A bibliometric review of large language models research from 2017 to 2023

L Fan, L Li, Z Ma, S Lee, H Yu, L Hemphill - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) are a class of language models that have demonstrated
outstanding performance across a range of natural language processing (NLP) tasks and …

Cybersecurity of smart inverters in the smart grid: A survey

Y Li, J Yan - IEEE Transactions on Power Electronics, 2022 - ieeexplore.ieee.org
The penetration of distributed energy resources (DERs) in smart grids significantly increases
the number of field devices owned and controlled by consumers, aggregators, third parties …

Ai-generated content (aigc): A survey

J Wu, W Gan, Z Chen, S Wan, H Lin - arXiv preprint arXiv:2304.06632, 2023 - arxiv.org
To address the challenges of digital intelligence in the digital economy, artificial intelligence-
generated content (AIGC) has emerged. AIGC uses artificial intelligence to assist or replace …

[PDF][PDF] Large language models can be used to effectively scale spear phishing campaigns

J Hazell - arXiv preprint arXiv:2305.06972, 2023 - newsletter.radensa.ru
Recent progress in artificial intelligence (AI), particularly in the domain of large language
models (LLMs), has resulted in powerful and versatile dual-use systems. Indeed, cognition …

[HTML][HTML] Cyber security threats: A never-ending challenge for e-commerce

X Liu, SF Ahmad, MK Anser, J Ke, M Irshad… - Frontiers in …, 2022 - frontiersin.org
This study explores the challenge of cyber security threats that e-commerce technology and
business are facing. Technology applications for e-commerce are attracting attention from …

Anatomy of an AI-powered malicious social botnet

KC Yang, F Menczer - arXiv preprint arXiv:2307.16336, 2023 - arxiv.org
Large language models (LLMs) exhibit impressive capabilities in generating realistic text
across diverse subjects. Concerns have been raised that they could be utilized to produce …

The wmdp benchmark: Measuring and reducing malicious use with unlearning

N Li, A Pan, A Gopal, S Yue, D Berrios, A Gatti… - arXiv preprint arXiv …, 2024 - arxiv.org
The White House Executive Order on Artificial Intelligence highlights the risks of large
language models (LLMs) empowering malicious actors in developing biological, cyber, and …

[HTML][HTML] The dual role of artificial intelligence in developing smart cities

ME Zamponi, E Barbierato - Smart Cities, 2022 - mdpi.com
Defining smart city pillars, and their nature and essence, continues to be debated in the
scientific literature. The vast amount of information collected by electronic devices, often …

[HTML][HTML] Security-Informed safety analysis of autonomous transport systems considering ai-powered cyberattacks and protection

O Illiashenko, V Kharchenko, I Babeshko, H Fesenko… - Entropy, 2023 - mdpi.com
The entropy-oriented approach called security-or cybersecurity-informed safety (SIS or
CSIS, respectively) is discussed and developed in order to analyse and evaluate the safety …

AI-driven cloud security: Examining the impact of user behavior analysis on threat detection

SO Olabanji, Y Marquis, CS Adigwe… - Asian Journal of …, 2024 - papers.ssrn.com
This study explores the comparative effectiveness of AI-driven user behavior analysis and
traditional security measures in cloud computing environments. It specifically examines their …