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96 articles for “E-learning Security”
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Research ArticleOpen accessIn the abstractProbabilistic Learning Models for Secure E-Commerce Transaction AnalysisAnanth Maria Pushpa, S. SubramaniaanThe tremendous expansion of e-commerce requires well-developed security mechanisms of transactions coupled with cryptography systems. This paper explores how probabilistic learning algorithms can be used to promote fraud and transaction validation in e-commerce systems that are cryptographically secured. A study compared different machine learning models to analyze retail data, including Naïve Bayes, Bayes Network, and Logistic learning. The results showed … …Journal of Computer Science, Vol. 22, Issue 11 · 20 Oct 2026 · 506 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Scalable Hybrid CNN-LSTM and SDN Based Architecture for Real-Time DDoS Defence in IoT and Cloud NetworksSujit Sutradhar, Joy Lal Sarkar, Rajesh Kumar VermaDistributed Denial-of-Service (DDoS) is one of the most significant threats to the security of IoT, cloud, and Software-Defined Network (SDN) environments because it can aggravate network unavailability and disrupt the continuity of services. This study presents a hybrid CNN-LSTM-based DDoS detection and mitigation system for real-time DDoS detection in the context of heterogeneous network environments, which is integrated with SDN … …Journal of Computer Science, Vol. 22, Issue 10 · 19 Oct 2026 · 508 accessesView PDFCite
Research ArticleOpen accessIn the abstractBenchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease DetectionPrince Daughin Ngqabutho NcubeSorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers struggle to diagnose reliably in the field. While deep learning has demonstrated strong potential for automated plant disease identification, sorghum remains underrepresented in the literature, and no prior study has provided a comprehensive, … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 535 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Based Prediction of Catch Yields in Small Scale FisheriesEpifelward Niño Olaivar Amora, Patrick D. CernaSmall-scale fisheries are critical for food security and livelihoods but increasingly face threats from overfishing and environmental change. This study employed machine learning to predict catch yields in Cogtong Bay, Philippines, using 3,478 records collected in 2020–2021 that included species, gear, location, season, and weather data. Models developed in Python with scikit-learn and XGBoost compared Random Forest (RF), Extreme Gradient … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,096 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Privacy-Preserving Access Control for Electronic Health Records Using Smart ContractsG. Bhanu Prasad, M. Venkateswara RaoElectronic medical records are crucial for providing high-quality healthcare, but they also raise serious privacy and security issues. Traditional centralised storage systems are vulnerable to manipulation, hacking, and illegal access. This study suggests a smart contract-based blockchain architecture that provides decentralised, unaltered, and privacy-preserving access control for EMRs. The model integrates cryptographic techniques like AES-256 encryption and SHA-256 hashing for … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Framework for Citrus Grading and Yield Prediction Using Classifier-Informed RegressionLydia Dede Obeng, Isaac O. OsunmakindeAgriculture remains a cornerstone of human sustenance, yet accurate citrus fruit grading and yield predictions remain significant challenges due to visual similarities between varieties such as oranges and grapefruits. This includes the inefficiencies of manual grading. This study presents a new dual-function machine learning system that integrates classification and regression to simultaneously grade citrus fruits and forecast crop yields. This … …Journal of Computer Science, Vol. 22, Issue 4 · 24 Apr 2026 · 1,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection Framework for MEC-Enabled IoT NetworksRofaida Tawfik, Abdelfattah Hegazy, Hesham Dahshan, Ahmed Gaber AbuabdallahMobile Edge Computing (MEC) has emerged as a promising paradigm for supporting latency-sensitive Internet of Things (IoT) applications by bringing computational resources closer to data sources. However, the distributed nature of MEC environments increases exposure to network-based security threats, particularly network intrusions that can impact both system reliability and task offloading efficiency. This paper proposes a security-aware framework that integrates … …Journal of Computer Science, Vol. 22, Issue 4 · 1 Apr 2026 · 1,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite