Efficient Software Vulnerability Detection Using Transformer-Based Models

Detecting software vulnerabilities is critical to ensuring the security and reliability of modern computer systems. Deep neural networks have shown promising results on vulnerability detection, but they lack the capability to capture global contextual information on vulnerable code. To address th...

AI-Powered Hybrid Intrusion Detection Framework for Cloud Security Using Novel Metaheuristic Optimization

Cybersecurity poses considerable problems to Cloud Computing CC, especially regarding Intrusion Detection Systems IDSs, facing difficulties with skewed datasets and suboptimal classification model performance. This study presents the Hybrid Intrusion Detection System HyIDS, an innovative IDS that...

CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets

In the ever-expanding domain of 5G-NR wireless cellular networks, over-the-air jamming attacks are prevalent as security attacks, compromising the quality of the received signal. We simulate a jamming environment by incorporating additive white Gaussian noise AWGN into the real-world In-phase and...