{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T11:36:26Z","timestamp":1785929786537,"version":"3.56.0"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T00:00:00Z","timestamp":1622764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T00:00:00Z","timestamp":1622764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s00521-021-06106-3","type":"journal-article","created":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T05:03:07Z","timestamp":1622782987000},"page":"4835-4854","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Deep-learning-based data-manipulation attack resilient supervisory backup protection of transmission lines"],"prefix":"10.1007","volume":"35","author":[{"given":"Astha","family":"Chawla","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prakhar","family":"Agrawal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bijaya Ketan","family":"Panigrahi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kolin","family":"Paul","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,6,4]]},"reference":[{"issue":"4","key":"6106_CR1","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1007\/s40565-018-0423-3","volume":"6","author":"AG Phadke","year":"2018","unstructured":"Phadke AG, Bi T (2018) Phasor measurement units, WAMS, and their applications in protection and control of power systems. J Modern Power Syst Clean Energy 6(4):619\u2013629","journal-title":"J Modern Power Syst Clean Energy"},{"issue":"1","key":"6106_CR2","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1109\/TPWRD.2016.2590961","volume":"32","author":"S Brahma","year":"2016","unstructured":"Brahma S, Kavasseri R, Cao H, Chaudhuri N, Alexopoulos T, Cui Y (2016) Real-time identification of dynamic events in power systems using pmu data, and potential applications\u2013models, promises, and challenges. IEEE Trans Power Deliv 32(1):294\u2013301","journal-title":"IEEE Trans Power Deliv"},{"issue":"1","key":"6106_CR3","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/TPWRD.2011.2168831","volume":"27","author":"EE Bernabeu","year":"2011","unstructured":"Bernabeu EE, Thorp JS, Centeno V (2011) Methodology for a security\/dependability adaptive protection scheme based on data mining. IEEE Trans Power Deliv 27(1):104\u2013111","journal-title":"IEEE Trans Power Deliv"},{"issue":"2","key":"6106_CR4","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1109\/61.997902","volume":"17","author":"J Tan","year":"2002","unstructured":"Tan J, Crossley P, McLaren P, Gale P, Hall I, Farrell J (2002) Application of a wide area backup protection expert system to prevent cascading outages. IEEE Trans Power Deliv 17(2):375\u2013380","journal-title":"IEEE Trans Power Deliv"},{"issue":"4","key":"6106_CR5","doi-asserted-by":"publisher","first-page":"1855","DOI":"10.1109\/TPWRD.2016.2520958","volume":"31","author":"M Biswal","year":"2016","unstructured":"Biswal M, Brahma SM, Cao H (2016) Supervisory protection and automated event diagnosis using pmu data. IEEE Trans Power Deliv 31(4):1855\u20131863","journal-title":"IEEE Trans Power Deliv"},{"issue":"3","key":"6106_CR6","doi-asserted-by":"publisher","first-page":"1124","DOI":"10.1109\/TPWRD.2011.2174808","volume":"27","author":"K Seethalekshmi","year":"2012","unstructured":"Seethalekshmi K, Singh SN, Srivastava SC (2012) A classification approach using support vector machines to prevent distance relay maloperation under power swing and voltage instability. IEEE Trans Power Deliv 27(3):1124\u20131133","journal-title":"IEEE Trans Power Deliv"},{"issue":"4","key":"6106_CR7","doi-asserted-by":"publisher","first-page":"3161","DOI":"10.1109\/JSYST.2017.2694453","volume":"12","author":"MK Jena","year":"2017","unstructured":"Jena MK, Samantaray SR, Panigrahi BK (2017) A new decentralized approach to wide-area back-up protection of transmission lines. IEEE Syst J 12(4):3161\u20133168","journal-title":"IEEE Syst J"},{"issue":"3","key":"6106_CR8","doi-asserted-by":"publisher","first-page":"3337","DOI":"10.1109\/JSYST.2018.2879874","volume":"13","author":"S Das","year":"2018","unstructured":"Das S, Panigrahi BK (2018) Real-time secured third zone relay operation under dynamic stressed conditions. IEEE Syst J 13(3):3337\u20133346","journal-title":"IEEE Syst J"},{"issue":"5","key":"6106_CR9","first-page":"5066","volume":"10","author":"S Samantaray","year":"2018","unstructured":"Samantaray S, Sharma A et al (2018) Enhancing performance of wide-area back-up protection scheme using pmu assisted dynamic state estimator. IEEE Trans Smart Grid 10(5):5066\u20135074","journal-title":"IEEE Trans Smart Grid"},{"key":"6106_CR10","doi-asserted-by":"crossref","unstructured":"Khan R, McLaughlin K, Laverty JHD, David H, Sezer S (2018) Demonstrating cyber-physical attacks and defense for