5G 기반 고정밀 측위 빅데이터 활용을 위한 위치정보 프라이버시 보호 기법 제안
A Proposal of Privacy Protection Method for Location Information to Utilize 5G-Based High-Precision Positioning Big Data
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초록
향후 5G 기술은 4차산업시대를 견인하는 핵심 인프라가 될 것이며, 지능화된 초융합 서비스를 위해서는 위치정보 등 다양한 개인정보의 수집이 필요할 것이다. 특히, 자율주행차 등 높은 품질의 서비스 제공을 위해서는 고정밀측위 데이터가 요구된다. 만약 특정 고정밀 위치정보가 악의를 가진 자에 의해 노출될 경우, 심각한 프라이버시 위험이 발생할 수 있다. 그러나 기존의 암호화, 더미 위치생성, 난독화 등의 위치정보보호 기법은 빅데이터 수집을 위한 정확성 유지 및 통계처리 등에서 한계점이 있다. 따라서 본 논문에서는 위치정보를 노출시키지 않은 상태에서 통계질의 및 데이터 분석이 가능한 새로운 기법을 제안하였다. 제안한 방식은 랜덤 영역 버킷화와 다항식 기반의 변환처리를 통하여 원본을 재식별할 수 없도록 한다. 또한, 원본 데이터의 품질을 훼손하지 않으므로 고정밀 측위 빅데이터의 활용성을 극대화할 수 있다는 장점이 있다.
Abstract
In the future, 5G technology will become the core infrastructure driving the 4th industrial era. For intelligentsuper-convergence service, it will be necessary to collect various personal information such as location data. If a person'shigh-precision location information is exposed by a malicious person, it can be a serious privacy risk. In the past, variousapproaches have been researched through encryption and obfuscation to protect location information privacy. In this paper,we proposed a new technique that enables statistical query and data analysis without exposing location information. Theproposed method does not allow the original to be re-identified through polynomial-based transform processing. In addition,since the quality of the original data is not compromised, the usability of positioning big data can be maximized
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