The security of digital signatures has been a focus of research in emerging area. Threshold signature is a technique designed for distributed scenarios, allowing the signing key to be divided into multiple shares. This approach can resist single point failures of device and ensure key security. However, most existing surveys on threshold signature schemes are either not comprehensive or cover only a limited range of signature types.

Sub-headline: BIT researchers introduce Malcom to tackle cross-domain encrypted traffic detection using self-supervised learning.

Deep neural networks (DNNs) are demonstrated to be vulnerable to adversarial examples. Adversarial training is mainstrem method to improve adversarial robustness of DNNs, which augments the training set with adversarial examples and adopts adversarial regularization loss to improve the robustness of DNNs. Existing adversarial training methods are facing the challenge to balance the accuracy and robustness.

Sub-headline: Beihang University researchers introduce a multi-authority ABE scheme, tackling dynamic access control challenges in cloud data.