开源情报:对网络安全当前状况,应用和未来前景的全面审查
Ashok Yadav1, Atul Kumar2, Vrijendra Singh1
1Department of Information Technology, Indian Institute of Information Technology Allahabad, Prayagraj, Uttar Pradesh 211015 India.
概括
开源情报 (OSINT) 利用大量的公共数据进行洞察. 本研究回顾了网络安全中的OSINT工具和AI应用,解决了数字取证和网络犯罪的挑战和未来的自主模型.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 数据科学数据科学数据科学
背景情况:
- 数字世界从社交网络,网络档案和公共数据库等来源产生了大量的公开可访问数据.
- 从这种数据洪流中提取可操作的情报带来了重大挑战.
- 开源情报 (OSINT) 为收集和分析这些信息提供了一个框架.
研究的目的:
- 审查开源情报 (OSINT) 工具和技术的当前状态.
- 探索OSINT在网络安全中的最先进应用.
- 讨论开发自主OSINT模型的挑战和未来方向.
主要方法:
- 对现有的OSINT工具和技术进行文献审查.
- 分析当前各领域的OSINT应用,特别是网络安全.
- 探索人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 对OSINT的方法.
主要成果:
- 随着人工智能驱动的新方法,OSINT正在迅速发展.
- OSINT应用涵盖国家安全,政治运动,网络行业,犯罪分析和社会问题.
- 目前的OSINT工具和技术正在通过AI增强网络安全.
结论:
- OSINT对于应对现代安全挑战至关重要,包括网络威胁和犯罪.
- 未来的研究应该专注于为OSINT开发自主AI/ML/DL模型.
- 这些先进的模型可以为社交网络安全,数字取证和网络犯罪调查提供有效的解决方案.
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