基于风险等级的块网络图像隐私信息去识别机制

Q4 Mathematics
Jinsu Kim, Sungwoo Jung, S. Oh, Won-Chi Jung, Doik Hyun, Yujin Jung, Eunsun Choi, Namje Park
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引用次数: 0

摘要

随着社会的发展,对个人安全的保护变得越来越重要。特别是个人信息的泄露,即可以从个人身上推断出的信息,是一个对社会造成巨大影响的大话题。为了加强对个人信息的保护,视频系统非常重视录制的视频信息或个人信息,并正在进行大量的研究,以防止其泄露或从泄露的数据中识别目标。然而,记录的信息可能包括罪犯,也可能包括普通人。在某些情况下,并不要求对所有罪犯披露个人信息,但根据犯罪主体的风险需要披露一些信息。本文研究了在基于区块链的数据记录环境中应用风险依赖非识别的机制,以增强基于目标风险信息的去识别过程中数据的可靠性,无论其是否犯罪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
De-identification Mechanism of Block Network Image Privacy Information based on Risk Level
As society develops, the protection of individual safety is becoming increasingly important. In particular, the leakage of personal information, which means information that can be inferred from individuals, is a big topic that has caused a huge impact on society. In order to strengthen the protection of personal information, the video system pays a lot of attention to recorded video information or personal information, and a lot of research is being conducted to prevent it from being leaked or to identify the target from the leaked data. However, the recorded information may include criminals as well as ordinary people. There are also cases where personal information is not required to be disclosed for all criminals, but some disclosure is required depending on the risk of the subject. In this paper, we study the mechanism of applying risk-dependent non-identification in a blockchain-based data recording environment to enhance the reliability of data in the process of de-identification based on target risk information and whether it is criminal or not.
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CiteScore
0.30
自引率
0.00%
发文量
2
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