The Internet of Vehicles (IoVs) is an emerging technology that enhances transportation systems by enabling interactions between vehicles, infrastructure, and other entities. Securing IoV networks from cyber threats like eavesdropping, data tampering, and intrusions is a major challenge. This research presents a Blockchain-Enabled Secure Authentication Protocol for IoVs (BESA-IOV), which leverages blockchain’s decentralized and tamper-resistant nature for secure communication in vehicular networks. By utilizing ECC-based lightweight cryptography and blockchain-based public key management, it ensures strong authentication, confidentiality, and integrity. The results show that BESA-IOV signif... More >

This paper introduces ViTDroid, a novel hybrid model that combines Vision Transformers (ViTs) and recurrent neural networks (RNNs) to enhance Android and IoT malware detection. ViTDroid addresses critical challenges by leveraging ViTs to capture global spatial dependencies and RNNs (LSTM and GRU) to model temporal patterns, enabling comprehensive analysis of complex malware behaviors. Additionally, the model integrates explainability tools, such as LIME and SHAP, to enhance transparency and trustworthiness, essential for real-world cybersecurity applications. The study evaluates ViTDroid's performance against conventional models, including RNN, LSTM, and GRU, using accuracy, precision, recal... More >

In the therapy of Coronavirus, the drug target is a demanding task to find novel medicine. A bunch of pharmaceutics procedures are employed to recognize these mutual actions. But they are exhausting and high-priced. Keeping this in view, computational procedures are widely approached to determine the mutual action of the medicine and their respective proteins. Many scientists have applied ML approaches to deduce attributes from simplified molecular-input line systems (for medicine) and protein sequences. Such approaches dropped the proteins' chemical, physical, and structural characteristics and the respective medicine. Our job is to undertake deep learning approaches to detect coronavirus e... More >

This paper introduces a novel method for controlling a class of nonlinear non-affine systems with fractional-order dynamics, using an adaptive fuzzy technique. By incorporating a novel fractional update law in the design procedure, the controller can effectively suppress chaotic behaviour and smoothly track desired trajectories. The proposed method offers key advantages such as robustness against uncertainties, fast error convergence to the neighbourhood of zero, and satisfactory disturbance rejection performance. To demonstrate the capabilities of the proposed fractional controller, simulation results were conducted using Python on a fractional order Arneodo chaotic system. The results high... More >

I am pleased to introduce a new Transactions focusing on the rapidly evolving field of Advanced Computing and Systems. This journal is intended to serve as a platform for cutting-edge research and technological advancements that have the potential to reshape industries through state-of-the-art computing methodologies. The goal is to foster interdisciplinary collaboration among researchers, practitioners, and industry leaders, facilitating the advancement of computing systems and exploring their impact on real-world applications. Through this publication, I aim to contribute to the academic discourse and help drive innovation in this critical domain. More >