{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T03:19:34Z","timestamp":1783567174962,"version":"3.55.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"23","license":[{"start":{"date-parts":[[2020,7,21]],"date-time":"2020-07-21T00:00:00Z","timestamp":1595289600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,7,21]],"date-time":"2020-07-21T00:00:00Z","timestamp":1595289600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1007\/s00521-020-05189-8","type":"journal-article","created":{"date-parts":[[2020,7,21]],"date-time":"2020-07-21T11:02:45Z","timestamp":1595329365000},"page":"17361-17378","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":108,"title":["Anomaly detection via blockchained deep learning smart contracts in industry 4.0"],"prefix":"10.1007","volume":"32","author":[{"given":"Konstantinos","family":"Demertzis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6404-1528","authenticated-orcid":false,"given":"Lazaros","family":"Iliadis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikos","family":"Tziritas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panagiotis","family":"Kikiras","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,7,21]]},"reference":[{"key":"5189_CR1","doi-asserted-by":"crossref","unstructured":"Bassi L (2017) Industry 4.0: hope, hype or revolution? In: 2017 IEEE 3rd international forum on research and technologies for society and industry (RTSI), Modena, 2017, pp 1\u20136","DOI":"10.1109\/RTSI.2017.8065927"},{"key":"5189_CR2","doi-asserted-by":"crossref","unstructured":"Lee J, Bagheri B, Kao H-A (2015) A cyber-physical systems architecture for industry 4.0-based manufacturing systems, vol 3, 2015, pp 18\u201323","DOI":"10.1016\/j.mfglet.2014.12.001"},{"key":"5189_CR3","doi-asserted-by":"crossref","unstructured":"Gilchrist A (2016) Industry 4.0: the industrial internet of things, Publisher: A press, Release Date: June 2016, ISBN: 9781484220474","DOI":"10.1007\/978-1-4842-2047-4"},{"issue":"8","key":"5189_CR4","doi-asserted-by":"publisher","first-page":"2941","DOI":"10.1080\/00207543.2018.1444806","volume":"56","author":"LD Xu","year":"2018","unstructured":"Xu LD, Xu EL, Li L (2018) Industry 4.0: state of the art and future trends. Int J Prod Res 56(8):2941\u20132962","journal-title":"Int J Prod Res"},{"key":"5189_CR5","doi-asserted-by":"crossref","unstructured":"Zhou K, Liu T, Zhou L (2015) Industry 4.0: towards future industrial opportunities and challenges. In: 2015 12th international conference on fuzzy systems and knowledge discovery (FSKD), Zhangjiajie, 2015, pp 2147\u20132152","DOI":"10.1109\/FSKD.2015.7382284"},{"key":"5189_CR6","doi-asserted-by":"crossref","unstructured":"El Hamdi S, Abouabdellah A, Oudani M (2019) Industry 4.0: fundamentals and main challenges. In: 2019 international colloquium on logistics and supply chain management (LOGISTIQUA), Montreuil\u2014Paris, France, 2019, pp 1\u20135","DOI":"10.1109\/LOGISTIQUA.2019.8907280"},{"issue":"3","key":"5189_CR7","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1109\/EMR.2019.2927559","volume":"47","author":"G Culot","year":"2019","unstructured":"Culot G, Fattori F, Podrecca M, Sartor M (2019) Addressing industry 4.0 cybersecurity challenges. IEEE Eng Manag Rev 47(3):79\u201386","journal-title":"IEEE Eng Manag Rev"},{"key":"5189_CR8","doi-asserted-by":"crossref","unstructured":"Sklyar V, Kharchenko V (2019) ENISA documents in cybersecurity assurance for industry 4.0: IIoT threats and attacks scenarios. In: 2019 10th IEEE international conference on intelligent data acquisition and advanced computing systems: technology and applications (IDAACS), Metz, France, 2019, pp 1046\u20131049","DOI":"10.1109\/IDAACS.2019.8924452"},{"issue":"5","key":"5189_CR9","doi-asserted-by":"publisher","first-page":"8182","DOI":"10.1109\/JIOT.2019.2935189","volume":"6","author":"F Meneghello","year":"2019","unstructured":"Meneghello F, Calore M, Zucchetto D, Polese M, Zanella A (2019) IoT: Internet of Threats? A survey of practical security vulnerabilities in real IoT devices. IEEE Internet Things J 