Enhancing Autonomous System Security and Resilience With Generative AI: A Comprehensive Survey

IEEE Access, Год журнала: 2024, Номер 12, С. 109470 - 109493

Опубликована: Янв. 1, 2024

This survey explores the transformative role of Generative Artificial Intelligence (GenAI) in enhancing trustworthiness, reliability, and security autonomous systems such as Unmanned Aerial Vehicles (UAVs), self-driving cars, robotic arms. As edge robots become increasingly integrated into daily life critical infrastructure, complexity connectivity these introduce formidable challenges ensuring security, resilience, safety. GenAI advances from mere data interpretation to autonomously generating new data, proving complex, context-aware environments like robotics. Our delves impact technologies—including Adversarial Networks (GANs), Variational Autoencoders (VAEs), Transformer-based models, Large Language Models (LLMs)—on cybersecurity, decision-making, development resilient architectures. We categorize existing research highlight how technologies address operational innovate predictive maintenance, anomaly detection, adaptive threat response. comprehensive analysis distinguishes this work reviews by mapping out applications, challenges, technological advancements their on creating secure frameworks for systems. discuss significant future directions integrating within evolving landscape cyber-physical threats, underscoring potential make more adaptive, secure, efficient.

Язык: Английский

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Enhancing user experience and trust in advanced LLM-based conversational agents

Computing and artificial intelligence., Год журнала: 2024, Номер 2(2), С. 1467 - 1467

Опубликована: Авг. 17, 2024

This study explores the enhancement of user experience (UX) and trust in advanced Large Language Model (LLM)-based conversational agents such as ChatGPT. The research involves a controlled experiment comparing participants using an LLM interface with those traditional messaging app human consultant. results indicate that LLM-based offer higher satisfaction lower cognitive load, demonstrating potential for LLMs to revolutionize various applications from customer service healthcare consultancy shopping assistance. Despite these positive findings, also highlights significant concerns regarding transparency data security. Participants expressed need clearer understanding how process information make decisions. perceived opacity processes can hinder trust, especially sensitive healthcare. Additionally, robust protection measures are crucial ensure privacy foster systems. To address issues, future development should focus on enhancing operations strengthening security protocols. Providing users clear explanations their is used decisions made build greater trust. Moreover, specialized may require tailored solutions meet specific expectations regulatory requirements. In conclusion, while have demonstrated substantial advantages improving experience, addressing essential broader acceptance effective deployment. By focusing areas, developers create more trustworthy user-friendly AI systems, paving way integration into diverse fields everyday use.

Язык: Английский

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History, development, and principles of large language models: an introductory survey

AI and Ethics, Год журнала: 2024, Номер unknown

Опубликована: Окт. 14, 2024

Язык: Английский

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A Review of Advancements and Applications of Pre-Trained Language Models in Cybersecurity

Опубликована: Апрель 29, 2024

In this paper, we delve into the transformative role of pre-trained language models (PLMs) in cybersecurity, offering a comprehensive examination their deployment across wide array cybersecurity tasks. Beginning with an exploration general PLMs, including advancements and emergence domain-specific tailored for provide insightful overview foundational technologies driving these developments. The core our review focuses on multifaceted applications PLMs ranging from malware vulnerability detection to more nuanced areas like log analysis, network traffic threat intelligence, among others. We also highlight recent strides application large (LLMs), showcasing growing influence enhancing measures. By charting landscape PLM pointing toward future directions, work serves as valuable resource both research community industry practitioners, underlining critical need continued innovation harnessing fortify defenses.

Язык: Английский

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LLM-Based Edge Intelligence: A Comprehensive Survey on Architectures, Applications, Security and Trustworthiness

IEEE Open Journal of the Communications Society, Год журнала: 2024, Номер 5, С. 5799 - 5856

Опубликована: Янв. 1, 2024

Язык: Английский

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