相关论文: Enhancing Security Control Production With Generat…

Various studies have studied the impact of Generative AI on Computing Education. However, they have focused on the implications for novice programmers. In this experience report, we analyze the use of GenAI as a support tool for learning,…

Generative Artificial Intelligence (AI) has seen mainstream adoption lately, especially in the form of consumer-facing, open-ended, text and image generating models. However, the use of such systems raises significant ethical and safety…

The use of generative AI (GenAI) tools has fundamentally transformed software development. Central to this shift is prompt engineering, the practice of crafting textual prompts to guide GenAI tools in generating useful content. Although…

Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content. Beyond content creation, GAI has significant analytical abilities…

Generative artificial intelligence (GenAI) is increasingly used for programming, yet it remains unclear when and where GenAI tools lead to productivity gains. Evidence on the effects of GenAI on the long-term development of programming…

Educators and learners worldwide are embracing the rise of Generative Artificial Intelligence (GenAI) as it reshapes higher education. However, GenAI also raises significant privacy and security concerns, as models and privacy-sensitive…

Generative AI (GenAI) is reshaping enterprise architecture work in agile software organizations, yet evidence on its effects remains scattered. We report a systematic literature review (SLR), following established SLR protocols of…

Modern Integrated Circuits (ICs) are becoming increasingly complex, and so is their development process. Hardware design verification entails a methodical and disciplined approach to the planning, development, execution, and sign-off of…

Generative Artificial Intelligence (GenAI) applies models and algorithms such as Large Language Model (LLM) and Foundation Model (FM) to generate new data. GenAI, as a promising approach, enables advanced capabilities in various…

Generative-AI (GenAI), a novel technology capable of producing various types of outputs, including text, images, and videos, offers significant potential for wireless communications. This article introduces the concept of strategic…

Since 2022, generative AI (genAI) has rapidly become integrated into workplaces. Though organizations have made commitments to use this technology "responsibly", how organizations and their employees prioritize responsibility in their…

Generative artificial intelligence (GenAI) is shifting from conversational assistants toward agentic systems -- autonomous decision-making systems that sense, decide, and act within operational workflows. This shift creates an autonomy…

The rapid development of generative AI has brought value- and ethics-related risks to the forefront, making value safety a critical concern while a unified consensus remains lacking. In this work, we propose an internationally inclusive and…

AI-assisted software generation has increased development speed, but it has also amplified a persistent engineering problem: systems that are functionally correct may still be structurally insecure. In practice, prompt-based security review…

Generative AI has made significant strides, yet concerns about the accuracy and reliability of its outputs continue to grow. Such inaccuracies can have serious consequences such as inaccurate decision-making, the spread of false…

This paper provides a comprehensive analysis of Generative AI (GenAI) potential to revolutionise software coding through increased efficiency and reduced time span for writing code. It acknowledges the transformative power of GenAI in…

As generative large model capabilities advance, safety concerns become more pronounced in their outputs. To ensure the sustainable growth of the AI ecosystem, it's imperative to undertake a holistic evaluation and refinement of associated…

Machine Learning and data mining techniques (i.e. supervised and unsupervised techniques) are used across domains to detect user safety violations. Examples include classifiers used to detect whether an email is spam or a web-page is…

Neural networks are often used to process information from image-based sensors to produce control actions. While they are effective for this task, the complex nature of neural networks makes their output difficult to verify and predict,…

Administrator-centered access control failures can cause data breaches, putting organizations at risk of financial loss and reputation damage. Existing graphical policy configuration tools and automated policy generation frameworks attempt…