Patent ID: 9547768
Date: 2017-01-17
CPC Classifications: G06F,Y04S

Claim:
1. A method to provide privacy measurement and privacy quantification of sensor data, the method comprising: receiving sensor data from a sensor; calculating a privacy measuring factor with respect to a private content and a non-private content, wherein the private content and the non-private content are associated with the sensor data, wherein the privacy measuring factor is calculated by using a computation technique, wherein the computation technique comprises an entropy based information theoretical model along with computational robustness enhancer through statistical compensation that is computed using Wasserstein distance when two-sample Kolmogorov-Smirnov test finds a misfit between the distribution of private data and the input sensor data and wherein the privacy measuring factor depicts an amount of privacy with respect to the private content; determining a compensation value with respect to a distribution dissimilarity of private content such that the compensation value compensates a statistical deviation in the privacy measuring factor, wherein the statistical deviation refers to a deviation in measurement of privacy while calculating the privacy measuring factor; determining a privacy quantification factor by using the compensation value and the privacy measuring factor; and scaling the privacy quantification factor with respect to a predefined finite scale to obtain at least one scaled privacy quantification factor, wherein the predefined scale comprises a finite set of values, and wherein each value from the finite set of values refers to quantification of privacy content associated with the sensor data; wherein the receiving, the identifying, the calculating, the determining the compensation value, the determining the privacy quantification factor and the scaling are performed by a processor.