Ransomware-Angriffe im Kontext der generativen künstlichen Intelligenz − eine experimentelle Studie

Author:

Teichmann FabianORCID

Abstract

AbstractRansomware attacks continue to be one of the biggest risks faced by both organizations and governments. In this experimental study, the author tested how criminals could use generative artificial intelligence (AI) for both the planning and implementation of ransomware attacks. It is found that criminals with very limited information technology (IT) knowledge may be enabled by chatbots using generative AI to carry out complex ransomware attacks. Furthermore, it is found that criminals with profound IT expertise but lacking other skills may be enabled by generative AI to draft more convincing phishing e‑mails. It is argued that the broad availability of generative AI could lead to an increase in both the number and the quality of ransomware attacks. Although previous studies have separately analyzed both ransomware attacks and generative AI, this article combines the two phenomena. The author uses criminological techniques and analyzes the potential use of AI from the perspective of a potential criminal. The risks identified in this article could serve as a foundation for further research in the fields of cybersecurity, IT law, and criminology.

Publisher

Springer Fachmedien Wiesbaden GmbH

Subject

Anesthesiology and Pain Medicine

Reference46 articles.

1. Almashhadani AO, Kaiiali M, Sezer S, O’Kane P (2019) A multi-classifier network-based crypto ransomware detection system: a case study of Locky ransomware. IEEE Access 7:47053–47067

2. Alotaibi FM, Vassilakis VG (2021) SDN-based detection of self-propagating ransomware: the case of BadRabbit. IEEE Access 9:28039–28058

3. Alzahrani S, Xiao Y, Sun W (2022) An analysis of Conti ransomware leaked source codes. IEEE Access 10:100178–100193

4. Aurangzeb S, Aleem M, Iqbal MA, Islam MA (2017) Ransomware: a survey and trends. J Inf Assur Secur 6(2):48–58

5. Baidoo-Anu D, Owusu Ansah L (2023) Education in the era of generative artificial intelligence (AI): understanding the potential benefits of ChatGPT in promoting teaching and learning (Available at SSRN 4337484.)

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