{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:31:42Z","timestamp":1777383102747,"version":"3.51.4"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Array"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.array.2026.100799","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T16:15:59Z","timestamp":1775060159000},"page":"100799","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A physics-informed machine learning for detecting suspicious satellite maneuvers (orbital manipulation)"],"prefix":"10.1016","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9006-0552","authenticated-orcid":false,"given":"K.K.H.","family":"Karunathilake","sequence":"first","affiliation":[]},{"given":"Kavinga Yapa","family":"Abeywardena","sequence":"additional","affiliation":[]},{"given":"Sara","family":"Vecchini","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.array.2026.100799_bib1","series-title":"Satellite communication systems","author":"Maral","year":"2020"},{"key":"10.1016\/j.array.2026.100799_bib2","series-title":"Satellite Signal Jamming Reaches New lows - Starlink and Other LEO Constellations Face a New Set of Security Risks","author":"Laursen","year":"2023"},{"key":"10.1016\/j.array.2026.100799_bib3","series-title":"Russia Hacked an American Satellite Company One Hour before the Ukraine Invasion","author":"O\u2019Neill","year":"2022"},{"key":"10.1016\/j.array.2026.100799_bib4","series-title":"Hacktivism goes orbital: investigating NB65's breach of ROSCOSMOS","author":"Thummala","year":"2024"},{"key":"10.1016\/j.array.2026.100799_bib5","doi-asserted-by":"crossref","DOI":"10.1093\/cybsec\/tyac008","article-title":"Building a launchpad for satellite cyber-security research: lessons from 60 years of spaceflight","volume":"8","author":"Pavur","year":"2022","journal-title":"Journal of Cybersecurity"},{"key":"10.1016\/j.array.2026.100799_bib6","series-title":"Workshop on security of space and satellite systems (SpaceSec) 2024, San Diego","article-title":"Threats against Satellite ground infrastructure: a retrospective analysis of sophisticated attacks","author":"Hamill-Stewart","year":"2024"},{"key":"10.1016\/j.array.2026.100799_bib8","series-title":"IEEE symposium on security and privacy (SP)","article-title":"Space odyssey: an experimental software security analysis of satellites","author":"Willbold","year":"2023"},{"issue":"4","key":"10.1016\/j.array.2026.100799_bib9","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1089\/space.2024.0015","article-title":"Survey of space Professionals' Perception of Satellite Cybersecurity from 2012 to 2022: decision-makers\u2019 thoughts on satellite cybersecurity evolving","volume":"12","author":"Jones","year":"2024","journal-title":"New Space"},{"key":"10.1016\/j.array.2026.100799_bib7","series-title":"A Chinese Space Tug Just Grappled a Dead Satellite","author":"Gough","year":"2022"},{"key":"10.1016\/j.array.2026.100799_bib39","series-title":"2023 IEEE 9th international conference on space Mission challenges for information technology (SMC-IT)","article-title":"WannaFly: an approach to satellite ransomware","author":"Falco","year":"2023"},{"key":"10.1016\/j.array.2026.100799_bib10","series-title":"Gecco '21: genetic and Evolutionary Computation Conference","article-title":"Detecting anomalies in spacecraft telemetry using evolutionary thresholding and LSTMs","author":"Benecki","year":"2021"},{"key":"10.1016\/j.array.2026.100799_bib11","doi-asserted-by":"crossref","DOI":"10.1088\/1742-6596\/2489\/1\/012036","article-title":"Anomaly detection of satellite telemetry data based on extended dominant sets clustering","volume":"2489","author":"Jin","year":"2023","journal-title":"J Phys Conf"},{"key":"10.1016\/j.array.2026.100799_bib12","series-title":"2021 IEEE\/CVF conference on computer vision and pattern recognition workshops (CVPRW)","article-title":"Spacecraft time-series anomaly detection using transfer learning","author":"Baireddy","year":"2021"},{"key":"10.1016\/j.array.2026.100799_bib13","article-title":"A deep learning anomaly detection framework for satellite telemetry with fake anomalies","volume":"2022","author":"Wang","year":"2022","journal-title":"International Journal of Aerospace Engineering"},{"key":"10.1016\/j.array.2026.100799_bib14","doi-asserted-by":"crossref","DOI":"10.3390\/s22176358","article-title":"Anomaly detection in satellite telemetry data using a sparse feature-based method","volume":"22","author":"He","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.array.2026.100799_bib15","series-title":"2024 IEEE aerospace conference","article-title":"An explainable machine learning approach for anomaly detection in satellite telemetry data","author":"Kricheff","year":"2024"},{"key":"10.1016\/j.array.2026.100799_bib16","series-title":"2024 4th international conference on Embedded & Distributed Systems (EDiS)","article-title":"Detection and prediction of satellite telemetry anomalies","author":"Habib","year":"2024"},{"key":"10.1016\/j.array.2026.100799_bib17","article-title":"Spacecraft telemetry Anomaly Detection based on parametric causality and double-criteria drift streaming peaks over threshold","volume":"12","author":"Zeng","year":"2022","journal-title":"Appl Sci"},{"key":"10.1016\/j.array.2026.100799_bib18","article-title":"A real-time Anomaly detection in satellite telemetry data using artificial intelligence techniques depending on time-series analysis","volume":"14","author":"Ali","year":"2023","journal-title":"Journal of the ACS Advances in Computer Science"},{"issue":"8","key":"10.1016\/j.array.2026.100799_bib19","doi-asserted-by":"crossref","first-page":"673","DOI":"10.3390\/aerospace10080673","article-title":"Generic diagnostic framework for Anomaly detection\u2014application in satellite and spacecraft systems","volume":"10","author":"Bieber","year":"2023","journal-title":"Aerospace"},{"issue":"3","key":"10.1016\/j.array.2026.100799_bib20","first-page":"2405","article-title":"Anomaly