IEEE

Attention-based CNN-BiLSTM Model With CTGAN Sample Augmentation for Intrusion Detection in IoT

Abstract: Intrusions or attacks on IoT networks have dramatically increased in recent years. As a result, protecting IoT infrastructure from these threats became essential to its global acceptance.
IEEE

Adversial Learning Through GAN and Feature Extraction Through CNN for Deep Fake Detection

Abstract: Deepfake technology, using deep learning, creates highly realistic yet artificial media, creating challenges for security and privacy. Convolutional Neural Networks (CNNs) play a crucial ...
IEEE

HemaX - A CNN-Based Approach for Anemia Detection from Conjunctiva Pallor Images

Abstract: Anaemia is a condition marked by an insufficient number of healthy red blood cells, often initially indicated through visible conjunctival pallor. Conventional diagnostic approaches rely on ...
IEEE

An Advanced CNN–LSTM–Attention Framework for the Detection of GNSS Spoofing Interference

Abstract: Our study addresses the shortcomings of existing methods by designing a software-based spoofing-signal identification system for civilian GNSS receivers, enabling intelligent detection of ...