Research ArticleOpen accessIn the abstractCRISP-DM-Based Mobile Application for Predicting High-Crime Areas in Metropolitan LimaHugo Vega Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza et al.The city of Lima, Peru, has been facing a serious climate of citizen security that has risen extremely high in recent years. The objective of this work is to identify and predict areas of high crime incidence through a mobile application based on historical data on criminal incidents recorded by users. The mobile application has been implemented using the CRISP-DM … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,972 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnveiling the Performance: A Comparative Study of HMAC and RSA Encryption on SHA-512Louis Leonardo, RojaliThe study evaluates critical operations including token signing, verification, and decoding, as well as data transfer efficiency, utilizing the jsonwebtoken library. By benchmarking these operations, we provide insights into the trade-offs between symmetric (HMAC) and asymmetric (RSA) encryption methods, highlighting their impact on performance and security. The results serve as a guideline for developers to make informed decisions when choosing … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractLSTM-Based AI Model for Sinkhole Attack Detection With Legal Basis in an Ecuadorian Public InstitutionEstefanía Alejandra Mora Parra, Rubén Nogales Portero, Moisés Toapanta T. et al.Wireless Sensor Networks (WSN) are an essential component of the Internet of Things (IoT). However, their decentralized nature, data transmission over unencrypted channels, and the physical exposure of nodes make them especially vulnerable to attacks, among which the sinkhole attack stands out. This research aims to develop a machine learning–based model to detect sinkhole‐type attacks in wireless sensor networks, with … …Journal of Computer Science, Vol. 22, Issue 3 · 4 Mar 2026 · 1,648 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Decisive Red Fox Optimizer-Based Feature Selection With Deep Learning-Based Intrusion Detection SystemC. Ananth, S. Sathiyarani, N. MohananthiniRecently, Intrusion Detection Systems (IDS) using Deep Learning (DL) models become useful in accomplishing network security. The selected features serve as input to the DL model, which is trained on labelled datasets to learn intrinsic patterns distinguishing malicious from normal network behaviour. DL techniques like Convolutional Neural Networks (CNN) are usually utilized. The seamless combination of Public Blockchain (BC) technology … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,714 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsability Assessment of E-Commerce Systems Using McCall’s Quality ModelSiti Solehah Othman, A Noraziah, Roslina Mohd SidekE-commerce platforms rely fundamentally on business database transaction systems that must balance user experience with security and data integrity. Traditional usability assessment methodologies often overlook critical security elements and transactional integrity requirements. This study employs McCall's Quality Model to comprehensively evaluate the usability characteristics of three prominent e-commerce platforms: Temu, Shopee, and Lazada. Through structured task-based evaluations and Likert-scale questionnaires, … …Journal of Computer Science, Vol. 21, Issue 11 · 19 Dec 2025 · 2,541 accessesView PDFCite
Research ArticleOpen accessIn the abstractSafeguarding Electronic Health Records: A Review of Privacy and Security in EHR WorkflowsGayathri Hegde M, P. Deepa Shenoy, Venugopal K RElectronic Health Records (EHRs) have revolutionized the healthcare industry by improving the accessibility to patient data, optimizing workflows and refining clinical decision making. The increasing use of digital records raises serious privacy and security concerns, particularly about healthcare data storage and management, access and retrieval, and sharing and interoperability. This survey paper comprehensively reviews existing privacy-preserving and security-enhancing approaches across … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 2,233 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Cybersecurity: Dynamically Retrainable Firewalls for Real-Time Network ProtectionSina AhmadiThe growing complexity of cyberattacks has necessitated the evolution of firewall technologies from static models to adaptive, machine learning-driven systems. This research introduces “Dynamically Retrainable Firewalls”, which respond to emerging threats in real-time. Unlike traditional firewalls that rely on static rules to inspect traffic, these advanced systems leverage machine learning algorithms to analyze network traffic patterns dynamically and identify threats. … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,558 accessesView PDFCite
Research ArticleOpen accessIn the abstractHacking Back: Using Genetic Algorithms to Outsmart HackersGhosoun Al Hindi, Mohammad Alshraideh et al.Web applications are widely used in today's digital landscape, necessitating robust security measures to protect against unauthorized access by malicious users. Ensuring the security of these applications requires effectively identifying and addressing vulnerabilities. This paper proposes an automated methodology for vulnerability detection, utilizing a genetic algorithm to generate test cases, which offers greater efficiency and performance compared to resource-intensive and … …Journal of Computer Science, Vol. 21, Issue 9 · 10 Oct 2025 · 2,600 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,993 accessesView PDFCite