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Evaluation of multimodal biometric score fusion rules under spoof attacks.

, , , и . ICB, стр. 402-407. IEEE, (2012)

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Udo Röling

Hans Rolinger

Rudolf Roling

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Johannes Rolink

 

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Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware., , и . CoRR, (2022)Robustness analysis of likelihood ratio score fusion rule for multimodal biometric systems under spoof attacks., , , и . ICCST, стр. 1-8. IEEE, (2011)Information fusion for computer security: State of the art and open issues., , , , и . Inf. Fusion, 10 (4): 274-284 (2009)Slope: A First-order Approach for Measuring Gradient Obfuscation., , , , и . ESANN, (2021)Poisoning Behavioral Malware Clustering., , , , , , и . CoRR, (2018)An Experimental Analysis of the Relationship between Biometric Template Update and the Doddington's Zoo: A Case Study in Face Verification., , и . ICIAP, том 5716 из Lecture Notes in Computer Science, стр. 434-442. Springer, (2009)A Classification-Selection Approach for Self Updating of Face Verification Systems Under Stringent Storage and Computational Requirements., , , и . ICIAP (2), том 9280 из Lecture Notes in Computer Science, стр. 540-550. Springer, (2015)Evasion attacks against machine learning at test time, , , , , , , и . Joint European Conference on Machine Learning and Knowledge Discovery in Databases, стр. 387--402. Springer, (2013)On Security and Sparsity of Linear Classifiers for Adversarial Settings., , , , и . CoRR, (2017)Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks., , , , , , , и . USENIX Security Symposium, стр. 321-338. USENIX Association, (2019)