Real-time communication between autonomous vehicles, infrastructure, and their environment has facilitated the Internet of Vehicles (IoVs). Although this connectivity provides vehicular networks with significant benefits, it also introduces severe security threats, such as message injection attacks, particularly due to the heavy reliance on the Controller Area Network (CAN) protocol, which is inherently vulnerable. Electronic Control Units (ECUs) become primary targets for these attacks, leading to unsafe vehicle behaviors. To address these challenges, an Intrusion Detection System (IDS) based on deep learning architectures, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and... More >

Roman Urdu sentiment analysis faces significant challenges due to transliteration inconsistencies, informal language usage, and the lack of labeled datasets. This study proposes a novel framework that addresses these challenges by combining advanced data preprocessing techniques and data augmentation strategies such as synonym replacement, back-translation, and random word insertion. These methods enhance dataset diversity, improving the model’s generalization ability. A rich Roman Urdu dataset was collected from diverse sources, including social media platforms (Facebook, Twitter, YouTube), blogs, forums, and e-commerce sites, to capture a wide range of user opinions. Three deep learning... More >