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ORCID14th AISec@CCS 2021: Virtual Event, Korea
- Nicholas Carlini, Ambra Demontis, Yizheng Chen:
AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, Virtual Event, Republic of Korea, 15 November 2021. ACM 2021, ISBN 978-1-4503-8657-9 - Nicholas Carlini:
Session details: Session 1: Adversarial Machine Learning. - Antreas Dionysiou
, Elias Athanasopoulos:
Unicode Evil: Evading NLP Systems Using Visual Similarities of Text Characters. 1-12 - Luke E. Richards, André T. Nguyen, Ryan Capps, Steven Forsyth, Cynthia Matuszek, Edward Raff:
Adversarial Transfer Attacks With Unknown Data and Class Overlap. 13-24 - Chawin Sitawarin, Supriyo Chakraborty, David A. Wagner:
SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing. 25-36 - Zhanyuan Zhang, Yizheng Chen, David A. Wagner:
SEAT: Similarity Encoder by Adversarial Training for Detecting Model Extraction Attack Queries. 37-48 - Akshaj Kumar Veldanda, Kang Liu, Benjamin Tan, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, Brendan Dolan-Gavitt, Siddharth Garg:
NNoculation: Catching BadNets in the Wild. 49-60 - Nicholas Carlini:
Session details: Session 2A: Machine Learning for Cybersecurity. - Aviv Yehezkel, Eyal Elyashiv, Or Soffer:
Network Anomaly Detection Using Transfer Learning Based on Auto-Encoders Loss Normalization. 61-71 - Robert J. Joyce, Edward Raff, Charles Nicholas:
A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels. 73-84 - Chinmay Deshpande, David Gens, Michael Franz:
StackBERT: Machine Learning Assisted Static Stack Frame Size Recovery on Stripped and Optimized Binaries. 85-95 - Shawn Shan, Arjun Nitin Bhagoji, Haitao Zheng, Ben Y. Zhao:
Patch-based Defenses against Web Fingerprinting Attacks. 97-109 - Ambra Demontis:
Session details: Session 2B: Machine Learning for Cybersecurity. - Giuseppina Andresini, Feargus Pendlebury, Fabio Pierazzi, Corrado Loglisci, Annalisa Appice, Lorenzo Cavallaro:
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection. 111-122 - Zeliang Kan, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Investigating Labelless Drift Adaptation for Malware Detection. 123-134 - Jan Malte Hilgefort, Daniel Arp, Konrad Rieck:
Spying through Virtual Backgrounds of Video Calls. 135-144 - Tom Ganz, Martin Härterich, Alexander Warnecke, Konrad Rieck:
Explaining Graph Neural Networks for Vulnerability Discovery. 145-156 - Kalle Kujanpää, Willie Victor, Alexander Ilin:
Automating Privilege Escalation with Deep Reinforcement Learning. 157-168 - Jan Peter Drees, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, Juraj Somorovsky:
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! 169-180 - Yizheng Chen:
Session details: Session 3: Privacy-Preserving Machine Learning. - Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig:
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data. 181-192 - Shadi Rahimian, Tribhuvanesh Orekondy, Mario Fritz:
Differential Privacy Defenses and Sampling Attacks for Membership Inference. 193-202
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