synchrophasor technology in smart grid, In: 2018 16th Annual Conference on Privacy, Security and Trust (PST). IEEE, 2018, pp. 1\u201310","DOI":"10.1109\/PST.2018.8514197"},{"issue":"5","key":"6106_CR11","doi-asserted-by":"publisher","first-page":"4601","DOI":"10.1109\/TSG.2017.2665461","volume":"9","author":"MS Almas","year":"2017","unstructured":"Almas MS, Vanfretti L, Singh RS, Jonsdottir GM (2017) Vulnerability of synchrophasor-based WAMPAC applications\u2019 to time synchronization spoofing. IEEE Trans Smart Grid 9(5):4601\u20134612","journal-title":"IEEE Trans Smart Grid"},{"issue":"5","key":"6106_CR12","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1109\/MC.2019.2960748","volume":"53","author":"A Chawla","year":"2020","unstructured":"Chawla A, Agrawal P, Singh A, Panigrahi BK, Paul K, Bhalja B (2020) Denial-of-service resilient frameworks for synchrophasor-based wide area monitoring systems. Computer 53(5):14\u201324","journal-title":"Computer"},{"key":"6106_CR13","unstructured":"Initiative NAS et\u00a0al. (2015) Naspi 2014 survey of synchrophasor system networks-results and findings, North American SynchroPhasor Initiative (NASPI)"},{"issue":"4","key":"6106_CR14","doi-asserted-by":"publisher","first-page":"1980","DOI":"10.1109\/TSG.2014.2302016","volume":"5","author":"K Martin","year":"2014","unstructured":"Martin K, Brunello G, Adamiak M, Antonova G, Begovic M, Benmouyal G, Bui P, Falk H, Gharpure V, Goldstein A et al (2014) An overview of the IEEE standard C37.118.2\u2014synchrophasor data transfer for power systems. IEEE Trans Smart Grid 5(4):1980\u20131984","journal-title":"IEEE Trans Smart Grid"},{"key":"6106_CR15","unstructured":"Case DU (2016) Analysis of the cyber attack on the ukrainian power grid, Electricity Information Sharing and Analysis Center (E-ISAC), vol. 388"},{"issue":"3","key":"6106_CR16","first-page":"1636","volume":"9","author":"A Ashok","year":"2016","unstructured":"Ashok A, Govindarasu M, Ajjarapu V (2016) Online detection of stealthy false data injection attacks in power system state estimation. IEEE Trans Smart Grid 9(3):1636\u20131646","journal-title":"IEEE Trans Smart Grid"},{"issue":"2","key":"6106_CR17","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1109\/TSG.2014.2298195","volume":"5","author":"S Sridhar","year":"2014","unstructured":"Sridhar S, Govindarasu M (2014) Model-based attack detection and mitigation for automatic generation control. IEEE Trans Smart Grid 5(2):580\u2013591","journal-title":"IEEE Trans Smart Grid"},{"issue":"7","key":"6106_CR18","doi-asserted-by":"publisher","first-page":"3271","DOI":"10.1109\/TII.2018.2825243","volume":"14","author":"J James","year":"2018","unstructured":"James J, Hou Y, Li VO (2018) Online false data injection attack detection with wavelet transform and deep neural networks. IEEE Trans Ind Inf 14(7):3271\u20133280","journal-title":"IEEE Trans Ind Inf"},{"issue":"6","key":"6106_CR19","doi-asserted-by":"publisher","first-page":"5227","DOI":"10.1109\/TSG.2020.3004303","volume":"11","author":"M Ghafouri","year":"2020","unstructured":"Ghafouri M, Au M, Kassouf M, Debbabi M, Assi C, Yan J (2020) Detection and mitigation of cyber attacks on voltage stability monitoring of smart grids. IEEE Trans Smart Grid 11(6):5227\u20135238","journal-title":"IEEE Trans Smart Grid"},{"issue":"2","key":"6106_CR20","doi-asserted-by":"publisher","first-page":"1188","DOI":"10.1109\/TPWRS.2019.2939192","volume":"35","author":"Y Chakhchoukh","year":"2019","unstructured":"Chakhchoukh Y, Lei H, Johnson BK (2019) Diagnosis of outliers and cyber attacks in dynamic pmu-based power state estimation. IEEE Trans Power Syst 35(2):1188\u20131197","journal-title":"IEEE Trans Power Syst"},{"issue":"4","key":"6106_CR21","doi-asserted-by":"publisher","first-page":"4401","DOI":"10.1109\/TSG.2018.2859339","volume":"10","author":"J Wang","year":"2018","unstructured":"Wang J, Shi D, Li Y, Chen J, Ding H, Duan X (2018) Distributed framework for detecting pmu data manipulation attacks with deep autoencoders. IEEE Trans Smart Grid 10(4):4401\u20134410","journal-title":"IEEE Trans Smart Grid"},{"issue":"5","key":"6106_CR22","doi-asserted-by":"publisher","first-page":"5057","DOI":"10.1109\/TSG.2017.2679122","volume":"9","author":"S Pal","year":"2017","unstructured":"Pal S, Sikdar B, Chow JH (2017) Classification and detection of pmu data manipulation attacks using transmission line parameters. IEEE Trans Smart Grid 9(5):5057\u20135066","journal-title":"IEEE Trans Smart Grid"},{"issue":"1","key":"6106_CR23","doi-asserted-by":"publisher","first-page":"710","DOI":"10.1109\/JSYST.2017.2741483","volume":"13","author":"AS Musleh","year":"2017","unstructured":"Musleh AS, Khalid HM, Muyeen S, Al-Durra A (2017) A prediction algorithm to enhance grid resilience