User Authentication and Security Systems

Neueste Paper

• Process Matters more than Output for Distinguishing Humans from Machines

  Milena Rmus, Mathew D. Hardy, Thomas L. Griffiths, Mayank Agrawal · 30. September 2026

  Reliable human-machine discrimination is becoming increasingly important as Large Language Models and autonomous agents are deployed in online settings. Existing approaches evaluate whether a system can produce responses indistinguishable from those of a human. This approach follows the focus on the…

• CaptchaArena: A Large-Scale, Fine-Grained Dataset for Training Computer-Use Agents on Interactive CAPTCHAs

  Zhenhao Zhang, Zhaoyu Fan, Haohan Ying, Jingwen Hu, Hancen Fan, Junhao Zhou, Zitian Chen, Linchao Zhu · 29. September 2026

  Interactive CAPTCHAs remain challenging for computer-use agents, while existing datasets face trade-offs among type coverage, interaction fidelity, and trajectory supervision. To address these gaps, we present CaptchaArena, the first large-scale, fine-grained training dataset for interactive CAPTCHA…

• Template Ageing and Longitudinal Verification in Fixed-Text Keystroke Dynamics: A Subject-Disjoint Study Across Eight Weeks

  Simon Parkinson, Saad Khan, Na Liu, Qing Xu · 25. September 2026

  Behavioural biometric templates are widely believed to degrade as the gap between enrolment and verification grows, but few studies measure this template ageing effect directly under controlled conditions. We collected a longitudinal dataset of 40 fixed passwords, each typed four times per weekly se…

• TP-CRIV: A Framework for Third-Party Challenge-Response Identity Verification of AI Models

  Teruki Sano, Minoru Kuribayashi, Masao Sakai, Shuji Isobe, Eisuke Koizumi, Zhang Zhang, Satoru Matsumoto · 25. September 2026

  Artificial intelligence (AI) models are increasingly deployed through remote services, making model misappropriation a growing concern. Existing approaches, including watermarking, fingerprinting, and model similarity analysis, primarily rely on predefined evidence or direct behavioral comparison an…

• Invisible in Space, Visible in Time: Motion Vision CAPTCHA against GUI Agents

  Zeyu Zhang, Dingyi Rong, Zijian Chen, Zicheng Zhang, Xiongkuo Min, Guangtao Zhai · 24. September 2026

  Most existing visual CAPTCHAs remain spatially solvable: the required information is exposed by static appearance, local structure, and interface state. This assumption is weakened by advances in multimodal large language models (MLLMs) and Graphical User Interface (GUI) agents, which exhibit strong…

• greCAPTCHA: Assessing Understanding as Evidence of Research Authorship Under Generative AI

  Justin Payan, B\'alint Gyevn\'ar, Atoosa Kasirzadeh, Nihar B. Shah · 18. September 2026

  Conferences, journals, funders, schools, and universities are struggling with a surge of potentially AI-generated submissions from ostensibly human authors, who may not have exercised sufficient human oversight for their manuscripts. In turn, institutions evaluating submissions can no longer reliabl…

• Same-Player Verification for Account Consistency in Counter-Strike 2

  Xuchen Zhang · 27. August 2026

  In competitive first-person shooter (FPS) games such as Counter-Strike 2 (CS2), account-integrity review often asks whether an account's recent behavior remains consistent with its historical operator. This consistency question arises in cases such as temporary substitution, rank boosting, and high-…

• Transfer Learning of Keystroke Dynamics for Cross-Device User Authentication

  Nuwan Kaluarachchi, Sevvandi Kandanaarachchi, Kristen Moore, Arathi Arakala, Conrad Sanderson · 18. August 2026

  Keystroke dynamics (typing patterns) can be used as a behavioural biometric modality for user authentication, with applications such as fraud prevention. While the modality has been shown to work well for single device authentication, its application to cross-device scenarios is more challenging. Dy…

