智能情报融合综述:对抗视角下的开源情报融合分析OACSTPCD
Research on intelligence fusion:a holistic analysis of open-source intelligence fusion from the perspective of confrontation
在"信息开放共享、万物互通互联"的数字社会,互联网中"海量、多源、爆炸式增长"的信息痕迹,为开源情报提供了富饶的"矿藏".自然语言处理和计算机视觉等先进人工智能技术赋能的情报处理,极大提升了情报产出效率,被广泛应用于安防领域.然而,以深度伪造为代表的生成式人工智能打开了人工智能的"潘多拉魔盒",不断被用于制造数字野火,投放虚假信息混淆视听,给智能情报融合带来巨大的挑战.为此,以开源情报为主要研究对象,深入分析开源情报特点和现有挑战;然后,综述先进人工智能技术在开源情报融合中的发展现状,从对抗视角总结现有的情报欺骗攻击方法和情报对抗防御方法;最后,提出未来智能情报融合新方向,旨在为可信情报融合分析提供借鉴,为智能态势分析与辅助决策提供支撑.
In the digital society of"open sharing of information and interconnection of everything",the information traces characterized with"massive,multi-source and explosive growth"in the internet provide rich"mineral deposits"for open-source intelligence collecting.Intelligence processing enabled by advanced artificial intelligence technologies,such as natural language processing and computer vision,greatly improves the efficiency of intelligence production and is widely used in the field of security.However,generative artificial intelligence represented by deepfake has opened the"Pan-dora's box"of artificial intelligence and is used to create digital wildfires and put false information,which confuse the public and bring crucial challenges to the integration of intelligent intelligence.This paper focuses on open-source intelli-gence and deeply analyzes its characteristics and existing challenges.Then,this paper summarizes the development of ad-vanced artificial intelligence technology in opensource intelligence fusion,summarizes the existing intelligence spoofing attack methods and intelligence anti-spoofing defense methods from the perspective of confrontation.Finally,new direc-tions of intelligence fusion in the future are proposed to provide reference for the trusted intelligence fusion and provide support for intelligent situation analysis and auxiliary decision making.
袁唯淋;赵卫伟;胡振震;曹巍;何俊;董绍进;王程远;王盛青
国防科技大学信息通信学院,湖北 武汉 430000国防科技大学智能科学学院,湖南 长沙 410073
计算机与自动化
开源情报融合情报欺骗攻击情报对抗防御深度造假舆情检测
open-source intelligence fusionintelligence spoofing attackintelligence anti-spoofing defensedeepfakepublic opinion detection
《智能科学与技术学报》 2024 (003)
284-300 / 17
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