toward cyber attacks in wamcs applications. IEEE Syst J 13(1):710\u2013719","journal-title":"IEEE Syst J"},{"issue":"4","key":"6106_CR24","doi-asserted-by":"publisher","first-page":"2026","DOI":"10.1109\/TSG.2016.2544854","volume":"7","author":"HM Khalid","year":"2016","unstructured":"Khalid HM, Peng JC-H (2016) A bayesian algorithm to enhance the resilience of WAMS applications against cyber attacks. IEEE Trans Smart Grid 7(4):2026\u20132037","journal-title":"IEEE Trans Smart Grid"},{"issue":"3","key":"6106_CR25","doi-asserted-by":"publisher","first-page":"3010","DOI":"10.1109\/TSG.2018.2817046","volume":"10","author":"C Cameron","year":"2018","unstructured":"Cameron C, Patsios C, Taylor PC, Pourmirza Z (2018) Using self-organizing architectures to mitigate the impacts of denial-of-service attacks on voltage control schemes. IEEE Trans Smart Grid 10(3):3010\u20133019","journal-title":"IEEE Trans Smart Grid"},{"key":"6106_CR26","doi-asserted-by":"crossref","unstructured":"Siami-Namini S, Tavakoli N, Namin AS (2018) A comparison of ARIMA and LSTM in forecasting time series. In: 2018 17th IEEE international conference on machine learning and applications (ICMLA). IEEE,  pp 1394\u20131401","DOI":"10.1109\/ICMLA.2018.00227"},{"issue":"2","key":"6106_CR27","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/s00521-015-1874-3","volume":"27","author":"G-G Wang","year":"2016","unstructured":"Wang G-G, Lu M, Dong Y-Q, Zhao X-J (2016) Self-adaptive extreme learning machine. Neural Comput Appl 27(2):291\u2013303","journal-title":"Neural Comput Appl"},{"issue":"8","key":"6106_CR28","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"6106_CR29","doi-asserted-by":"crossref","unstructured":"Gers FA, Schmidhuber J, Cummins F (1999) Learning to forget: continual prediction with LSTM. In: Ninth international conference on artificial neural networks ICANN 99.  pp 850\u2013855","DOI":"10.1049\/cp:19991218"},{"issue":"2","key":"6106_CR30","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/s00521-009-0295-6","volume":"19","author":"PJ Garc\u00eda-Laencina","year":"2010","unstructured":"Garc\u00eda-Laencina PJ, Sancho-G\u00f3mez J-L, Figueiras-Vidal AR (2010) Pattern classification with missing data: a review. Neural Comput Appl 19(2):263\u2013282","journal-title":"Neural Comput Appl"},{"key":"6106_CR31","unstructured":"Yoon J, Jordon J, Schaar M (2018) GAIN: missing data imputation using generative adversarial nets. In: International conference on machine learning, PMLR.  pp 5689\u20135698"},{"key":"6106_CR32","unstructured":"Goodfellow IJ, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial networks, arXiv preprint arXiv:1406.2661"},{"issue":"1","key":"6106_CR33","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1109\/TPWRD.2005.860244","volume":"21","author":"SH Horowitz","year":"2006","unstructured":"Horowitz SH, Phadke AG (2006) Third zone revisited. IEEE Trans Power Deliv 21(1):23\u201329","journal-title":"IEEE Trans Power Deliv"},{"key":"6106_CR34","doi-asserted-by":"crossref","unstructured":"Phadke AG, Thorp JS (2010) Communication needs for wide area measurement applications, In: 2010 5th International Conference on Critical Infrastructure (CRIS), 2010, pp. 1\u20137","DOI":"10.1109\/CRIS.2010.5617484"},{"issue":"7","key":"6106_CR35","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.1007\/s00521-015-1923-y","volume":"31","author":"G-G Wang","year":"2019","unstructured":"Wang G-G, Deb S, Cui Z (2019) Monarch butterfly optimization. Neural Comput Appl 31(7):1995\u20132014","journal-title":"Neural Comput Appl"},{"key":"6106_CR36","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Future Gen Comput Syst 97:849\u2013872","journal-title":"Future Gen Comput Syst"},{"issue":"9","key":"6106_CR37","doi-asserted-by":"publisher","first-page":"1415","DOI":"10.3390\/math8091415","volume":"8","author":"J Li","year":"2020","unstructured":"Li J, Lei H, Alavi AH, Wang G-G (2020) Elephant herding optimization: variants, hybrids, and applications. Mathematics 8(9):1415","journal-title":"Mathematics"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06106-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06106-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06106-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T15:02:35Z","timestamp":1676041355000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06106-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,4]]},"references-count":37,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["6106"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06106-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,4]]},"assertion":[{"value":"6 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 June 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}