Deep Learning Based Behavioral Drift Modeling for Continuous Biometric Authentication
This research proposes a two-level keystroke dynamics authentication system that provides defense-in-depth security thro
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共收录 84 条相关情报。
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Password-based authentication remains challenging for many users, especially for those who face usability and accessibil
Usable String Matching by Humans through Overlaid Presentation
We explore the ability of humans to compare strings, an error-prone activity which occurs in critical contexts (e.g., ba
Measuring Users' Security and Privacy Concerns About Third-Party Community Bots on Discord
Third-party community-based bots are central to how social platforms such as Discord work. They moderate content, manage
What Victims Take Away: Attack Reuse and Defense Revision after Prompt-Injection Attacks
Attack logs and red-team reports show targets the attacks used against them, to help them repair their defenses. Prompt
STROKE: Simple Sparse Structural Occlusions for Black-Box Adversarial Attacks
We introduce STROKE, a query-efficient score-based black-box adversarial attack that constructs perturbations from simpl
Can Loan Processors and Underwriters Spot AI-Edited Statements? An Empirical Study
AI-assisted editing can produce loan documents that preserve familiar issuer layouts while changing the applicant's iden
Data-Void Exploits in Web-Searching LLMs
Web-searching Large Language Models (LLMs) have changed how users seek online information: instead of sifting through ra
CAESAR: Mixed Reality Search-and-Rescue Platform for Cognitive Attack Evaluation
Mixed Reality (MR) enables immersive training by tightly coupling virtual content with the physical environment and supp
Act on Your Behalf, Beyond Your Authorization: Benchmarking LLM Agent Authorization Alignment
When an LLM agent acts on behalf of a user, it is expected to act within the authorization scope the user grants. Existi
When Care Expands and Control Declines: Understanding Digital Privacy in End-of-Life Care
Terminally ill patients generate extensive digital health data through hospital portals, physiological monitoring device
Collaborative Hand Drawing to Conceptualize Usable Privacy and Security Research Problems: Students' Perspectives (Extended Version)
In this paper, we explore students' perspectives on incorporating hand drawing to conceptualize usable privacy and secur
Bad Diagnosis: Analyzing Consent and Data Collection Practices of Mobile Medical Apps
Mobile health (mHealth) apps collect personally-identifiable information while handling uniquely sensitive medical data,
From GAN-Based Models to GPT-5: A Taxonomy-Guided Study of Human Performance in Detecting Deepfake Face Images
Generative models for deepfakes have rapidly evolved from GAN-based architectures to diffusion models and multimodal lar
CompanionSafe: From Multi-turn Safety Evaluation to Guardrails for AI Companions
AI companions provide users with emotional support and ongoing companionship, but their sustained relational interaction
The Amplifier Effect: Human-Factor Risks of AI-Suggested Correlation and Auto-Propagation in Multi-Framework GRC Self-Assessment
Multi-framework Governance, Risk and Compliance (GRC) platforms increasingly automate the link between an organisation's
Bounded Reasoning: Cognitive Hierarchy in Human-versus-AI Cyber Defense
Human-agent evaluations often compress interaction into a single performance score, even when human and automated polici
When Privacy Becomes a Weapon: Understanding Doxxing and Privacy Vulnerabilities in Mainland China's Social Media Ecosystem
本论文聚焦“人肉搜索”（doxxing，即恶意公开他人个人信息）这一日益普遍的隐私威胁，指出既有研究高度以西方语境为中心，难以解释在强制实名体系、平台治理机制与本土文化逻辑共同作用下，隐私风险与伤害路径如何被根本性重塑。为填补这一空白，作者
PrivacySkills: How Privacy Guidance Shapes Source Selection in LLM Agents
本文提出 PrivacySkills，一个受控评测框架，研究大语言模型智能体在信息获取路径选择上如何受隐私指引呈现方式影响。核心问题是：当多种获取路径能带来同等任务相关价值时——查询公开可得的个人信息、访问机密来源，或直接与用户交互——智能
You Can't Spot a Deepfake?And Neither Can Your Brain Nor Eyes: A Neurophysiological Framework for Deepfake Exploitation of Cognitive Engagement and Implicit Visual Evaluation
该论文从人因与神经生理学角度审视深度伪造（deepfake）对信息真实性与安全的威胁。作者指出，尽管深度伪造已被广泛视为利用人类对视听感知信任的攻击手段，但此前尚不清楚人类及其潜意识层面的神经生理过程能否可靠区分深度伪造视频与真实视频。为此