• Behaviorally Adaptive Visual Diversion for Inclusive and Resilient Digital Assessment Delivery

  Gupta Lovi Raj, kaur Kamalpreet, Dama Sriram, Parali Prajithaa · 5. August 2026

  Institutions increasingly rely on browser lockdown, webcam monitoring, and behavioral analytics to secure high-stakes digital assessments, yet these mechanisms are commonly designed and evaluated independently and often overlook learner accessibility. This paper introduces Behaviorally-Adaptive Visu…

• Rendering on Real Silicon: GPU Render-Timing as a Passive, AI-Resistant CAPTCHA Signal

  David Noever, Forrest McKee · 28. Juli 2026

  Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or enrollment costs. We investigate an orthogonal signal: the physical timing behavior of a client's GPU under a controlled WebGL rendering workload. Un…

• Examining User Behavior and Cognitive Biases in Personal Password Security

  Evelyn Crowe, Patralika Ghosh, Shreyas Kumar, Rebecca Schlegel, Rebecca Ward, Guofei Gu · 23. Juli 2026

  Despite increasing awareness of cybersecurity risks, users continue to engage in insecure password practices, such as reusing passwords, choosing weak credentials, and neglecting security recommendations. The study explores the behavioral and cognitive factors that influence password decision-making…

• Inverse Reinforcement Learning for Interpretable Keystroke Biomarkers in Parkinson's Disease

  Navin Bondade · 2. Juli 2026

  Keystroke dynamics have been explored extensively as a passive digital biomarker for Parkinson's disease (PD), typically by extracting summary statistics from typing timing and training a classifier to discriminate PD from healthy controls. We instead apply inverse reinforcement learning (IRL) to ke…

• Inverse Reinforcement Learning for Interpretable Keystroke Biomarkers in Parkinson's Disease

  Navin Bondade · 25. Juni 2026

  Keystroke dynamics have been explored extensively as a passive digital biomarker for Parkinson's disease (PD), typically by extracting summary statistics from typing timing and training a classifier to discriminate PD from healthy controls. We instead apply inverse reinforcement learning (IRL) to ke…

• EERLoss: A Novel Loss Function for Training Deep Biometric Models. A Case Study in Keystroke Dynamics

  Nahuel Gonzalez, Marta Robledo-Moreno, Ivan DeAndres-Tame, Ruben Vera-Rodriguez, Ruben Tolosana · 24. Juni 2026

  Deep learning approaches to biometric verification are commonly trained by optimizing indirect objectives, creating a misalignment between the optimization process and the primary evaluation metric, typically the Equal Error Rate (EER). This paper introduces EERLoss: a subdifferentiable, arbitrarily…

• Continuous Behavioral Authentication via Multi-Expert BERT Log Analysis for Secure Data Sharing

  Stergios Lantzos, Ilias Syrigos, Apostolos Apostolaras, Thanasis Korakis · 23. Juni 2026

  Continuous authentication for mobile and zero-trust systems requires nonintrusive evidence confirming the enrolled user-device context remains valid after initial login. This paper presents a BERT log analysis framework for continuous behavioral authentication using Android system logs. The proposed…

• Capable but Careless: Do Computer-Use Agents Follow Contextual Integrity?

  Anmol Goel, Iryna Gurevych · 23. Juni 2026

  Computer-use agents (CUAs) now act on a user's behalf across personal applications such as email, calendars, and to-do lists. This cross-application access is useful, but it also creates a privacy risk that has been largely overlooked: when an agent works in one context, it can pull in information f…

• On the Identifiability of User Adaptation in Co-Adaptive Neural Interfaces

  Philip Waggoner · 23. Juni 2026

  We analyze identifiability in co-adaptive human-machine systems. We show that closed-loop encoder estimates do not uniquely identify user adaptation, but instead reflect properties of the joint system. We discuss implications for interpreting behavioral adaptation and propose conditions for identifi…