6(5):8182\u20138201","journal-title":"IEEE Internet Things J"},{"issue":"1","key":"5189_CR10","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1109\/MITP.2013.7","volume":"15","author":"C Sample","year":"2013","unstructured":"Sample C, Schaffer K (2013) An overview of anomaly detection. IT Prof 15(1):8\u201311","journal-title":"IT Prof"},{"key":"5189_CR11","doi-asserted-by":"crossref","unstructured":"Dixit M, Tiwari A, Pathak H, Astya R (2018) An overview of deep learning architectures, libraries and its applications areas. In: 2018 international conference on advances in computing, communication control and networking (ICACCCN), Greater Noida (UP), India, 2018, pp 293\u2013297","DOI":"10.1109\/ICACCCN.2018.8748442"},{"key":"5189_CR12","doi-asserted-by":"crossref","unstructured":"Chen CLP (2015) Deep learning for pattern learning and recognition. In: 2015 IEEE 10th jubilee international symposium on applied computational intelligence and informatics, Timisoara, 2015, pp 17\u201317","DOI":"10.1109\/SACI.2015.7208200"},{"key":"5189_CR13","unstructured":"Schmidhuber J Deep learning in neural networks: an overview. arXiv:1404.7828v4 [cs.NE]"},{"key":"5189_CR14","doi-asserted-by":"crossref","unstructured":"Chatterjee R, Chatterjee R (2017) An overview of the emerging technology: blockchain. In: 2017 3rd international conference on computational intelligence and networks (CINE), Odisha, 2017, pp 126\u2013127","DOI":"10.1109\/CINE.2017.33"},{"key":"5189_CR15","doi-asserted-by":"crossref","unstructured":"Mermer GB, Zeydan E, Arslan SS (2018) An overview of blockchain technologies: principles, opportunities and challenges. In: 2018 26th signal processing and communications applications conference (SIU), Izmir, 2018, pp 1\u20134","DOI":"10.1109\/SIU.2018.8404513"},{"issue":"6","key":"5189_CR16","doi-asserted-by":"publisher","first-page":"1442","DOI":"10.1109\/TCSS.2019.2924054","volume":"6","author":"S Zhao","year":"2019","unstructured":"Zhao S, Li S, Yao Y (2019) Blockchain enabled industrial internet of things technology. IEEE Trans Comput Soc Syst 6(6):1442\u20131453","journal-title":"IEEE Trans Comput Soc Syst"},{"issue":"11","key":"5189_CR17","doi-asserted-by":"publisher","first-page":"2266","DOI":"10.1109\/TSMC.2019.2895123","volume":"49","author":"S Wang","year":"2019","unstructured":"Wang S, Ouyang L, Yuan Y, Ni X, Han X, Wang F (2019) Blockchain-enabled smart contracts: architecture, applications, and future trends. IEEE Trans Syst Man Cybern Syst 49(11):2266\u20132277","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"5189_CR18","doi-asserted-by":"crossref","unstructured":"Mohanta BK, Panda SS, Jena D (2018) An overview of smart contract and use cases in blockchain technology. In: 2018 9th international conference on computing, communication and networking technologies (ICCCNT), Bangalore, 2018, pp 1\u20134","DOI":"10.1109\/ICCCNT.2018.8494045"},{"key":"5189_CR19","doi-asserted-by":"crossref","unstructured":"Abbas QE, Sung-Bong J (2019) A survey of blockchain and its applications. In: 2019 international conference on artificial intelligence in information and communication (ICAIIC), Okinawa, Japan, 2019, pp 001\u2013003","DOI":"10.1109\/ICAIIC.2019.8669067"},{"key":"5189_CR20","unstructured":"Andersen MP, Kolb J, Chen K, Fierro G, Culler DE, Popa RA (2017) WAVE: a decentralized authorization system for IoT via blockchain smart contracts. Technical report no. UCB\/EECS-2017-234, Dec 29, 2017"},{"key":"5189_CR21","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","volume":"61","author":"J\u00fcrgen Schmidhuber","year":"2015","unstructured":"Schmidhuber J\u00fcrgen (2015) Deep learning in neural networks: an overview. Neural Netw 61:85\u2013117","journal-title":"Neural Netw"},{"key":"5189_CR22","unstructured":"Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press. http:\/\/www.deeplearningbook.org. Accessed 22 Feb 2019"},{"issue":"2","key":"5189_CR23","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc Ser B (Stat Methodol) 67(2):301\u2013320","journal-title":"J R Stat Soc Ser B (Stat