Exposing the Impact of GenAI for Cybercrime: An Investigation into the Dark Side
원문 초록
In recent years, the rapid advancement and democratization of generative AI models have sparked significant debate over safety, ethical risks, and dual-use concerns, particularly in the context of cybersecurity. While anecdotally known, this paper provides empirical evidence regarding generative AI's association with malicious internet-related activities and cybercrime by examining the phenomenon through psychological frameworks of technological amplification and affordance theory. Using a quasi-experimental design with interrupted time series analysis, we analyze two datasets, one general and one cryptocurrency-focused, to empirically assess generative AI's role in cybercrime. The findings contribute to ongoing discussions about AI governance by balancing control and fostering innovation, underscoring the need for strategies to guide policymakers, inform AI developers and cybersecurity professionals, and educate the public to maximize AI's benefits while mitigating its risks.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Emergence of Functionally Differentiated Structures via Mutual Information Optimization in Recurrent Neural Networks
A Review of the Long Horizon Forecasting Problem in Time Series Analysis
The interplay of robustness and generalization in quantum machine learning
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.