Multi-user semantic communication (MUSC) has emerged as a promising paradigm for
future 6G networks and applications, where massive clients (eg, mobile devices) …

Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable
solution for future efficient communication. Deep Learning (DL)-based semantic codecs …

Semantic communication systems (SCS) have gained extensive attention with the
advancement of Artificial Intelligence (AI), which transmits the data feature instead of the raw …

Deep learning-based semantic communications (DLSC) replace the physical blocks in
traditional communication systems as end-to-end neural networks. DLSC significantly boost …

Recently, the newly emerged multimodal models, which leverage both visual and linguistic
modalities to train powerful encoders, have gained increasing attention. However, learning …

Transfer-based attacks utilize the proxy model to craft adversarial examples against the
target model and make significant advancements in the realm of black-box attacks. Recent …

Data poisoning is one of the most relevant security threats against machine learning and
data-driven technologies. Since many applications rely on untrusted training data, an …

Data poisoning attacks pose a significant threat to the integrity of machine learning models
by leading to misclassification of target distribution test data by injecting adversarial …

Extensive studies have revealed that the prevalent deep neural networks (DNNs) are
vulnerable to adversarial examples in image recognition tasks. However, previous …

Image scaling is one of the most common operations in image processing. For instance, it is
often conducted before image transferring to preserve resources, image classifiers also …