detection of UAV state data based on single-class triangular global alignment kernel extreme learning machine","volume":"136","author":"Hu","year":"2023","journal-title":"Comput Model Eng Sci"},{"issue":"6","key":"10.1016\/j.array.2026.100799_bib21","doi-asserted-by":"crossref","first-page":"408","DOI":"10.3390\/drones9060408","article-title":"Unmanned aerial vehicle anomaly detection based on causality-enhanced graph neural networks","volume":"9","author":"Feng","year":"2025","journal-title":"Drones"},{"issue":"10","key":"10.1016\/j.array.2026.100799_bib22","doi-asserted-by":"crossref","first-page":"534","DOI":"10.3390\/drones8100534","article-title":"UAV anomaly detection method based on convolutional autoencoder and support vector data description with 0\/1 soft-margin loss","volume":"8","author":"Huakun","year":"2024","journal-title":"Drones"},{"issue":"2","key":"10.1016\/j.array.2026.100799_bib23","doi-asserted-by":"crossref","first-page":"219","DOI":"10.4271\/01-15-02-0017","article-title":"Anomaly detection for unmanned aerial vehicle sensor data using a stacked recurrent autoencoder method with dynamic thresholding","volume":"15","author":"Bell","year":"2022","journal-title":"SAE International Journal of Aerospace"},{"issue":"1","key":"10.1016\/j.array.2026.100799_bib24","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1016\/j.asr.2024.09.050","article-title":"On-orbit satellite hierarchical anomaly detection using causal structure learning","volume":"75","author":"Chen","year":"2025","journal-title":"Adv Space Res"},{"issue":"2","key":"10.1016\/j.array.2026.100799_bib25","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.cja.2022.05.001","article-title":"A method for satellite time series anomaly detection based on fast-DTW and improved-KNN","volume":"36","author":"Cui","year":"2023","journal-title":"Chin J Aeronaut"},{"key":"10.1016\/j.array.2026.100799_bib26","article-title":"Ault diagnosis of spacecraft electrical power system based on improved Newman community divisions method","author":"Song","year":"2025","journal-title":"Chin J Aeronaut"},{"issue":"13","key":"10.1016\/j.array.2026.100799_bib27","doi-asserted-by":"crossref","DOI":"10.3390\/app12136296","article-title":"Unsupervised anomaly detection for time series data of spacecraft using multi-task learning","volume":"12","author":"Yang","year":"2022","journal-title":"Appl Sci"},{"key":"10.1016\/j.array.2026.100799_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108083","article-title":"Explainable anomaly detection in spacecraft telemetry","volume":"133","author":"Cu\u00e9llar","year":"2024","journal-title":"Eng Appl Artif Intell"},{"key":"10.1016\/j.array.2026.100799_bib35","series-title":"Rocket propulsion elements","author":"Sutton","year":"2001"},{"key":"10.1016\/j.array.2026.100799_bib30","series-title":"Ascend","article-title":"When Satellites attack: satellite-to-Satellite cyber attack, defense and resilience","author":"Falco","year":"2020"},{"issue":"2","key":"10.1016\/j.array.2026.100799_bib29","doi-asserted-by":"crossref","first-page":"4729","DOI":"10.55248\/gengpi.6.0225.1033","article-title":"\"Advanced Cybersecurity Frameworks for Protecting Satellite Networks, Deep-Space Communications, and Space Assets\"","volume":"6","author":"Aderinto","year":"2025","journal-title":"International Journal of Research Publication and Reviews"},{"key":"10.1016\/j.array.2026.100799_bib31","first-page":"17826","article-title":"European space agency benchmark for Anomaly detection in satellite telemetry","volume":"2406","author":"Kotowski","year":"2024","journal-title":"ArXiv"},{"key":"10.1016\/j.array.2026.100799_bib40","series-title":"Big data from space (BiDS\u201923)","article-title":"Annotating large satellite telemetry dataset for ESA international AI anomaly detection benchmark","author":"Kotowski","year":"2023"},{"issue":"8","key":"10.1016\/j.array.2026.100799_bib32","first-page":"24","article-title":"Orbital decay of low Earth orbit satellites: a numerical investigation","volume":"7","author":"Hossain","year":"2023","journal-title":"International Journal of Scientific Engineering and Science"},{"key":"10.1016\/j.array.2026.100799_bib33","series-title":"Advanced level physics","author":"Nelkon","year":"1995"},{"key":"10.1016\/j.array.2026.100799_bib34","series-title":"The tsiolkovsky rocket equation: a parallel derivation","author":"Hay","year":"2022"},{"key":"10.1016\/j.array.2026.100799_bib36","series-title":"Orbital mechanics for engineering students","author":"Curtis","year":"2005"},{"key":"10.1016\/j.array.2026.100799_bib37","series-title":"Fundamentals of astrodynamics and applications","author":"Vallado","year":"2013"},{"key":"10.1016\/j.array.2026.100799_bib38","unstructured":"Software for digital mission engineering and systems analysis,\" Ansys STK, [Online]. Available: https:\/\/www.ansys.com\/products\/missions\/ansys-stk. [Accessed 19 October 2025]."}],"container-title":["Array"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626001220?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626001220?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T09:25:34Z","timestamp":1777368334000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2590005626001220"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":40,"alternative-id":["S2590005626001220"],"URL":"https:\/\/doi.org\/10.1016\/j.array.2026.100799","relation":{},"ISSN":["2590-0056"],"issn-type":[{"value":"2590-0056","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A physics-informed machine learning for detecting suspicious satellite maneuvers (orbital manipulation)","name":"articletitle","label":"Article Title"},{"value":"Array","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.array.2026.100799","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"100799"}}