HWGN2: Side-channel Protected Neural Networks through Secure and Private Function Evaluation. (arXiv:2208.03806v1 [cs.CR])
Recent work has highlighted the risks of intellectual property (IP) piracy of deep learning (DL) models from the side-channel leakage of DL hardware accelerators. In response, to provide side-channel leakage…
Garbled EDA: Privacy Preserving Electronic Design Automation. (arXiv:2208.03822v1 [cs.CR])
The complexity of modern integrated circuits (ICs) necessitates collaboration between multiple distrusting parties, including thirdparty intellectual property (3PIP) vendors, design houses, CAD/EDA tool vendors, and foundries, which jeopardizes confidentiality and…
Garbled EDA: Privacy Preserving Electronic Design Automation. (arXiv:2208.03822v1 [cs.CR])
The complexity of modern integrated circuits (ICs) necessitates collaboration between multiple distrusting parties, including thirdparty intellectual property (3PIP) vendors, design houses, CAD/EDA tool vendors, and foundries, which jeopardizes confidentiality and…
Automatic Security Assessment of GitHub Actions Workflows. (arXiv:2208.03837v1 [cs.CR])
The demand for quick and reliable DevOps operations pushed distributors of repository platforms to implement workflows. Workflows allow automating code management operations directly on the repository hosting the software. However,…
Automatic Security Assessment of GitHub Actions Workflows. (arXiv:2208.03837v1 [cs.CR])
The demand for quick and reliable DevOps operations pushed distributors of repository platforms to implement workflows. Workflows allow automating code management operations directly on the repository hosting the software. However,…
DeepTLS: comprehensive and high-performance feature extraction for encrypted traffic. (arXiv:2208.03862v1 [cs.CR])
Feature extraction is critical for TLS traffic analysis using machine learning techniques, which it is also very difficult and time-consuming requiring huge engineering efforts. We designed and implemented DeepTLS, a…
DeepTLS: comprehensive and high-performance feature extraction for encrypted traffic. (arXiv:2208.03862v1 [cs.CR])
Feature extraction is critical for TLS traffic analysis using machine learning techniques, which it is also very difficult and time-consuming requiring huge engineering efforts. We designed and implemented DeepTLS, a…
Differential biases, $c$-differential uniformity, and their relation to differential attacks. (arXiv:2208.03884v1 [cs.CR])
Differential cryptanalysis famously uses statistical biases in the propagation of differences in a block cipher to attack the cipher. In this paper, we investigate the existence of more general statistical…
Differential biases, $c$-differential uniformity, and their relation to differential attacks. (arXiv:2208.03884v1 [cs.CR])
Differential cryptanalysis famously uses statistical biases in the propagation of differences in a block cipher to attack the cipher. In this paper, we investigate the existence of more general statistical…
Dataset Obfuscation: Its Applications to and Impacts on Edge Machine Learning. (arXiv:2208.03909v1 [cs.CR])
Obfuscating a dataset by adding random noises to protect the privacy of sensitive samples in the training dataset is crucial to prevent data leakage to untrusted parties for edge applications.…