期刊
ARTIFICIAL INTELLIGENCE REVIEW
卷 56, 期 11, 页码 12407-12438出版社
SPRINGER
DOI: 10.1007/s10462-023-10454-y
关键词
Artificial intelligence; Open-source intelligence; Cyber security; Public data; Social networks; Deep learning
The amount of publicly available data generated by the digitally connected world today is enormous. Open-source intelligence (OSINT) is a method of extracting and gathering intelligence from various publicly available data sources, including web archives, public databases, and social networks such as Facebook, Twitter, LinkedIn, Emails, and Telegrams. OSINT is expanding rapidly and brings new artificial intelligence-based approaches to address issues in national security, political campaigns, the cyber industry, criminal profiling, society, and cyber threats and crimes. This paper provides an overview of the current state of OSINT tools/techniques and discusses its various applications in cybersecurity, as well as the challenges and future directions for developing autonomous models using machine learning, deep learning, and artificial intelligence with OSINT.
The volume of data generated by today's digitally connected world is enormous, and a significant portion of it is publicly available. These data sources are web archives, public databases, and social networks such as Facebook, Twitter, LinkedIn, Emails, Telegrams, etc. Open-source intelligence (OSINT) extracts information from a collection of publicly available and accessible data. OSINT can provide a solution to the challenges in extracting and gathering intelligence from various publicly available information and social networks. OSINT is currently expanding at an incredible rate, bringing new artificial intelligence-based approaches to address issues of national security, political campaign, the cyber industry, criminal profiling, and society, as well as cyber threats and crimes. In this paper, we have described the current state of OSINT tools/techniques and the state of the art for various applications of OSINT in cyber security. In addition, we have discussed the challenges and future directions to develop autonomous models. These models can provide solutions for different social network-based security, digital forensics, and cyber crime-based problems using various machine learning (ML), deep learning (DL) and artificial intelligence (AI) with OSINT.
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