Large Language Models in Cyberattacks

IF 0.5 4区 数学 Q3 MATHEMATICS
S. V. Lebed, D. E. Namiot, E. V. Zubareva, P. V. Khenkin, A. A. Vorobeva, D. A. Svichkar
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引用次数: 0

Abstract

The article provides an overview of the practice of using large language models (LLMs) in cyberattacks. Artificial intelligence models (machine learning and deep learning) are applied across various fields, with cybersecurity being no exception. One aspect of this usage is offensive artificial intelligence, specifically in relation to LLMs. Generative models, including LLMs, have been utilized in cybersecurity for some time, primarily for generating adversarial attacks on machine learning models. The analysis focuses on how LLMs, such as ChatGPT, can be exploited by malicious actors to automate the creation of phishing emails and malware, significantly simplifying and accelerating the process of conducting cyberattacks. Key aspects of LLM usage are examined, including text generation for social engineering attacks and the creation of malicious code. The article is aimed at cybersecurity professionals, researchers, and LLM developers, providing them with insights into the risks associated with the malicious use of these technologies and recommendations for preventing their exploitation as cyber weapons. The research emphasizes the importance of recognizing potential threats and the need for active countermeasures against automated cyberattacks.

Abstract Image

网络攻击中的大型语言模型
本文概述了在网络攻击中使用大型语言模型(llm)的实践。人工智能模型(机器学习和深度学习)应用于各个领域,网络安全也不例外。这种用法的一个方面是攻击性人工智能,特别是与法学硕士相关的人工智能。包括法学硕士在内的生成模型已经在网络安全领域使用了一段时间,主要用于对机器学习模型产生对抗性攻击。分析的重点是llm(如ChatGPT)如何被恶意行为者利用来自动创建网络钓鱼电子邮件和恶意软件,从而大大简化和加速进行网络攻击的过程。法学硕士使用的关键方面进行了检查,包括社会工程攻击的文本生成和恶意代码的创建。本文针对网络安全专业人员、研究人员和法学硕士开发人员,为他们提供与恶意使用这些技术相关的风险的见解,以及防止其被利用为网络武器的建议。该研究强调了识别潜在威胁的重要性,以及对自动网络攻击采取主动对策的必要性。
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来源期刊
Doklady Mathematics
Doklady Mathematics 数学-数学
CiteScore
1.00
自引率
16.70%
发文量
39
审稿时长
3-6 weeks
期刊介绍: Doklady Mathematics is a journal of the Presidium of the Russian Academy of Sciences. It contains English translations of papers published in Doklady Akademii Nauk (Proceedings of the Russian Academy of Sciences), which was founded in 1933 and is published 36 times a year. Doklady Mathematics includes the materials from the following areas: mathematics, mathematical physics, computer science, control theory, and computers. It publishes brief scientific reports on previously unpublished significant new research in mathematics and its applications. The main contributors to the journal are Members of the RAS, Corresponding Members of the RAS, and scientists from the former Soviet Union and other foreign countries. Among the contributors are the outstanding Russian mathematicians.
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