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ORCIDASHES@CCS 2021: Virtual Event, Korea
- Chip-Hong Chang, Ulrich Rührmair, Stefan Katzenbeisser, Debdeep Mukhopadhyay:
ASHES@CCS 2021: Proceedings of the 5th Workshop on Attacks and Solutions in Hardware Security, Virtual Event, Republic of Korea, 19 November 2021. ACM 2021, ISBN 978-1-4503-8662-3 - Farinaz Koushanfar:
Machine Learning on Encrypted Data: Hardware to the Rescue. 1 - Ruby B. Lee:
Speculative Execution Attacks and Hardware Defenses. 3 - Calvin Deutschbein
, Andres Meza, Francesco Restuccia, Ryan Kastner, Cynthia Sturton:
Isadora: Automated Information Flow Property Generation for Hardware Designs. 5-15 - Thilo Krachenfels, Jean-Pierre Seifert, Shahin Tajik:
Trojan Awakener: Detecting Dormant Malicious Hardware Using Laser Logic State Imaging. 17-27 - Kunihiro Kuroda, Yuta Fukuda, Kota Yoshida, Takeshi Fujino:
Practical Aspects on Non-profiled Deep-learning Side-channel Attacks against AES Software Implementation with Two Types of Masking Countermeasures including RSM. 29-40 - Wenye Liu, Chip-Hong Chang:
A Forward Error Compensation Approach for Fault Resilient Deep Neural Network Accelerator Design. 41-50 - Kalle Ngo, Elena Dubrova, Thomas Johansson:
Breaking Masked and Shuffled CCA Secure Saber KEM by Power Analysis. 51-61 - Tatsuya Oyama, Shunsuke Okura, Kota Yoshida, Takeshi Fujino:
Backdoor Attack on Deep Neural Networks Triggered by Fault Injection Attack on Image Sensor Interface. 63-72 - Aurélien Vasselle, Hugues Thiebeauld, Philippe Maurine:
Spatial Dependency Analysis to Extract Information from Side-Channel Mixtures. 73-84 - Malik Imran, Felipe Almeida, Jaan Raik, Andrea Basso, Sujoy Sinha Roy, Samuel Pagliarini:
Design Space Exploration of SABER in 65nm ASIC. 85-90 - Rony Komissarov, Avishai Wool:
Spoofing Attacks Against Vehicular FMCW Radar. 91-97 - Erland Wittkotter:
WaC: Trustworthy Encryption and Communication in an IT Ecosystem with Artificial Superintelligence. 99-109 - Yoo-Seung Won, Soham Chatterjee, Dirmanto Jap, Arindam Basu, Shivam Bhasin:
WaC: First Results on Practical Side-Channel Attacks on Commercial Machine Learning Accelerator. 111-114
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