This study investigates user perceptions of privacy risks associated with GenAI smartphones, finding that users express heightened concerns across the entire data lifecycle and suggest comprehensive,…

This study examines the impact of Microsoft 365 Copilot adoption on employee acceptance in a state Department of Transportation using a matched two-wave survey.

This study proposes a negotiation framework, using composite indices (RBTI and CATI), to explain how youth navigate competing privacy pressures when using smart voice assistants, finding that high usa…

This paper analyzes online developer discussions to identify four major security concerns—data leakage, code licensing, adversarial attacks, and insecure suggestions—associated with using generative A…

The study evaluated text-based explanations of Trusted Execution Environments (TEEs) to non-experts, finding that while non-technical explanations improved understanding, they did not significantly in…

This paper investigates how Generative AI enables scalable, hyper-realistic fraud in Chinese e-commerce by fabricating product defect evidence, proposing new defense mechanisms like verifiable materia…

The paper investigates how AI coding assistants shift developers' security focus from proactive prevention to reactive review, finding that this structural change is reinforced by current tool interac…

Two student cohorts designed cognitively accessible GenAI interfaces, leading to structural and experiential scaffolding concepts.

The paper introduces Privacy Detective, a game that trains developers on privacy awareness using real-world legal documents.

This paper identifies and categorizes digital security and privacy questions asked to large language models using a dataset of user-LLM conversations, and evaluates the response quality and consistenc…

This paper analyzes the shift in student adoption and accountability practices of GenAI tools in a graduate-level HCI prototyping course across three cohorts using GitHub data.

The paper addresses the lack of user understanding regarding the actions and residual effects of advanced computer-use agents by proposing AgentTrace, a traceability framework for visualizing agent be…

The paper analyzes the escalating security and safety threats posed by generative AI systems as they transition from merely generating content to executing real-world actions via tools and agents, fin…

This survey proposes a proactive, lifecycle-based framework, utilizing the C5 Interaction Model, to detect emerging adversarial synthetic narratives generated by GenAI, moving beyond traditional react…

This survey proposes a proactive, lifecycle-based framework, utilizing the C5 Interaction Model, to detect emerging adversarial synthetic narratives generated by Generative AI, moving beyond tradition…

Despite having access to web search, users' reliance on conversational AI for information remains high, driven primarily by pre-existing trust and influenced indirectly by the chatbot's conversational…

The paper argues that LLM agent security is fundamentally an agent-human interaction (AHI) problem, demonstrating that industry practices rely on human-centric mechanisms while academic research focus…

The paper proposes using Differentially Private (DP) synthetic data, specifically through tabular synthesis and DP-Seeded Agent-Based Modeling (ABM), to resolve the conflict between data utility and p…

The paper reports on penetration tests conducted on proprietary, large-scale AI agent systems, finding that security vulnerabilities persist despite stricter development standards.

This paper investigates the practical barriers preventing the trustworthy deployment of AI-driven Cyber Threat Intelligence (CTI) in the highly regulated financial sector, identifying four key socio-t…