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Conventional adversarial perturbations on traffic sign images often induce noticeable color shifts and abnormal contrast compared to natural images, rendering them susceptible to detection, particularly by Vision Transfo...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

Malware represents the most critical threat in cybersecurity, meant to compromise the security for any individual or any organization. These are covert software, designed to perform malicious act like data theft, data al...

Generative Artificial Intelligence (Generative AI) models are now broadly used for academic writing and software development for the sake of productivity and efficiency. Concerns on the impact of Artificial Intelligence ...

Abstract The development of trustworthy AI models is crucial, particularly for critical medical applications such as brain tumor detection using MRI images. However, medical images are being increasingly targeted by adve...

Cooperative driving automation (CDA) has gained attention over the years because of its cooperative driving capability that provides solution to individual automated driving challenges. Although reliance on communication...

Federated Learning (FL) has emerged as a privacy-preserving distributed learning paradigm that enables collaborative model training without sharing raw data. Despite its advantages, ensuring trustworthy FL deployment rem...

The perception systems for Traffic Sign Recognition (TSR) and Lane Line Recognition (LLR) are foundational pillars for the safe and effective operation of Advanced Driver-Assistance Systems (ADAS) and fully autonomous ve...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

With the rapid growth of Internet of Vehicles (IoV) technology, the attack surface has expanded significantly in recent years. Traditional intrusion detection systems, such as signature-based and rule-based approaches, a...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

Object detection is a central task in computer vision, with wide adoption in real-world applications such as surveillance systems, autonomous driving, healthcare monitoring, and smart devices. Models such as YOLOv8, SSD,...