Research on intelligence fusion: a holistic analysis of open-source intelligence fusion from the perspective of confrontation

Autor: YUAN Weilin, ZHAO Weiwei, HU Zhenzhen, CAO Wei, HE Jun, DONG Shaojin, WANG Chengyuan, WANG Shengqing
Jazyk: čínština
Rok vydání: 2024
Předmět:
Zdroj: 智能科学与技术学报, Vol 6, Pp 284-300 (2024)
Druh dokumentu: article
ISSN: 2096-6652
DOI: 10.11959/j.issn.2096-6652.202429
Popis: 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 "Pandora'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 intelligence and deeply analyzes its characteristics and existing challenges. Then, this paper summarizes the development of advanced 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 directions 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.
Databáze: Directory of Open Access Journals