5 documents found, page 1 of 1
Machine learning stroke prediction in smart healthcare: integrating Fuzzy K-Nea...
Ahad, Abdul; Puspitasari, Ira; Jiangbin Zheng; Ullah, Shamsher; Ullah, Farhan; Bakhsh, Sheikh Tahir; Pires, Ivan MiguelThis research explores the use of Fuzzy K-Nearest Neighbor (F-KNN) and Artificial Neural Networks (ANN) for predicting heart stroke incidents, focusing on the impact of feature selection methods, specifically Chi-Square and Best First Search (BFS). The study demonstrates that BFS significantly enhances the performance of both classifiers. With BFS preprocessing, the ANN model achieved an impressive accuracy of ...
Enhancing security in 5G edge networks: predicting real-time zero trust attacks...
Ashfaq, Fiza; Wasim, Muhammad; Shah, Mumtaz Ali; Ahad, Abdul; Pires, Ivan MiguelThe Internet has been vulnerable to several attacks as it has expanded, including spoofing, viruses, malicious code attacks, and Distributed Denial of Service (DDoS). The three main types of attacks most frequently reported in the current period are viruses, DoS attacks, and DDoS attacks. Advanced DDoS and DoS attacks are too complex for traditional security solutions, such as intrusion detection systems and fi...
Dataset for authentication and authorization using physical layer properties in...
Ahmed, Kazi Istiaque; Tahir, Mohammad; Lau, Sian Lun; Habaebi, Mohamed Hadi; Ahad, Abdul; Pires, Ivan MiguelThe proliferation landscape of the Internet of Things (IoT) has accentuated the critical role of Authentication and Authorization (AA) mechanisms in securing interconnected devices. There is a lack of relevant datasets that can aid in building appropriate machine learning enabled security solutions focusing on authentication and authorization using physical layer characteristics. In this context, our research p...
Classification of Vascular Dementia on magnetic resonance imaging using deep le...
Tufail, Hina; Ahad, Abdul; Naqvi, Mustahsan Hammad; Maqsood, Rahman; Pires, Ivan MiguelVascular Dementia is a severe disease that results from dead nerve cells’ accumulation in blood vessels. This affects the blood flow and impairs memory and decision-making abilities. Machine learning and deep learning have been used in detecting this disease. Nevertheless, their accuracy has been inconsistent, explaining why their utilization in diagnosing patients has led to poor performance. We developed seve...
Controller-driven vector autoregression model for predicting content popularity...
Qaiser, Firdous; Hussain, Mudassar; Ahad, Abdul; Pires, Ivan MiguelNamed Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networki...