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Roberto Jordaney
Roberto Jordaney
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{TESSERACT}: Eliminating experimental bias in malware classification across space and time
F Pendlebury, F Pierazzi, R Jordaney, J Kinder, L Cavallaro
28th USENIX security symposium (USENIX Security 19), 729-746, 2019
3942019
Transcend: Detecting concept drift in malware classification models
R Jordaney, K Sharad, SK Dash, Z Wang, D Papini, I Nouretdinov, ...
26th USENIX security symposium (USENIX security 17), 625-642, 2017
3192017
Conformal clustering and its application to botnet traffic
G Cherubin, I Nouretdinov, A Gammerman, R Jordaney, Z Wang, D Papini, ...
Statistical Learning and Data Sciences: Third International Symposium, SLDS …, 2015
262015
Misleading metrics: On evaluating machine learning for malware with confidence
R Jordaney, Z Wang, D Papini, I Nouretdinov, L Cavallaro
Tech. Rep., 2016
202016
Enabling fair ml evaluations for security
F Pendlebury, F Pierazzi, R Jordaney, J Kinder, L Cavallaro
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018
112018
POSTER: Enabling Fair ML Evaluations for Security
F Pendlebury, F Pierazzi, R Jordaney, J Kinder, L Cavallaro
CCS. ACM, 2018
32018
Poster misleading metrics: On evaluating ml for malware with confidence
R Jordaney, Z Wang, D Papini, I Nouretdinov, K Sharad, L Cavallaro
Proceedings of the 37th IEEE Symposium on Security and Privacy (Oakland)(San …, 2016
12016
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
Z Kan, S McFadden, D Arp, F Pendlebury, R Jordaney, J Kinder, ...
arXiv preprint arXiv:2402.01359, 2024
2024
Machine Learning Techniques for Evolving Threats
L Cavallaro, R Jordaney
2019
POSTER: Enabling Fair ML Evaluations for Security {References for Poster Timeline}
F PENDLEBURY, F PIERAZZI, R JORDANEY, J KINDER
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Artículos 1–10