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公开(公告)号：US11921848B2
公开(公告)日：2024-03-05
申请号：US17086855
申请日：2020-11-02
Applicant: Oracle International Corporation
Inventor： Zexi Chen , Kenny C. Gross , Ashin George , Guang C. Wang
CPC classification number: G06F21/554 , G06F17/16 , G06F17/18 , G06N5/04 , G06N20/00
Abstract: The disclosed embodiments relate to a system that characterizes susceptibility of an inferential model to follow signal degradation. During operation, the system receives a set of time-series signals associated with sensors in a monitored system during normal fault-free operation. Next, the system trains the inferential model using the set of time-series signals. The system then characterizes susceptibility of the inferential model to follow signal degradation. During this process, the system adds degradation to a signal in the set of time-series signals to produce a degraded signal. Next, the system uses the inferential model to perform prognostic-surveillance operations on the set of time-series signals with the degraded signal. Finally, the system characterizes susceptibility of the inferential model to follow degradation in the signal based on results of the prognostic-surveillance operations.
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公开(公告)号：US11460500B2
公开(公告)日：2022-10-04
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
Abstract: Detecting whether a target 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：US11255894B2
公开(公告)日：2022-02-22
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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公开(公告)号：US11210400B1
公开(公告)日：2021-12-28
申请号：US16915593
申请日：2020-06-29
Applicant: Oracle International Corporation
Inventor： Guang C. Wang , Kenny C. Gross
Abstract: The disclosed embodiments provide a system that detects unwanted electronic components in a target asset. During operation, the system obtains target electromagnetic interference (EMI) signals by monitoring EMI signals generated by the target asset while the target asset is running a periodic workload. Next, the system generates a target EMI fingerprint from the target EMI signals. The system then applies a compression/dilation technique to time-series signals in the target EMI fingerprint to achieve alignment with corresponding time-series signals in a reference EMI fingerprint to produce a synchronized target EMI fingerprint. Finally, the system compares the synchronized target EMI fingerprint against the reference EMI fingerprint to determine whether the target asset contains any unwanted electronic components.
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公开(公告)号：US11132875B1
公开(公告)日：2021-09-28
申请号：US16891938
申请日：2020-06-03
Applicant: Oracle International Corporation
Inventor： Guang C. Wang , William A. Wimsatt , Andrew J. Lewis , Michael H. S. Dayringer , Kenny C. Gross
Abstract: A system is provided that detects a card skimmer in a target system, wherein the card skimmer surreptitiously gathers credit/debit card information during operation of the target system. This system first gathers target electromagnetic interference (EMI) signals by monitoring EMI signals generated by the target system through an external scanner with a directional antenna. Next, the system generates a target EMI fingerprint from the target EMI signals. The system then compares the target EMI fingerprint against a reference EMI fingerprint for the target system to determine whether the target system contains a card skimmer.
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Patent Agency Ranking
公开(公告)号：US20210235275A1
公开(公告)日：2021-07-29
申请号：US17230156
申请日：2021-04-14
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Ashin George , Guang C. Wang
IPC: H04W12/79 , G06F21/75 , H04W12/108
Abstract: The disclosed embodiments relate to a system that camouflages EMI fingerprints in EMI emissions from a computing system to enhance system security. During operation, the system monitors the EMI emissions from the computer system during operation of the computer system to produce corresponding EMI signals. Next, the system determines a dynamic amplitude of the EMI emissions based on the EMI signals. If the dynamic amplitude of the EMI emissions drops below a threshold value, the system executes synthetic transactions, which have interarrival times that, when superimposed on a workload of the computer system, cause the computer system to produce randomized EMI emissions.
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公开(公告)号：US11012862B2
公开(公告)日：2021-05-18
申请号：US16258544
申请日：2019-01-26
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Ashin George , Guang C. Wang
IPC: H04L29/06 , G06F21/75 , H04W12/79 , H04W12/108
Abstract: The disclosed embodiments relate to a system that camouflages electromagnetic interference (EMI) fingerprints in EMI emissions from a computing system to enhance system security. During operation, the system monitors the EMI emissions from the computer system while the computer system is operating to produce corresponding EMI signals. Next, the system performs a Fast Fourier Transform (FFT) operation on the EMI signals. The system then converts an output of the FFT operation into a frequency-domain representation of the EMI signals. Next, the system generates a camouflaging signal based on the frequency-domain representation of the EMI signals. Finally, the system outputs the camouflaging signal through a transmitter to camouflage EMI fingerprints in the EMI emissions from the computer system.
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28.发明授权公开(公告)号：US10929776B2
公开(公告)日：2021-02-23
申请号：US16186365
申请日：2018-11-09
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Guang C. Wang , Edward R. Wetherbee
Abstract: During operation, the system obtains time-series sensor signals gathered from sensors in an asset during operation of the asset in an outdoor environment, wherein the time-series sensor signals include temperature signals. Next, the system produces thermally-compensated time-series sensor signals by performing a thermal-compensation operation on the temperature signals to compensate for variations in the temperature signals caused by dynamic variations in an ambient temperature of the outdoor environment. The system then trains a prognostic inferential model for a prognostic pattern-recognition system based on the thermally-compensated time-series sensor signals. During a surveillance mode for the prognostic pattern-recognition system, the system receives recently-generated time-series sensor signals from the asset, and performs a thermal-compensation operation on temperature signals in the recently-generated time-series sensor signals. Finally, the system applies the prognostic inferential model to the thermally-compensated, recently-generated time-series sensor signals to detect incipient anomalies that arise during operation of the asset.
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29.发明授权公开(公告)号：US10862302B1
公开(公告)日：2020-12-08
申请号：US16458498
申请日：2019-07-01
Applicant: Oracle International Corporation
Inventor： Cornell Thomas Eyford, III , Kenny C. Gross , Guang C. Wang
Abstract: The system receives a set of load signals from an archive that contains historic load information gathered at various locations throughout an electrical grid, which distributes electrical power for the utility system. Next, the system applies a first difference function to the set of load signals to produce a set of difference signals. The system then performs a spike-detection operation on the set of difference signals to identify pairs of positive-negative and negative-positive spikes, which identify gaps in the set of load signals associated with periods of network disruption. Next, the system modifies the set of load signals by filling in each identified gap with projected load values determined by performing a localized loadshape forecasting operation based on the continuous load values immediately preceding the identified gap. Finally, the system forecasts electricity demand for the utility system based on the modified set of load signals.
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30.发明申请公开(公告)号：US20200310396A1
公开(公告)日：2020-10-01
申请号：US16371694
申请日：2019-04-01
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Guang C. Wang
IPC: G05B19/418 , G05B23/02 , G06F17/50
Abstract: During operation, the system receives time-series signals from sensors in the asset while the asset is operating. Next, the system obtains real-time environmental parameters for an environment in which the asset is operating. The system then selects an environment-specific inferential model for the asset based on the real-time environmental parameters, wherein the environment-specific inferential model was trained on a golden system while the golden system was operating in an environment that matches the real-time environmental parameters. Next, the system uses the environment-specific inferential model to generate estimated values for the received time-series signals based on correlations among the received time-series signals, and performs a pairwise-differencing operation between actual values and the estimated values for the received time-series signals to produce residuals. Finally, the system determines from the residuals whether the asset is operating correctly.
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