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ORCID13th AISec@CCS 2020: Virtual Event, Korea
- Jay Ligatti, Xinming Ou:
AISec@CCS 2020: Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security, Virtual Event, USA, 13 November 2020. ACM 2020, ISBN 978-1-4503-8094-2 - Chang Liao, Yao Cheng, Chengfang Fang, Jie Shi:
Where Does the Robustness Come from?: A Study of the Transformation-based Ensemble Defence. 1-12 - Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross J. Anderson:
Towards Certifiable Adversarial Sample Detection. 13-24 - An Ju, David A. Wagner:
E-ABS: Extending the Analysis-By-Synthesis Robust Classification Model to More Complex Image Domains. 25-36 - Jesus Solano, Christian Lopez, Esteban Rivera, Alejandra Castelblanco
, Lizzy Tengana, Martín Ochoa:
SCRAP: Synthetically Composed Replay Attacks vs. Adversarial Machine Learning Attacks against Mouse-based Biometric Authentication. 37-47 - Michael R. Smith, Nicholas T. Johnson, Joe B. Ingram, Armida J. Carbajal, Bridget I. Haus, Eva Domschot, Ramyaa, Christopher C. Lamb, Stephen J. Verzi, W. Philip Kegelmeyer:
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis. 49-60 - Sicco Verwer, Azqa Nadeem, Christian A. Hammerschmidt, Laurens Bliek, Abdullah Al-Dujaili, Una-May O'Reilly:
The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search. 61-70 - Edward Raff, Richard Zak, Gary Lopez Munoz, William Fleming, Hyrum S. Anderson, Bobby Filar, Charles Nicholas, James Holt:
Automatic Yara Rule Generation Using Biclustering. 71-82 - Carlos Novo, Ricardo Morla:
Flow-based Detection and Proxy-based Evasion of Encrypted Malware C2 Traffic. 83-91 - Alexander Schlögl, Rainer Böhme:
eNNclave: Offline Inference with Model Confidentiality. 93-104 - Esteban Rivera, Lizzy Tengana, Jesus Solano, Alejandra Castelblanco, Christian Lopez, Martín Ochoa:
Risk-based Authentication Based on Network Latency Profiling. 105-115 - Kota Yoshida, Takeshi Fujino:
Disabling Backdoor and Identifying Poison Data by using Knowledge Distillation in Backdoor Attacks on Deep Neural Networks. 117-127
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