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公开(公告)号：US20210270884A1
公开(公告)日：2021-09-02
申请号：US16804531
申请日：2020-02-28
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Edward R. WETHERBEE , Rui ZHONG , Kenny C. GROSS , Guang C. WANG
Abstract: Detecting a counterfeit status of a target utility device by: selecting a set of frequencies that best reflect load dynamics or other information content of a reference utility device while undergoing a power test sequence; obtaining target electromagnetic interference (EMI) signals emitted by the target utility device while undergoing the same power test sequence; creating a sequence of target kiviat plots from the amplitude of the target EMI signals at each of the set of frequencies at observations over the power test sequence to form a target kiviat tube EMI fingerprint; comparing the target kiviat tube EMI fingerprint to a reference kiviat tube EMI fingerprint for the reference utility device undergoing the power test sequence to determine whether the target utility device and the reference utility device are of the same type; and generating a signal to indicate a counterfeit status based at least in part on the results of the comparison.
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12.发明申请公开(公告)号：US20210247442A1
公开(公告)日：2021-08-12
申请号：US16784506
申请日：2020-02-07
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Edward R. WETHERBEE , Guang C. WANG , Kenny C. GROSS , Michael DAYRINGER , Andrew LEWIS , Matthew T. GERDES
IPC: G01R31/28 , G06F21/55 , G01R31/302 , G06K9/62
Abstract: Detecting whether a target utility device that includes multiple electronic components is genuine or suspected counterfeit by: performing a test sequence of energizing and de-energizing the target device and collecting electromagnetic interference (EMI) signals emitted by the target device; generating a target EMI fingerprint from the EMI signals collected; retrieving a plurality of reference EMI fingerprints from a database library, each of which corresponds to a different configuration of electronic components of a genuine device of the same make and model as the target device; iteratively comparing the target EMI fingerprint to the retrieved reference EMI fingerprints and generating a similarity metric between each compared set; and indicating that the target device (i) is genuine where the similarity metric for any individual reference EMI fingerprint satisfies a threshold test, and is a suspect counterfeit device where no similarity metric for any individual reference EMI fingerprint satisfies the test.
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公开(公告)号：US20240354633A1
公开(公告)日：2024-10-24
申请号：US18133125
申请日：2023-04-11
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Keyang RU , Matthew T. GERDES , Guang Chao WANG , Kenny C. GROSS , Ruixian LIU
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: Systems, methods, and other embodiments associated with determining a quantity of exemplar vectors to select from available training vectors are described. In one embodiment, a method includes determining an available quantity of training vectors that are available in a set of time series signals. A boost function is automatically selected from a plurality of different boost functions based on the available quantity of the training vectors. A selection quantity of the exemplar vectors to select from the training vectors is generated by applying the selected boost function to the training vectors. A quantity of the exemplar vectors is selected from the training vectors based on the selection quantity. A machine learning model is trained to detect an anomaly in the time series signals based on the exemplar vectors that were selected.
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公开(公告)号：US20240127630A1
公开(公告)日：2024-04-18
申请号：US17967254
申请日：2022-10-17
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Guy G. MICHAELI , Mandip S. BHULLER , Timothy D. CLINE , Kenny C. GROSS
CPC classification number: G06V40/40 , G06V20/46 , G06V40/168 , G06V40/172
Abstract: Systems, methods, and other embodiments associated with computer deepfake detection are described. In one embodiment, a method includes converting audio-visual content of a person delivering a speech into a set of time series signals. Residual time series signals of residuals that indicate an extent to which the time series signals differ from machine learning estimates of authentic delivery of the speech by the person are generated. Residual values from one synchronous observation of the residual time series signals are placed into an array of residual values for a point in time. A sequential analysis of the residual values of the array is performed to detect an anomaly in the residual values for the point in time. In response to detection of the anomaly, an alert that deepfake content is detected in the audio-visual content is generated.
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公开(公告)号：US20230358597A1
公开(公告)日：2023-11-09
申请号：US18098277
申请日：2023-01-18
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Matthew T. GERDES , Guang C. WANG , Timothy D. CLINE , Kenny C. GROSS
Abstract: Systems, methods, and other embodiments associated with acoustic detection of changes in mass of cargo carried by a vehicle are described herein. In one example method for acoustic cargo surveillance, a first acoustic output of a vehicle carrying cargo at a first time of surveillance of the vehicle is recorded. Then, a second acoustic output of the vehicle at a subsequent time in the surveillance of the vehicle carrying the cargo is recorded. A change in a mass of the cargo carried by the vehicle is acoustically detected based at least on an acoustic change between the first acoustic output and the second acoustic output. An electronic alert is generated that the mass of the cargo has changed based on the acoustic change.
