深度合成待证数据的风险剖析与辨识机制  

Risk Analysis and Identification Mechanism of Data Deep Synthesis to be Proved

作　　者：眭占菱 何亮亮 蒋洁 Sui Zhanling;He Liangliang;Jiang Jie

机构地区：[1]南京信息工程大学中意网络侵权研究所,江苏南京210044 [2]南京信息工程大学法政学院,江苏南京210044

出　　处：《图书与情报》2020年第6期59-64,共6页Library & Information

基　　金：国家社科基金项目“云环境中的取证问题研究”(项目编号:15CFX029);司法部国家法治建设与法学理论研究项目“大数据背景下电子取证问题研究”(项目编号:15SFB3018)研究成果之一。

摘　　要：数字经济新产业、新业态和新模式获得加速培育的全新场景下,渗透千行百业的数据信息深度合成技术在提高生产效率、改善生活质量、助力经济社会发展的同时,众多恶意应用亦严重威胁个人权益、政治安全、社会稳定和国家安全等等。文章从深度合成数据的概念与类型入手,结合待证数据的特质与现行采信模式,集中探讨了深度合成待证数据影响鉴真算法实效、引发涟漪式信任衰退、威胁安全体系等关键性风险,进而提出严格遏止源头违规、重塑专家鉴定模式、加强环境经验支撑等一系列健全辨识机制的方式方法。On one hand,the technology of data deep synthesis,which has been used in thousands of industries,improves the production efficiency and the quality of life,and helps the economic and social development.On the other hand,many malicious applications also seriously threaten personal rights,political security,social stability and national security.This paper starts with the concept and classification of data deep synthetic,combined with the characteristics of data to be proved and the current criteria of the accepting,focuses on the key risks in affecting the effectiveness of authentication algorithm,causing trust decline,infringing personal rights and interests,and threatening the security system.Then,it put forward a series of methods,such as strictly curbing source violations,reshaping the expert witness,and strengthening the supporting mechanism of circumstantial experience.

关 键 词：深度合成 待证数据 风险剖析 辨识机制 

分 类 号：G250.2[文化科学—图书馆学]