{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T09:13:34Z","timestamp":1773393214679,"version":"3.50.1"},"reference-count":0,"publisher":"Advances in Artificial Intelligence and Machine Learning","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAIML"],"published-print":{"date-parts":[[2025,1,1]]},"abstract":"<jats:p>This study explores the application of deep learning (DL) to enhance security in Near Field Communication (NFC) technology, which is widely used in secure access control and contactless payments. As NFC usage grows, concerns have emerged about security vulnerabilities, particularly relay attacks, where attackers relay signals without breaking encryption or other protective measures. Previous research focused on ambient-based, distance-bounding protocols and deep learning with RF fingerprinting via Wi-Fi to mitigate such threats. This study will improve detecting of NFC relay attacks using RF fingerprints and deep learning via Bluetooth. SDR++ software and a HackRF device were used to gather 2,400 NFC signal samples. 1,200 samples are allocated to the Normal category, while another 1,200 samples are assigned to the Relay Attack category. The dataset is trained, validated, and tested using the 2D-CNN model. The model\u2019s test set accuracy was 88%, with 0.85 precision and 0.91 recall for the \u201dNormal\u201d class and 0.90 precision and 0.84 recall for the \u201dAttack\u201d class. Both classes\u2019 F1-scores were approximately 0.88, showing performance that was balanced between sensitivity and precision.<\/jats:p>","DOI":"10.54364\/aaiml.2025.54264","type":"journal-article","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:44:52Z","timestamp":1767339892000},"page":"4765","source":"Crossref","is-referenced-by-count":0,"title":["Detecting Wireless Relay Attacks in NFC Using Deep-Learning"],"prefix":"10.54364","volume":"05","author":[{"given":"Asia","family":"Othman Aljahdali","sequence":"first","affiliation":[]},{"given":"Maria","family":"Jawah","sequence":"additional","affiliation":[]},{"given":"Jana","family":"Bakhalqi","sequence":"additional","affiliation":[]},{"given":"Talah","family":"Fairaq","sequence":"additional","affiliation":[]}],"member":"32807","published-online":{"date-parts":[[2025,1,1]]},"container-title":["Advances in Artificial Intelligence and Machine Learning"],"original-title":[],"link":[{"URL":"https:\/\/www.oajaiml.com\/uploads\/archivepdf\/143154264.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T07:43:34Z","timestamp":1773387814000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.oajaiml.com\/uploads\/archivepdf\/143154264.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,1]]},"references-count":0,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2025,1,1]]},"published-print":{"date-parts":[[2025,1,1]]}},"URL":"https:\/\/doi.org\/10.54364\/aaiml.2025.54264","relation":{},"ISSN":["2582-9793"],"issn-type":[{"value":"2582-9793","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,1]]}}}