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This paper addresses a critical gap in the measurement and detection of browser fingerprinting, an invasive tracking technique used for profiling users online
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This paper tackles sybil detection from a graph-algorithms angle rather than as a pure machine-learning classification task
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This paper tackles a very specific bottleneck in forehead-crease biometrics: there are too few real identities and too little within-subject variation to train a verification system that generalize…
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This paper asks a practical security question that voting-based LLM leaderboards have mostly glossed over: if model identities are hidden during pairwise voting, can an adversary still learn which …
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This paper asks a practical question that keystroke-biometrics researchers often assume away: how much dataset breadth (number of subjects) and depth (samples per subject, sequence length, and trip…
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MagicMirror targets a specific bottleneck in personalized video generation: you want a subject’s identity to stay stable across frames, but you also want the video to move naturally instead of look…
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The Keystroke Verification Challenge - onGoing (KVC-onGoing) addresses the lack of standardized benchmarking protocols and large-scale, publicly accessible datasets for keystroke dynamics (KD) biom…
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This study addresses challenges in web crawling caused by webpage diversity and anti-scraping defenses by leveraging generative AI systems, specifically Claude AI (Sonnet 3.5) and ChatGPT-4.0, with…
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This paper addresses the critical challenge of improving Risk-based Authentication (RBA) systems by leveraging Federated Learning (FL) to enhance privacy, scalability, and adaptability
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The paper introduces the IMPROVE dataset, a novel, large-scale multimodal resource aimed at investigating how mobile phone usage affects learners in remote online education settings
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This position paper, produced by a large multidisciplinary team spanning Google/Jigsaw, Google DeepMind, MIT, Yale, Georgetown, Reddit, and multiple civil society organizations, argues that LLMs re…
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This paper addresses the escalating threat of automated web scanners that perform malicious activities like credential stuffing, command injection, and account hijacking at web scale, causing tens …
