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USING TOKENIZED ANONYMIZATION OF DATA FOR TREND ANALYSIS

IP.com Disclosure Number: IPCOM000247342D
Publication Date: 2016-Aug-25
Document File: 4 page(s) / 33K

Publishing Venue

The IP.com Prior Art Database

Related People

Avraham Poupko: AUTHOR [+2]

Abstract

A system and method are presented in which data is fully anonymized, but it is still possible to trace trends over time using a token that is not traceable back to the individual device or user. This allows an operator to collect and store trend data even in countries that a have very limiting laws regarding the storage of data. Contrary to traditional anonymization methods, the token generation is not a function of the subject it represents, precluding the ability to replicate the generation process to bypass the anonymization.

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USING TOKENIZED ANONYMIZATION OF DATA FOR TREND ANALYSIS

AUTHORS:

Avraham Poupko Erez Ravina

CISCO SYSTEMS, INC.

ABSTRACT

    A system and method are presented in which data is fully anonymized, but it is still possible to trace trends over time using a token that is not traceable back to the individual device or user. This allows an operator to collect and store trend data even in countries that a have very limiting laws regarding the storage of data. Contrary to traditional anonymization methods, the token generation is not a function of the subject it represents, precluding the ability to replicate the generation process to bypass the anonymization.

DETAILED DESCRIPTION

    Data analysis can be used to recognize and analyze trends. One use is to improve marketing messages or campaigns, change offerings or modify business tactics or plans. However, in order to track a trend, it is often necessary to store personal data. Otherwise there is no way of tracking personal usage of a product or service over time. For example, if it is desirable to know if people are watching more TV this year as compared to last year, it is important to know how much TV specific users viewed last year and how much they viewed this year. The anonymization of an individual identity should not come at the cost of losing the ability to track behavior associated with this individual over the long. Moreover, the removal of identifying characteristics should not lead to identity replication (so that an individual inadvertently gets counted three times: once as a male over the age of 40, once as a resident of Sacramento, and once as an avid viewer of sports-content).

Copyright 2016 Cisco Systems, Inc.

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    In some countries, storing such data is highly regulated or even illegal. That means that in those countries there is currently no way to obtains statistical trends. Even obtaining trends on the aggregate of the population is impossible.

    An underlying assumption is that any operator granting anonymized tokenization- service, as well as consumer-entities using these tokens for anonymization (i.e. operators), adhere to the local laws and regulations governing mandatory destruction of private data. Thus any private data that can be associated with the tokens during their generation should be assumed to have been properly destroyed in accordance with the law (thus the need to validate whether a record has been destroyed or not - is not being addressed in this document).

TECHNICAL EXPLANATION

    The token-generation and distribution service is provided to a plurality of client devices. Devices can be set-top boxes, companion devices, home gateways, or other devices through which operators are able to harvest data for trend-analysis, and because of which they are exposed to privacy-regulated data. However, the solution will not be able to ascribe a single token to several devices associated with a single individual. This is due to the need to adhere to the stricte...