生成人工智能时代的网络安全：人工智能驱动的脆弱性评估和风险管理的系统分类法

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-08-28 DOI:10.1016/j.future.2025.108107

Seyedeh Leili Mirtaheri , Narges Movahed , Reza Shahbazian , Valerio Pascucci , Andrea Pugliese

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引用次数: 0

摘要

本文讨论了生成式人工智能（GenAI）对脆弱性评估（VA）和风险管理（RM）领域的变革性影响，从其生命周期的开始到网络安全（CS）的结束。通过对100多篇出版物（2021-2025）的系统回顾，我们对GenAI在VA/RM中的双重进攻和防御应用进行了综合分类。该调查阐明了GenAI的主要技术，也指出了具有挑战性的方面，包括安全性、可解释性和可信度。由此产生的研究结果强化了GenAI可以帮助解决许多传统的VA/RM挑战的信念，从而为该领域的研究和实践提供了肥沃的土壤。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Cybersecurity in the age of generative AI: A systematic taxonomy of AI-powered vulnerability assessment and risk management

The article discusses the transformative impact of Generative AI (GenAI) to the field of vulnerability assessment (VA) and risk management (RM) right from the beginning of their life cycle to the end in cybersecurity (CS). Through a systematic review of over 100 publications (2021-2025), we develop a comprehensive taxonomy classifying GenAI’s dual offensive and defensive applications in VA/RM. The survey spells out the dominant techniques of GenAI and also points towards challenging aspects, which include security, explainability, and trustworthiness. The resultant findings reinforce the belief that GenAI could help resolve many traditional VA/RM challenges, thus providing fertile ground for research and practice in this area.

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.