{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T19:25:38Z","timestamp":1783970738209,"version":"3.55.0"},"reference-count":66,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund","doi-asserted-by":"publisher","award":["NPRP12C-0814-190012-SP165"],"award-info":[{"award-number":["NPRP12C-0814-190012-SP165"]}],"id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Iberdrola S.A.","award":["NPRP12C-0814-190012-SP165"],"award-info":[{"award-number":["NPRP12C-0814-190012-SP165"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCP"],"abstract":"<jats:p>Power-Line Communication (PLC) allows data transmission through existing power lines, thus avoiding the expensive deployment of ad hoc network infrastructures. However, power line networks remain vastly unattended, which allows tampering by malicious actors. In fact, an attacker can easily inject a malicious signal (jamming) with the aim of disrupting ongoing communications. In this paper, we propose a new solution to detect jamming attacks before they significantly affect the quality of the communication link, thus allowing the detection of a jammer (geographically) far away from a receiver. We consider two scenarios as a function of the receiver\u2019s ability to know in advance the impact of the jammer on the received signal. In the first scenario (jamming-aware), we leverage a classifier based on a Convolutional Neural Network, which has been trained on both jammed and non-jammed signals. In the second scenario (jamming-unaware), we consider a one-class classifier based on autoencoders, allowing us to address the challenge of jamming detection as a classical anomaly detection problem. Our proposed solution can detect jamming attacks on PLC networks with an accuracy greater than 99% even when the jammer is 68 m away from the receiver while requiring training only on traffic acquired during the regular operation of the target PLC network.<\/jats:p>","DOI":"10.3390\/jcp5030046","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T11:52:58Z","timestamp":1752580378000},"page":"46","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Detecting Jamming in Smart Grid Communications via Deep Learning"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1387-6784","authenticated-orcid":false,"given":"Muhammad","family":"Irfan","sequence":"first","affiliation":[{"name":"College of Science and Engineering, Hamad Bin Khalifa University, Doha 5825, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aymen","family":"Omri","sequence":"additional","affiliation":[{"name":"Iberdrola Innovation Middle East, Doha 210177, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6809-2381","authenticated-orcid":false,"given":"Javier","family":"Hernandez Fernandez","sequence":"additional","affiliation":[{"name":"Iberdrola Innovation Middle East, Doha 210177, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0974-3639","authenticated-orcid":false,"given":"Savio","family":"Sciancalepore","sequence":"additional","affiliation":[{"name":"Eindhoven Artificial Intelligence Systems Institute, Eindhoven University of Technology, 5612 Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9637-0430","authenticated-orcid":false,"given":"Gabriele","family":"Oligeri","sequence":"additional","affiliation":[{"name":"College of Science and Engineering, Hamad Bin Khalifa University, Doha 5825, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"ref_1","unstructured":"Wadhwani, P. 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