Method and system for anonymizing subsets selected from datasets of parameters relating to a plurality of network-connected devices

1. A method comprising:

obtaining a plurality of datasets, each dataset comprising a set of parameters related to one of a plurality of network-connected devices;

automatically selecting a subset of parameters from at least one of the datasets relating to one of the plurality of network-connected devices, wherein the selecting is based on specified selection criteria;

calculating an autocorrelation of the selected subset of parameters;

calculating a correlation of the selected subset of parameters and one or more subsets of parameters selected from the datasets relating to network-connected devices other than said one of the plurality of network-connected devices, based on selection criteria that are identical to said specified selection criteria;

applying said correlation and said autocorrelation to a decision function to determine, based on said correlation and said autocorrelation and said selection criteria, whether said selected subset of parameters is an anonymized subset that is insufficient for determining an identity of said one of the plurality of the network-connected devices.

2. The method according to claim 1 , wherein said decision function comprises an operator applied to said correlation and said autocorrelation and further applies a threshold on an outcome of said operator beyond which said selected subset of parameters is considered an anonymized subset that is insufficient for determining an identity of the said one of the plurality of the network-connected devices.

3. The method according to claim 2 , wherein in a case that said outcome is not above said specified threshold, determining said selected subset of parameters as a subset that is sufficient for determining an identity of the said one of the plurality of the network-connected devices and revising said selection criteria to similar and non-identical selection criteria.

4. The method according to claim 2 , wherein said operator is division and said outcome is a quotient of said correlation divided by said autocorrelation, wherein in a case that said quotient is above a specified threshold, determining said selected subset of parameters as an anonymized subset that is insufficient for determining an identity of the said one of the plurality of the network-connected devices, and wherein in a case that said quotient is not above said specified threshold, determining said selected subset of parameters as a subset that is sufficient for determining an identity of the said one of the plurality of the network-connected devices.

5. The method according to claim 1 , wherein the selection criteria include selecting a portion of a spatiotemporal space relating to said plurality of network-connected devices.

6. The method according to claim 1 , wherein said network-connected devices comprise connect vehicles and wherein said parameters include at least one activity of said connected vehicles, wherein said activity is further associated with at least one of: time of occurring, and location of occurring.

7. The method according to claim 3 , wherein said similar and non-identical selection criteria comprise a partial overlap of portions of a spatiotemporal space representing the respective selection criteria.

8. A system comprising:

a computer memory configured to obtain a plurality of datasets, each dataset comprising a set of parameters related to one of a plurality of network-connected devices; and

a computer processor configured to:

automatically select a subset of parameters from at least one of the datasets relating to one of the plurality of network-connected devices, wherein the selecting is based on specified selection criteria;

calculate an autocorrelation of the selected subset of parameters;

calculate a correlation of the selected subset of parameters and one or more subsets of parameters selected from the datasets relating to network-connected devices other than said one of the plurality of network-connected devices, based on selection criteria that are identical to said specified selection criteria; and

apply said correlation and said autocorrelation to a decision function to determine, based on said correlation and said autocorrelation and said selection criteria, whether said selected subset of parameters is an anonymized subset that is insufficient for determining an identity of said one of the plurality of the network-connected devices.

9. The system according to claim 8 , wherein said decision function comprises an operator applied to said correlation and said autocorrelation and further applies a threshold on an outcome of said operator beyond which said selected subset of parameters is considered an anonymized subset that is insufficient for determining an identity of the said one of the plurality of the network-connected devices.

10. The system according to claim 9 , wherein in a case that said outcome is not above said specified threshold, determining said selected subset of parameters as a subset that is sufficient for determining an identity of the said one of the plurality of the network-connected devices and revising said selection criteria to similar and non-identical selection criteria.

11. The system according to claim 9 , wherein said operator is division and said outcome is a quotient of said correlation divided by said autocorrelation, wherein in a case that said quotient is above a specified threshold, determining said selected subset of parameters as an anonymized subset that is insufficient for determining an identity of the said one of the plurality of the network-connected devices, and wherein in a case that said quotient is not above said specified threshold, determining said selected subset of parameters as a subset that is sufficient for determining an identity of the said one of the plurality of the network-connected devices.

12. The system according to claim 9 , wherein the selection criteria include selecting a portion of a spatiotemporal space relating to said plurality of network-connected devices.

13. The system according to claim 8 , wherein said network-connected devices comprise connect vehicles and wherein said parameters include at least one activity of said connected vehicles, wherein said activity is further associated with at least one of: time of occurring, and location of occurring.

14. The system according to claim 10 , wherein said similar and non-identical selection criteria comprise a partial overlap of portions of a spatiotemporal space representing the respective selection criteria.

15. A non-transitory computer readable medium comprising a set of instructions that when executed cause at least one computer processor to:

obtain a plurality of datasets, each dataset comprising a set of parameters related to one of a plurality of network-connected devices;

automatically select a subset of parameters from at least one of the datasets relating to one of the plurality of network-connected devices, wherein the selecting is based on specified selection criteria;

calculate an autocorrelation of the selected subset of parameters;

calculate a correlation of the selected subset of parameters and one or more subsets of parameters selected from the datasets relating to network-connected devices other than said one of the plurality of network-connected devices, based on selection criteria that are identical to said specified selection criteria; and

apply said correlation and said autocorrelation to a decision function to determine, based on said correlation and said autocorrelation and said selection criteria, whether said selected subset of parameters is an anonymized subset that is insufficient for determining an identity of said one of the plurality of the network-connected devices.

16. The non-transitory computer readable medium according to claim 15 , wherein said decision function comprises an operator applied to said correlation and said autocorrelation and further applies a threshold on an outcome of said operator beyond which said selected subset of parameters is considered an anonymized subset that is insufficient for determining an identity of the said one of the plurality of the network-connected devices.

17. The non-transitory computer readable medium according to claim 16 , wherein in a case that said outcome is not above said specified threshold, determining said selected subset of parameters as a subset that is sufficient for determining an identity of the said one of the plurality of the network-connected devices and revising said selection criteria to similar and non-identical selection criteria.

18. The non-transitory computer readable medium according to claim 16 , wherein said operator is division and said outcome is a quotient of said correlation divided by said autocorrelation, wherein in a case that said quotient is above a specified threshold, determining said selected subset of parameters as an anonymized subset that is insufficient for determining an identity of the said one of the plurality of the network-connected devices, and wherein in a case that said quotient is not above said specified threshold, determining said selected subset of parameters as a subset that is sufficient for determining an identity of the said one of the plurality of the network-connected devices.

19. The non-transitory computer readable medium according to claim 16 , wherein the selection criteria include selecting a portion of a spatiotemporal space relating to said plurality of network-connected devices.

20. The non-transitory computer readable medium according to claim 15 , wherein said network-connected devices comprise connect vehicles and wherein said parameters include at least one activity of said connected vehicles, wherein said activity is further associated with at least one of: time of occurring, and location of occurring.

21. The system non-transitory computer readable medium to claim 17 , wherein said similar and non-identical selection criteria comprise a partial overlap of portions of a spatiotemporal space representing the respective selection criteria.