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    • 1. 发明授权
    • Camouflaging business-activity information in a telemetry signal through randomization
    • 通过随机化在遥测信号中伪装业务活动信息
    • US07482947B2
    • 2009-01-27
    • US11471204
    • 2006-06-20
    • Kenny C. GrossKeith A. WhisnantRamakrishna C. Dhanekula
    • Kenny C. GrossKeith A. WhisnantRamakrishna C. Dhanekula
    • H04K3/00
    • H04L63/0428H04L67/125
    • One embodiment of the present invention provides a system that camouflages business-activity information in telemetry signals from a computer system. During operation, the system monitors telemetry signals from the computer system to obtain a time series containing a telemetry metric which provides business-activity information. Next, the system computes a serial correlation between data values in the time series. The system then determines if the computed serial correlation between the data values in the time series is above a predetermined threshold level. If so, the system performs frequency domain analysis on the time series. The system then generates artificial activity on the computer system which causes the frequency spectra of the time series to reduce the serial correlation between the data values in the time series.
    • 本发明的一个实施例提供一种从计算机系统伪装遥测信号中的业务活动信息的系统。 在操作期间,系统监视来自计算机系统的遥测信号,以获得包含提供业务活动信息的遥测度量的时间序列。 接下来,系统计算时间序列中的数据值之间的串行相关性。 然后,系统确定所计算的时间序列中的数据值之间的串行相关性是否高于预定的阈值水平。 如果是这样,系统会对时间序列进行频域分析。 然后,该系统在计算机系统上产生人为活动,其导致时间序列的频谱以减少时间序列中的数据值之间的串行相关性。
    • 2. 发明授权
    • Characterizing a computer system using a pattern-recognition model
    • 使用模式识别模型来表征计算机系统
    • US08150655B2
    • 2012-04-03
    • US12240211
    • 2008-09-29
    • Ramakrishna C. DhanekulaKeith A. WhisnantKenny C. Gross
    • Ramakrishna C. DhanekulaKeith A. WhisnantKenny C. Gross
    • G06F11/30
    • G06F1/206G06F11/0706G06F11/0751G06F11/3428G06F11/3476
    • Some embodiments of the present invention provide a system that characterizes a computer system using a pattern-recognition model. First, values for an environmental parameter are monitored from a set of sensors associated with the computer system. Then, a baseline for the environmental parameter is calculated based on the monitored values from a subset of the set of sensors. Next, the baseline is subtracted from the monitored values from sensors in the set of sensors to produce compensated values. Then, the compensated values are used as inputs to the pattern-recognition model, which produces estimates for the compensated values based on correlations between the compensated values learned during a training phase. Next, residuals are calculated by subtracting the estimates for the compensated values from the compensated values. Then, the residuals are analyzed to characterize the computer system.
    • 本发明的一些实施例提供一种表征使用模式识别模型的计算机系统的系统。 首先,从与计算机系统相关联的一组传感器监测环境参数的值。 然后,基于来自传感器组的子集的监视值来计算环境参数的基线。 接下来,从传感器组中的传感器的监视值中减去基线,以产生补偿值。 然后,补偿值被用作模式识别模型的输入,其基于在训练阶段期间学习的补偿值之间的相关性而产生对补偿值的估计。 接下来,通过从补偿值中减去补偿值的估计值来计算残差。 然后,分析残差以表征计算机系统。
    • 5. 发明申请
    • CHARACTERIZING A COMPUTER SYSTEM USING A PATTERN-RECOGNITION MODEL
    • 使用模式识别模型表征计算机系统
    • US20100082299A1
    • 2010-04-01
    • US12240211
    • 2008-09-29
    • Ramakrishna C. DhanekulaKeith A. WhisnantKenny C. Gross
    • Ramakrishna C. DhanekulaKeith A. WhisnantKenny C. Gross
    • G06F15/00
    • G06F1/206G06F11/0706G06F11/0751G06F11/3428G06F11/3476
    • Some embodiments of the present invention provide a system that characterizes a computer system using a pattern-recognition model. First, values for an environmental parameter are monitored from a set of sensors associated with the computer system. Then, a baseline for the environmental parameter is calculated based on the monitored values from a subset of the set of sensors. Next, the baseline is subtracted from the monitored values from sensors in the set of sensors to produce compensated values. Then, the compensated values are used as inputs to the pattern-recognition model, which produces estimates for the compensated values based on correlations between the compensated values learned during a training phase. Next, residuals are calculated by subtracting the estimates for the compensated values from the compensated values. Then, the residuals are analyzed to characterize the computer system.
    • 本发明的一些实施例提供一种表征使用模式识别模型的计算机系统的系统。 首先,从与计算机系统相关联的一组传感器监测环境参数的值。 然后,基于来自传感器组的子集的监视值来计算环境参数的基线。 接下来,从传感器组中的传感器的监视值中减去基线,以产生补偿值。 然后,补偿值被用作模式识别模型的输入,其基于在训练阶段期间学习的补偿值之间的相关性而产生对补偿值的估计。 接下来,通过从补偿值中减去补偿值的估计值来计算残差。 然后,分析残差以表征计算机系统。
    • 9. 发明申请
    • Camouflaging business-activity information in a telemetry signal through randomization
    • 通过随机化在遥测信号中伪装业务活动信息
    • US20080001777A1
    • 2008-01-03
    • US11471204
    • 2006-06-20
    • Kenny C. GrossKeith A. WhisnantRamakrishna C. Dhanekula
    • Kenny C. GrossKeith A. WhisnantRamakrishna C. Dhanekula
    • G08C19/16
    • H04L63/0428H04L67/125
    • One embodiment of the present invention provides a system that camouflages business-activity information in telemetry signals from a computer system. During operation, the system monitors telemetry signals from the computer system to obtain a time series containing a telemetry metric which provides business-activity information. Next, the system computes a serial correlation between data values in the time series. The system then determines if the computed serial correlation between the data values in the time series is above a predetermined threshold level. If so, the system performs frequency domain analysis on the time series. The system then generates artificial activity on the computer system which causes the frequency spectra of the time series to reduce the serial correlation between the data values in the time series.
    • 本发明的一个实施例提供一种从计算机系统伪装遥测信号中的业务活动信息的系统。 在操作期间,系统监视来自计算机系统的遥测信号,以获得包含提供业务活动信息的遥测度量的时间序列。 接下来,系统计算时间序列中的数据值之间的串行相关性。 然后,系统确定所计算的时间序列中的数据值之间的串行相关性是否高于预定的阈值水平。 如果是这样,系统会对时间序列进行频域分析。 然后,该系统在计算机系统上产生人为活动,其导致时间序列的频谱以减少时间序列中的数据值之间的串行相关性。