• Investigating Gender Bias in Touch Biometrics

  Joshua Lee, Ben Khant, Rajesh Kumar · 11. Juni 2026

  Behavioral biometrics offer a promising approach for continuous authentication, but their fairness across demographic groups remains largely unexplored. This paper investigates gender bias in swipe-based authentication using the BBMAS (117 users) and ANTAL (71 users) datasets and evaluates XGBoost a…

• TRL-Bench: Standardizing Cross-Paradigm Representation-Level Evaluation of Tabular Encoders

  Wei Pang, Xiangru Jian, Hehan Li, Zhixuan Yu, Alex Xue, Jinyang Li, Zhengyuan Dong, Xinjian Zhao, Hao Xu, Chao Zhang, Reynold Cheng, M. Tamer \"Ozsu, Tianshu Yu · 9. Juni 2026

  Tabular encoders are usually evaluated inside task-specific end-to-end pipelines, so models from different training paradigms are difficult to compare directly even when they operate on similar tabular signals. We introduce TRL-Bench, a multi-granular tabular representation learning (TRL) benchmark …

• Learning Behavioral Signals from Encrypted Smartphone Network Traffic

  Rameen Mahmood, Omar El Shahawy, Souptik Barua, Zachary Beattie, Jeffrey Kaye, Xuhai "Orson'' Xu, Chao-Yi Wu, Danny Yuxing Huang · 9. Juni 2026

  Human behavior is challenging to measure continuously at scale, yet traces of daily routines and well-being may be reflected in interactions with personal devices. We investigate whether encrypted smartphone network traffic can serve as a passive sensing signal for behavioral states related to sleep…

• HLL: Can Agents Cross Humanity's Last Line of Verification?

  Xinhao Song, Su Su, Sirui Song, Hongliang Wu, Wen Shen, Zhihua Wei, Gongshen Liu, Linfeng Zhang, Dongrui Liu · 2. Juni 2026

  Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute for humans in workflows that services deliberately protect against automation? CAPTCHA verification makes this question concrete. It is not merely a …

• HLL: Can Agents Cross Humanity's Last Line of Verification?

  Xinhao Song, Su Su, Sirui Song, Hongliang Wu, Wen Shen, Zhihua Wei, Gongshen Liu, Linfeng Zhang, Dongrui Liu · 2. Juni 2026

  Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute for humans in workflows that services deliberately protect against automation? CAPTCHA verification makes this question concrete. It is not merely a …

• Position: Retire the "Positive Backdoor" Label -- Secret Alignment Requires Strict and Systematic Evaluation

  Jianwei Li, Jung-Eun Kim · 28. Mai 2026

  This position paper argues that the AI/ML community should stop overclaiming and retire the label "positive backdoor," and instead treat trigger-activated hidden behaviors as Secret Alignment. Crucially, protective claims based on Secret Alignment should be presumed not secure by default unless supp…

• CaptchaMind: Training CAPTCHA Solvers via Reinforcement Learning with Explicit Reasoning Supervision

  Pengcheng Wang, Haoxiang Liu, Yang Dai, Xiangxiang Zeng, Guanhua Chen, Baotian Hu, Longyue Wang, Weihua Luo · 20. Mai 2026

  CAPTCHAs are widely deployed as human verification mechanisms and frequently block intelligent agents from completing end-to-end automation in real-world web environments. Solving modern CAPTCHAs requires robust multi-step visual reasoning and interaction capabilities, yet training-based approaches …

• BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

  Ishpuneet Singh, Gursmeep Kaur, Uday Pratap Singh Atwal, Guramrit Singh, Gurjot Singh, Maninder Singh · 18. Mai 2026

  Continuous authentication in high-stakes digital environments requires datasets with fine-grained behavioral signals under realistic cognitive and motor demands. But current benchmarks are often limited by small scale, unimodal sensing or lack of synchronised environmental context. To address this g…