大数据 ›› 2023, Vol. 9 ›› Issue (5): 150-173.doi: 10.11959/j.issn.2096-0271.2023066
曹娟1,2, 朱勇椿1,2, 亓鹏1,2, 黄子尧1,2, 杨天韵1,2, 王政嘉1,2, 卜语嫣1,2
出版日期:
2023-09-15
发布日期:
2023-09-01
作者简介:
曹娟(1980- ),女,博士,中国科学院计算技术研究所研究员、前瞻研究实验室主任、数字内容合成与伪造检测实验室主任,中国科学院大学岗位教授,中国科学院计算技术研究所“十四五”规划重点研究方向“数字内容合成与伪造检测”方向牵头人。主要从事多媒体数字内容分析与伪造检测相关的研究工作。作为第一完成人,成果入选2022年世界互联网大会领先科技成果;获得2020年北京市科学技术进步奖一等奖、2020年北京市三八红旗奖章及2021年中国人工智能大赛“创新人物”和“创新之星”称号。作为项目负责人,围绕多媒体内容安全方向承担十余项国家级重要课题基金资助:
Juan CAO1,2, Yongchun ZHU1,2, Peng QI1,2, Ziyao HUANG1,2, Tianyun YANG1,2, Zhengjia WANG1,2, Yuyan BU1,2
Online:
2023-09-15
Published:
2023-09-01
Supported by:
摘要:
近年来,数字生成内容技术得到了极大的发展,数字内容的检测和取证技术面临新的挑战。首先从自然语言大模型、视觉生成技术、多模态生成技术3个方面介绍数字内容生成技术,从生成文本检测、生成图片检测、生成音视频检测3个方面介绍数字内容检测技术,从利用事实信息和伪造痕迹两方面介绍数字内容取证技术;接着介绍这些技术的应用场景;最后对该研究领域的未来工作进行展望,指出几个需要重点关注的方向。
中图分类号:
曹娟, 朱勇椿, 亓鹏, 黄子尧, 杨天韵, 王政嘉, 卜语嫣. 数字内容生成、检测与取证技术综述[J]. 大数据, 2023, 9(5): 150-173.
Juan CAO, Yongchun ZHU, Peng QI, Ziyao HUANG, Tianyun YANG, Zhengjia WANG, Yuyan BU. A survey on digital content generation, detection, and forensics techniques[J]. Big Data Research, 2023, 9(5): 150-173.
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