Information privacy protection method oriented to DIKW model driving

Abstract

The invention provides an information privacy protection method for DIKW model driving, which comprises the following steps: S1, according to contents directly or indirectly generated by a target individual object in a network, establishing a DIKWP model of the target individual object, the DIKWP model of the target individual object comprising a DIKWP model of a visitor and a DIKWP model of a visited person; s2, performing essential calculation or differential calculation on the type resources in the visited person, judging whether the corresponding type resources are privacy resources or not based on a calculation result, executing a privacy protection strategy based on the privacy resources, and establishing a privacy DIKWP model; s3, the access request of the visitor is analyzed based on the DIKWP model of the visitor, the intention of the visitor is obtained, the DIKWP model of the interviewee judges whether the visitor has the corresponding privacy access permission or not based on the intention of the visitor, and if yes, privacy resources are searched for in the privacy DIKWP model.

Description

Technical field [0001] The present invention relates to the field of data privacy protection, in particular to information privacy protection methods driven for DIKW models. Background technique [0002] With the broad popularity of the Internet and the advent of big data age, there has been a variety of resources with huge commercial value and social value, people can get huge benefits from these resources, but with increasing amounts of accumulation, people are increasing It is necessary to work hard to achieve a variety of purposes, including sharing content resources and corresponding privacy protection. At the same time, there may be a large number of sensitive content in these resources, including important personal privacy data and information, such as patient health care data collected by major hospitals, using the user location information collected by the Global Positioning System Protocol application, these Sensitive resources itself and new sensitive resources formed ...

AI Technical Summary

Problems solved by technology

At the same time, there may be a lot of sensitive content in these resources, including important personal privacy data and information, for example, patient health data collected by major hospitals, user location information collected by using GPS protocol applications, etc., these Sensitive resources themselves and the new sensitive resources formed after the correlation and fusion of related resources may lead to more frequent privacy leaks and privacy theft with more concealed and diverse data collection, storage and data mining, resulting in greater harm and impact , sparking widespread concerns and concerns about privacy

In the existing technology, the original type of resources released through the network and other channels without any processing has great risks in privacy protection. At present, the way to protect private resources is mostly manual decision-making. For example, by Administrators of virtual communities manually encrypt and protect private resources, which is less efficient and prone to errors

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