{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T23:31:22Z","timestamp":1780356682279,"version":"3.54.1"},"reference-count":0,"publisher":"SASA Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JOWUA"],"published-print":{"date-parts":[[2025,6,30]]},"abstract":"<jats:p>The rapid proliferation of Internet of Things (IoT) technologies has enabled the development of\nmore advanced applications, such as stress detection in healthcare and occupational settings. Still,\nIoT networks face vulnerabilities related to privacy and latency requirements during real-time aerial\ndata processing. This work proposes a paradigm-shifting Secure Dual Stream Edge Fusion\nOptimization (SDEFO) algorithm that simultaneously solves two significant challenges: (1) realtime stress monitoring and automated feedback using physiological sensor data; and (2)\ncommunication security across wireless IoT nodes. Within the proposed SDEFO framework, dualstream edge analytics bio-signal processing (e.g., GSR or heart rate variability) is emotion-aware\nand deregulated. At the same time, network threat levels dictate responsive routing and encryption\nat the node level. A multilayered fusion technique integrates biometric feature extraction with\nentropy-based secure transmission, strengthening reliability and privacy simultaneously. The system\nis tested on a real-time dataset acquired through wearable IoT sensors under various stress levels\nand network threat simulations. Evaluation results demonstrate enhanced accuracy in stress\ndetection, accompanied by lower packet loss and improved resilience to denial-of-service attacks\nand data tampering. The model demonstrates improvement over other proposed single-stream and\nnon-secure configurations in latency, throughput, and security index. This study has significant\nimplications for health monitoring, innovative workplaces, and defense communication systems,\nwhere both data transmission reliability and confidentiality are crucial. This paper presents a novel,\nmultilayered architecture that integrates affective computing with cryptographic routing to enhance\nthe design of intelligent, secure, and adaptive IoT networks.<\/jats:p>","DOI":"10.58346\/jowua.2025.i2.055","type":"journal-article","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T12:26:06Z","timestamp":1754569566000},"page":"886-902","source":"Crossref","is-referenced-by-count":3,"title":["Real-Time Stress Detection and Secure Communication in Wireless IoT Networks Using the Secure Dual-Stream Edge Fusion Optimization (SDEFO) Algorithm"],"prefix":"10.58346","volume":"16","author":[{"given":"Wad","family":"Ghaban","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"37075","published-online":{"date-parts":[[2025,6,30]]},"container-title":["Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications"],"original-title":[],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T12:26:10Z","timestamp":1754569570000},"score":1,"resource":{"primary":{"URL":"https:\/\/jowua.com\/wp-content\/uploads\/2025\/08\/2025.I2.055.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,6,30]]},"published-print":{"date-parts":[[2025,6,30]]}},"URL":"https:\/\/doi.org\/10.58346\/jowua.2025.i2.055","relation":{},"ISSN":["2093-5374","2093-5382"],"issn-type":[{"value":"2093-5374","type":"print"},{"value":"2093-5382","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,30]]}}}