Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …

ABSTRACT The Internet of Things (IoT) is a relatively new technology that has piqued
academics' and business information systems' attention in recent years. The Internet of …

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

Text-to-image diffusion models are nothing but a revolution, allowing anyone, even without
design skills, to create realistic images from simple text inputs. With powerful personalization …

Large language models (LLMs), designed to provide helpful and safe responses, often rely
on alignment techniques to align with user intent and social guidelines. Unfortunately, this …

Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

Adversarial attacks are valuable for evaluating the robustness of deep learning models.
Existing attacks are primarily conducted on the visible light spectrum (eg, pixel-wise texture …

Although semantic communications have exhibited satisfactory performance on a large
number of tasks, the impact of semantic noise and the robustness of the systems have not …

Given the severe vulnerability of Deep Neural Networks (DNNs) against adversarial
examples, there is an urgent need for an effective adversarial attack to identify the …

Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …