{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T15:10:53Z","timestamp":1783696253303,"version":"3.55.0"},"reference-count":34,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deanship of Scientific Research at Najran University","award":["U\/DRP\/SERC\/12\/39"],"award-info":[{"award-number":["U\/DRP\/SERC\/12\/39"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the modern power system\u2019s rapid development, more scattered smart grid components are securely linked into the power system by encircling a wide electrical power network with the underpinning communication system. By enabling a wide range of applications, such as distributed energy management, system state forecasting, and cyberattack security, these components generate vast amounts of data that automate and improve the efficiency of the smart grid. Due to traditional computer technologies\u2019 inability to handle the massive amount of data that smart grid systems generate, AI-based alternatives have received a lot of interest. Long Short-Term Memory (LSTM) and recurrent Neural Networks (RNN) will be specifically developed in this study to address this issue by incorporating the adaptively time-developing energy system\u2019s attributes to enhance the model of the dynamic properties of contemporary Smart Grid (SG) that are impacted by Revised Encoding Scheme (RES) or system reconfiguration to differentiate LSTM changes &amp; real-time threats. More specifically, we provide a federated instructional strategy for consumer sharing of power data to Power Grid (PG) that is supported by edge clouds, protects consumer privacy, and is communication-efficient. They then design two optimization problems for Energy Data Owners (EDO) and energy service operations, as well as a local information assessment method in Federated Learning (FL) by taking non-independent and identically distributed (IID) effects into consideration. The test results revealed that LSTM had a longer training duration, four hidden levels, and higher training loss than other models. The provided method works incredibly well in several situations to identify FDIA. The suggested approach may successfully induce EDOs to employ high-quality local models, increase the payout of the ESP, and decrease task latencies, according to extensive simulations, which are the last points. According to the verification results, every assault sample could be effectively recognized utilizing the current detection methods and the LSTM RNN-based structure created by Smart.<\/jats:p>","DOI":"10.3390\/s23198016","type":"journal-article","created":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T05:32:45Z","timestamp":1695360765000},"page":"8016","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["Artificial Intelligence-Based Secured Power Grid Protocol for Smart City"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8539-7024","authenticated-orcid":false,"given":"Adel","family":"Sulaiman","sequence":"first","affiliation":[{"name":"Department of Computer Science, College of Computer Science, and Information Systems, Najran University, Najran 61441, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4917-6691","authenticated-orcid":false,"given":"Bharathiraja","family":"Nagu","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3322-1315","authenticated-orcid":false,"given":"Gaganpreet","family":"Kaur","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pradeepa","family":"Karuppaiah","sequence":"additional","affiliation":[{"name":"Department of CSE, St. Michael College of Engineering and Technology, Kalayarkoil, Sivaganga 630551, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8799-9448","authenticated-orcid":false,"given":"Hani","family":"Alshahrani","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer Science, and Information Systems, Najran University, Najran 61441, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2266-9608","authenticated-orcid":false,"given":"Mana Saleh Al","family":"Reshan","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Computer Science, and Information Systems, Najran University, Najran 61441, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0371-0847","authenticated-orcid":false,"given":"Sultan","family":"AlYami","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer Science, and Information Systems, Najran University, Najran 61441, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4806-6159","authenticated-orcid":false,"given":"Asadullah","family":"Shaikh","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Computer Science, and Information Systems, Najran University, Najran 61441, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103371","DOI":"10.1016\/j.scs.2021.103371","article-title":"Towards sustainable SC: A secure and scalable trading system for residential homes using blockchain and artificial intelligence","volume":"76","author":"Samuel","year":"2022","journal-title":"Sustain. 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