DETECTING ANOMALIES IN AN INTERNET OF THINGS NETWORK
First Claim
1. A computer-implemented method comprising:
- receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment;
identifying a set of normal data records from the dataset based on the target variable;
identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and
detecting anomaly based on the inter-feature correlations for predictive maintenance.
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Abstract
The present disclosure describes methods, systems, and computer program products for detecting anomalies in an Internet-of-Things (IoT) network. One computer-implemented method includes receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance.
46 Citations
20 Claims
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1. A computer-implemented method comprising:
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receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A non-transitory, computer-readable medium storing computer-readable instructions executable by a computer and configured to perform operations comprising:
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receiving a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance. - View Dependent Claims (12, 13, 14, 15)
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16. A system, comprising:
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a memory; at least one hardware processor interoperably coupled with the memory and configured to perform operations comprising; receiving a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance. - View Dependent Claims (17, 18, 19, 20)
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Specification