Risk identification of personally identifiable information from collective mobile app data
AssigneeInje University Industry-Academic Cooperation Foundation
InventorsJinhong YANG, Chul Soo KIM, Nam Yong LEE, Md Mehedi Hassan ONIK
Life of this patent
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Abstract
Big data analytics is being used by many market participants. PII (Personally Identifiable Information) (e.g., age, race, social security number, address, etc.) plays a vital role in providing user-centric services. Many IT companies collect, store and process PII of their customers by means of various mobile applications. The example embodiments may explain how collective permission gathering through multiple Android applications by same publishers can disclose user's PII by using two new PII risk factors, and determine total risk factor for PII.
Claims11
A risk identification method for PII (Personally Identifiable Information) comprising:
- generating a profiling chart for identifying an application having privacy permission for PII and PPII (Potential Personally Identifiable Information);
- collecting privacy permission of an application identified through the profiling chart;
- identifying a first risk factor through total PPII collected by publisher of the application identified through the profiling chart;
- and
- identifying a second risk factor through total PPII collected by parent organization of the publisher;
- and
- determining total risk factor based on the first risk factor and the second risk factor.
A computer device comprising at least one processor implemented to execute a computer readable instruction, and
- wherein the computer device, by the at least one processor,
- generates a profiling chart for identifying an application having privacy permission for PII (Personal Identification Information) and PPII (Potential Personally Identifiable Information),
- collects privacy permission of an application identified through the profiling chart,
- identifies a first risk factor through total PPII collected by publisher of the application identified through the profiling chart,
- identifies a second factor through total PPII collected by parent organization of the publisher, and
- determines total risk factor based on the first risk factor and the second risk factor.
Dependencies are inferred from the claim text.