01); G06F 3/0482 (2013.01); G06F 8/38 (2018.01); G06F 40/186 (2020.01)
CPC H04L 63/20 (2013.01) [G06F 3/04817 (2013.01); G06F 3/0482 (2013.01); G06F 8/38 (2013.01); G06F 40/186 (2020.01); H04L 63/0263 (2013.01)] 26 Claims
OG exemplary drawing
 
1. A method for detecting anomalies in a supply chain, comprising:
loading at least one predetermined supply chain data source in a form provided by a supply chain information technologies (IT) system, the at least one predetermined supply chain data including procurement data;
automatically parsing the at least one predetermined supply chain data source and transforming the parsed at least one predetermined supply chain data source into at least one consistent, consolidated normalized supply chain data source;
automatically selecting, based on the at least one normalized supply chain data source, at least one anomaly detection algorithm designed to indicate anomalies related to supply chain risks on the at least one normalized supply chain data source;
indicating the anomalies in the at least one normalized supply chain data source by executing the at least one anomaly detection algorithm on the at least one normalized supply chain data source pertaining to information about organizations in the supply chain, products/services in the supply chain, logistical events and data;
mapping any of the indicated anomalies in the at least one normalized supply chain data source to identified supply chain risk indicators; and
outputting any of the identified supply chain risk indicators.