A systematic review on research utilising artificial intelligence for open source intelligence (OSINT) applications

IF 2.4 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Information Security Pub Date : 2024-06-05 DOI:10.1007/s10207-024-00868-2

Thomas Oakley Browne, Mohammad Abedin, Mohammad Jabed Morshed Chowdhury

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Abstract

This paper presents a systematic review to identify research combining artificial intelligence (AI) algorithms with Open source intelligence (OSINT) applications and practices. Currently, there is a lack of compilation of these approaches in the research domain and similar systematic reviews do not include research that post dates the year 2019. This systematic review attempts to fill this gap by identifying recent research. The review used the preferred reporting items for systematic reviews and meta-analyses and identified 163 research articles focusing on OSINT applications leveraging AI algorithms. This systematic review outlines several research questions concerning meta-analysis of the included research and seeks to identify research limitations and future directions in this area. The review identifies that research gaps exist in the following areas: Incorporation of pre-existing OSINT tools with AI, the creation of AI-based OSINT models that apply to penetration testing, underutilisation of alternate data sources and the incorporation of dissemination functionality. The review additionally identifies future research directions in AI-based OSINT research in the following areas: Multi-lingual support, incorporation of additional data sources, improved model robustness against data poisoning, integration with live applications, real-world use, the addition of alert generation for dissemination purposes and incorporation of algorithms for use in planning.

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关于利用人工智能进行开源情报（OSINT）应用研究的系统性综述

本文介绍了一项系统性综述，旨在确定将人工智能（AI）算法与开源情报（OSINT）应用和实践相结合的研究。目前，研究领域缺乏对这些方法的汇编，类似的系统综述也不包括2019年以后的研究。本系统综述试图通过确定最新研究来填补这一空白。该综述使用了系统综述和荟萃分析的首选报告项目，并确定了 163 篇研究文章，重点关注利用人工智能算法的 OSINT 应用。本系统综述概述了有关对所纳入研究进行荟萃分析的几个研究问题，并试图确定该领域的研究局限性和未来方向。综述发现以下领域存在研究空白：将已有的 OSINT 工具与人工智能相结合、创建适用于渗透测试的基于人工智能的 OSINT 模型、未充分利用替代数据源以及整合传播功能。此外，审查还确定了基于人工智能的 OSINT 研究在以下领域的未来研究方向：多语言支持、纳入更多数据源、提高模型对数据中毒的稳健性、与实时应用集成、实际应用、为传播目的添加警报生成功能以及纳入用于规划的算法。

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来源期刊

International Journal of Information Security 工程技术-计算机：理论方法

CiteScore

6.30

自引率

3.10%

发文量

审稿时长

12 months

期刊介绍： The International Journal of Information Security is an English language periodical on research in information security which offers prompt publication of important technical work, whether theoretical, applicable, or related to implementation. Coverage includes system security: intrusion detection, secure end systems, secure operating systems, database security, security infrastructures, security evaluation; network security: Internet security, firewalls, mobile security, security agents, protocols, anti-virus and anti-hacker measures; content protection: watermarking, software protection, tamper resistant software; applications: electronic commerce, government, health, telecommunications, mobility.