Research ArticleOpen accessIn the author namesMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,696 accessesView PDFCite
Review ArticleOpen accessIn the author namesFederated Learning for Analysis of Medical Images: A SurveyMuhammad Imran Sharif, Mehwish Mehmood, Md Palash Uddin et al.Machine learning models trained in medical imaging can help in the early detection, diagnosis, and prognosis of the disease. However, it confronts two major obstacles: deep learning models require access to a substantial amount of imaging data, which is a hard constraint, and the patient data is private and sensitive, so it cannot be shared like 1 other imaging data … …Journal of Computer Science, Vol. 20, Issue 12 · 28 Oct 2024 · 11,824 accessesView PDFCite
Research ArticleOpen accessIn the author namesPhishing Website Detection Using Improved Multilayered Convolutional Neural NetworksHadia Bibi, Syed Rehan Shah, Mirza Murad Baig et al.The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks; this could lead to financial damages and loss of personal information. Phishing is seen as an internet threat and a cybercrime where anyone can capture personal information and data by posing as a reliable source. … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,578 accessesView PDFCite
Research ArticleOpen accessIn the author namesEnhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel PropositionMeer Hazar Khan, Muhammad Imran Sharif, Mehwish Mehmood et al.Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images … …Journal of Computer Science, Vol. 20, Issue 5 · 23 Feb 2024 · 5,562 accessesView PDFCite
Review ArticleOpen accessIn the author namesA Comprehensive Survey on Applications, Challenges, Threats and Solutions in IoT Environment and ArchitectureSadia Waheed, Savera Hanif, Rubab Hafeez et al.The influence of the Internet of Things (IoT) on how people live, interact and conduct business has rapidly increased. Integrating physical objects with electronic networking, or the Internet of Things (IoT), allows for better communication and environment detection. In coming years, higher service levels will be offered by IoT-based technologies, remarkably changing how people would conduct their daily lives. Currently, … …Journal of Computer Science, Vol. 20, Issue 3 · 30 Jan 2024 · 7,261 accessesView PDFCite
Research ArticleOpen accessIn the author namesAnalysis of Mental Health Counseling Conversation Using Natural Language ProcessingSaad Ahmed, Sidrah Khurshid, Muhammad Imran et al.One of the most significant public health challenges of our day is mental illness. Despite the benefits of psychotherapy and counseling, our understanding of conducting effective counseling conversations has been limited due to a lack of high-quality data with labeled results. This research presents a quantitative analysis of relatively good-quality data scraped from an online counseling forum. The dataset comprises … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,857 accessesView PDFCite