Methodol)"},{"key":"5189_CR24","doi-asserted-by":"crossref","unstructured":"Chen Z, Yeo CK, Lee BS, Lau CT (2018) Autoencoder-based network anomaly detection. In: 2018 wireless telecommunications symposium (WTS), Phoenix, AZ, 2018, pp 1\u20135","DOI":"10.1109\/WTS.2018.8363930"},{"key":"5189_CR25","volume-title":"Progress in pattern recognition, image analysis, computer vision, and applications. CIARP 2018. Lecture notes in computer science","author":"IA Fern\u00e1ndez-Sa\u00faco","year":"2019","unstructured":"Fern\u00e1ndez-Sa\u00faco IA, Acosta-Mendoza N, Gago-Alonso A, Garc\u00eda-Reyes EB (2019) Computing anomaly score threshold with autoencoders pipeline. In: Vera-Rodriguez R, Fierrez J, Morales A (eds) Progress in pattern recognition, image analysis, computer vision, and applications. CIARP 2018. Lecture notes in computer science, vol 11401. Springer, Cham"},{"issue":"6","key":"5189_CR26","doi-asserted-by":"publisher","first-page":"4486","DOI":"10.1109\/JIOT.2018.2822842","volume":"5","author":"G Falco","year":"2018","unstructured":"Falco G, Caldera C, Shrobe H (2018) IIoT cybersecurity risk modeling for SCADA Systems. IEEE Internet Things J 5(6):4486\u20134495","journal-title":"IEEE Internet Things J"},{"key":"5189_CR27","doi-asserted-by":"crossref","unstructured":"Al-Dalky R, Abduljaleel O, Salah K, Otrok H, Al-Qutayri M (2014) A modbus traffic generator for evaluating the security of SCADA systems. In: 2014 9th international symposium on communication systems, networks & digital sign (CSNDSP), Manchester, 2014, pp 809\u2013814","DOI":"10.1109\/CSNDSP.2014.6923938"},{"key":"5189_CR28","doi-asserted-by":"crossref","unstructured":"Fachkha C (2019) Cyber threat investigation of SCADA modbus activities. In: 2019 10th IFIP international conference on new technologies, mobility and security (NTMS), CANARY ISLANDS, Spain, 2019, pp 1\u20137","DOI":"10.1109\/NTMS.2019.8763817"},{"key":"5189_CR29","volume-title":"Handbook of big data and IoT security","author":"S Grooby","year":"2019","unstructured":"Grooby S, Dargahi T, Dehghantanha A (2019) Protecting IoT and ICS platforms against advanced persistent threat actors: analysis of APT1, silent chollima and molerats. In: Dehghantanha A, Choo KK (eds) Handbook of big data and IoT security. Springer, Cham"},{"key":"5189_CR30","doi-asserted-by":"publisher","DOI":"10.1109\/tsg.2015.2409775","author":"S Pan","year":"2015","unstructured":"Pan S, Morris T, Adhikari U (2015) Developing a hybrid intrusion detection system using data mining for power systems. IEEE Trans Smart Grid. https:\/\/doi.org\/10.1109\/tsg.2015.2409775","journal-title":"IEEE Trans Smart Grid"},{"key":"5189_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tii.2015.2420951","volume":"1","author":"S Pan","year":"2015","unstructured":"Pan S, Morris T, Adhikari U (2015) Classification of disturbances and cyber-attacks in power systems using heterogeneous time-synchronized data. IEEE Trans Ind Inform 1:1. https:\/\/doi.org\/10.1109\/tii.2015.2420951","journal-title":"IEEE Trans Ind Inform"},{"issue":"2","key":"5189_CR32","first-page":"174","volume":"17","author":"S Pan","year":"2015","unstructured":"Pan S, Morris T, Adhikari U (2015) A specification-based intrusion detection framework for cyber-physical environment in electric power system. Int J Netw Secur 17(2):174\u2013188","journal-title":"Int J Netw Secur"},{"key":"5189_CR33","unstructured":"Beaver J, Borges R, Buckner M, Morris T, Adhikari U, Pan S (2014) Machine learning for power system disturbance and cyber-attack discrimination. In: Proceedings of the 7th international symposium on resilient control systems, Aug 19\u201321, 2014, Denver, CO, USA"},{"key":"5189_CR34","doi-asserted-by":"crossref","unstructured":"Wenzhu S, Wenting H, Zufeng X, Jianping C (2019) Overview of one-class classification. In: 2019 IEEE 4th international conference on signal and image processing (ICSIP), Wuxi, China, 2019, pp 6\u201310","DOI":"10.1109\/SIPROCESS.2019.8868559"},{"issue":"5\u20136","key":"5189_CR35","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1080\/713827180","volume":"17","author":"Shichao