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Patent Agency Ranking
公开(公告)号：US20230113706A1
公开(公告)日：2023-04-13
申请号：US17495880
申请日：2021-10-07
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： James ROHRKEMPER , Yifan WU , Guang C. WANG , Kenny C. GROSS
IPC: G01V3/10
Abstract: Embodiments for passive spychip detection through polarizability and advanced pattern recognition are described. For example a method includes inducing a magnetic field in a passive component of a target system while the target system is emitting EMI with changes in amplitude repeating at a time interval; generating a time series of measurements of a combined magnetic field strength of the induced magnetic field and the EMI; executing a frequency-domain to time-domain transformation on the time series of measurements to create time series signals of combined magnetic field strength over time at a specific frequency range; monitoring the time series signals with an ML model trained to predict correct signal values to determine whether predicted and measured values of the time series agree; and indicating that the target device may contain a passive spychip where anomalies are detected, and is free of passive spychips where no anomalies are detected.
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公开(公告)号：US20230075065A1
公开(公告)日：2023-03-09
申请号：US17463742
申请日：2021-09-01
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Ikenna D. IVENSO , Matthew T. GERDES , Kenny C. GROSS , Guang C. WANG , Hariharan BALASUBRAMANIAN
IPC: G06N20/00
Abstract: Systems, methods, and other embodiments associated with passive inferencing of signal following in multivariate anomaly detection are described. In one embodiment, a method for inferencing signal following in a machine learning (ML) model includes calculating an average standard deviation of measured values of time series signals in a set of time series signals; training the ML model to predict values of the signals; predicting values of each of the signals with the trained ML model; generating a time series set of residuals between the predicted values and the measured values; calculating an average standard deviation of the sets of residuals; determining that signal following is present in the trained ML model where a ratio of the average standard deviation of measured values to the average standard deviation of the sets of residuals exceeds a threshold; and presenting an alert indicating the presence of signal following in the trained ML model.
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18.发明申请公开(公告)号：US20220261689A1
公开(公告)日：2022-08-18
申请号：US17382593
申请日：2021-07-22
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： William A. WIMSATT , Matthew T. GERDES , Kenny C. GROSS , Guang C. WANG
Abstract: Systems, methods, and other embodiments associated with off-duty-cycle-robust machine learning for anomaly detection in assets with random downtimes are described. In one embodiment, a method includes inferring ranges of asset downtime from spikes in a numerical derivative of a time series signal for an asset; extracting an asset downtime signal from the time series signal based on the inferred ranges of asset downtime; determining that the asset downtime signal carries telemetry based on the variance of the asset downtime signal; training a first machine learning model for the asset downtime signal; detecting a first spike in the numerical derivative of the time signal that indicates a transition to asset downtime; and in response to detection of the first spike, monitoring the time series signal for anomalous activity with the trained first machine learning model.
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19.发明申请公开(公告)号：US20210295210A1
公开(公告)日：2021-09-23
申请号：US16826478
申请日：2020-03-23
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Edward R. WETHERBEE , Kenneth P. BACLAWSKI , Guang C. WANG , Kenny C. GROSS , Anna CHYSTIAKOVA , Dieter GAWLICK , Zhen Hua LIU , Richard Paul SONDEREGGER
Abstract: In one embodiment, a method for auditing the results of a machine learning model includes: retrieving a set of state estimates for original time series data values from a database under audit; reversing the state estimation computation for each of the state estimates to produce reconstituted time series data values for each of the state estimates; retrieving the original time series data values from the database under audit; comparing the original time series data values pairwise with the reconstituted time series data values to determine whether the original time series and reconstituted time series match; and generating a signal that the database under audit (i) has not been modified where the original time series and reconstituted time series match, and (ii) has been modified where the original time series and reconstituted time series do not match.
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公开(公告)号：US20250164345A1
公开(公告)日：2025-05-22
申请号：US18514587
申请日：2023-11-20
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Gerard WARRENS , Guang Chao WANG , Kenny C. GROSS , Matthew T. GERDES , Ruixian LIU
IPC: G01M7/00
Abstract: Systems, methods, and other embodiments associated with ML-based detection of amplification of vibration due to resonance are described. In one embodiment, a method includes recording vibrations of a reference asset while the reference asset is operated based on a test pattern that sweeps over a range of workload for the reference asset. Cross power spectral densities between the recorded vibrations and the test pattern are determined at intervals to identify resonance frequencies of the reference asset. Vibrations of a target asset are monitored at the resonance frequencies with a machine learning model trained to generate estimated values at the resonance frequencies that are consistent with the reference asset. Resonant vibration amplification is detected based on a dissimilarity between vibration values for the target asset at the resonance frequencies and the estimated values. And, an electronic alert that the target asset is undergoing the resonant vibration amplification is generated.
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