Zhang","year":"2003","unstructured":"Zhang Shichao, Zhang Chengqi, Yang Qiang (2003) Data preparation for data mining. Appl Artif Intell 17(5\u20136):375\u2013381","journal-title":"Appl Artif Intell"},{"issue":"1","key":"5189_CR36","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/34.824819","volume":"22","author":"J Mao","year":"2000","unstructured":"Mao J, Jain AK, Duin PW (2000) Statistical pattern recognition: a review. IEEE Trans Pattern Anal Mach Intell 22(1):4\u201337","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"8","key":"5189_CR37","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","volume":"27","author":"T Fawcett","year":"2006","unstructured":"Fawcett T (2006) An introduction to ROC analysis. Pattern Recognit Lett 27(8):861\u2013874","journal-title":"Pattern Recognit Lett"},{"key":"5189_CR38","doi-asserted-by":"publisher","first-page":"35","DOI":"10.3390\/bdcc2040035","volume":"2","author":"K Demertzis","year":"2018","unstructured":"Demertzis K, Kikiras P, Tziritas N, Sanchez SL, Iliadis L (2018) The next generation cognitive security operations center: network flow forensics using cybersecurity intelligence. Big Data Cogn Comput 2:35","journal-title":"Big Data Cogn Comput"},{"key":"5189_CR39","doi-asserted-by":"publisher","first-page":"6","DOI":"10.3390\/bdcc3010006","volume":"3","author":"K Demertzis","year":"2019","unstructured":"Demertzis K, Tziritas N, Kikiras P, Sanchez SL, Iliadis L (2019) The next generation cognitive security operations center: adaptive analytic lambda architecture for efficient defense against adversarial attacks. Big Data Cogn Comput 3:6","journal-title":"Big Data Cogn Comput"},{"key":"5189_CR40","doi-asserted-by":"crossref","unstructured":"Demertzis K, Iliadis L, Kikiras P, Tziritas N (2019) Cyber-typhon: an online multi-task anomaly detection framework. In: MacIntyre J, Maglogiannis I, Iliadis L, Pimenidis E (eds) Artificial intelligence applications and innovations. AIAI 2019. IFIP advances in information and communication technology, vol 559. Springer, Cham","DOI":"10.1007\/978-3-030-19823-7_2"},{"key":"5189_CR41","unstructured":"Korda N, Szorenyi B, Li S (2016) Distributed clustering of linear bandits in peer to peer networks. In: ICML\u201916: proceedings of the 33rd international conference on international conference on machine learning, vol 48, June 2016, pp 1301\u20131309"},{"key":"5189_CR42","doi-asserted-by":"publisher","unstructured":"Li S, Karatzoglou A, Gentile C (2016) Collaborative filtering bandits. In: Proceedings of the 39th international ACM SIGIR conference on research and development in information retrieval (SIGIR\u201916). Association for Computing Machinery, New York, NY, USA, pp 539\u2013548. https:\/\/doi.org\/10.1145\/2911451.2911548","DOI":"10.1145\/2911451.2911548"},{"key":"5189_CR43","doi-asserted-by":"publisher","first-page":"553","DOI":"10.3390\/su8060553","volume":"8","author":"F Hao","year":"2016","unstructured":"Hao F, Park D-S, Li S, Lee HM (2016) Mining \u03bb-maximal cliques from a fuzzy graph. Sustainability 8:553","journal-title":"Sustainability"},{"key":"5189_CR44","unstructured":"Gentile C, Li S, Zappella G (2014) Online clustering of bandits. In: Proceedings of the 31st international conference on international conference on machine learning, vol 32 (ICML\u201914). JMLR.org, II\u2013757\u2013II\u2013765"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05189-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-05189-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05189-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,20]],"date-time":"2021-07-20T23:49:22Z","timestamp":1626824962000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-05189-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,21]]},"references-count":44,"journal-issue":{"issue":"23","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["5189"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-05189-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,21]]},"assertion":[{"value":"23 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}