{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T01:46:36Z","timestamp":1773279996229,"version":"3.50.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T00:00:00Z","timestamp":1652227200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T00:00:00Z","timestamp":1652227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Liaoning Provincial Department of Education","award":["LJKZ0208"],"award-info":[{"award-number":["LJKZ0208"]}]},{"DOI":"10.13039\/501100004314","name":"Shenyang Aerospace University","doi-asserted-by":"publisher","award":["18YB06"],"award-info":[{"award-number":["18YB06"]}],"id":[{"id":"10.13039\/501100004314","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"crossref","award":["JCKY2018410C004"],"award-info":[{"award-number":["JCKY2018410C004"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s11227-022-04542-z","type":"journal-article","created":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T19:25:15Z","timestamp":1652297115000},"page":"16876-16897","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Network attack detection scheme based on variational quantum neural network"],"prefix":"10.1007","volume":"78","author":[{"given":"Changqing","family":"Gong","sequence":"first","affiliation":[]},{"given":"Weiqi","family":"Guan","sequence":"additional","affiliation":[]},{"given":"Abdullah","family":"Gani","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4278-8740","authenticated-orcid":false,"given":"Han","family":"Qi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,11]]},"reference":[{"key":"4542_CR1","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.neunet.2020.02.009","volume":"125","author":"J Ukita","year":"2020","unstructured":"Ukita J (2020) Causal importance of low-level feature selectivity for generalization in image recognition. Neural Netw 125:185\u2013193","journal-title":"Neural Netw"},{"issue":"3","key":"4542_CR2","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/s11128-020-2603-0","volume":"19","author":"C Gong","year":"2020","unstructured":"Gong C, Du J (2020) Grover algorithm-based quantum homomorphic encryption ciphertext retrieval scheme in quantum cloud computing. Quantum Inf Process 19(3):105","journal-title":"Quantum Inf Process"},{"key":"4542_CR3","doi-asserted-by":"crossref","unstructured":"Gong C, Shi T (2020) An improved quantum genetic algorithms and application for ddos attack detection. In: 2019 IEEE International Conference on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking (ISPA\/BDCloud\/SocialCom\/SustainCom)","DOI":"10.1109\/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00068"},{"issue":"7779","key":"4542_CR4","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1038\/s41586-019-1666-5","volume":"574","author":"BR AruteF","year":"2019","unstructured":"AruteF BR, Arya K (2019) Quantum supremacy using a programmable superconducting processor. Nature 574(7779):505\u2013510","journal-title":"Nature"},{"issue":"3\u20134","key":"4542_CR5","first-page":"143","volume":"52","author":"SC Kak","year":"1995","unstructured":"Kak SC (1995) Quantum neural computing. Syst Control Inf 52(3\u20134):143\u2013160","journal-title":"Syst Control Inf"},{"issue":"1","key":"4542_CR6","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/S1004-4132(08)60063-8","volume":"19","author":"P Li","year":"2008","unstructured":"Li P, Li S (2008) Learning algorithm and application of quantum bp neural networks based on universal quantum gates. J Syst Eng Electron 19(1):167\u2013174","journal-title":"J Syst Eng Electron"},{"issue":"4","key":"4542_CR7","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.98.042308","volume":"98","author":"R Patrick","year":"2018","unstructured":"Patrick R, Thomas B, Christian W, Seth L (2018) Quantum hopfield neural network. Phys Rev A 98(4):042308","journal-title":"Phys Rev A"},{"key":"4542_CR8","doi-asserted-by":"crossref","unstructured":"Leonardo B, Nicola P, Sougato B (2016) Quantum gate learning in qubit networks: toffoli gate without time-dependent control. npj Quantum Inf 2:16019","DOI":"10.1038\/npjqi.2016.19"},{"key":"4542_CR9","doi-asserted-by":"publisher","first-page":"79","DOI":"10.22331\/q-2018-08-06-79","volume":"2","author":"J P","year":"2018","unstructured":"P J (2018) Quantum computing in the nisq era and beyond. Quantum 2:79","journal-title":"Quantum"},{"issue":"6","key":"4542_CR10","doi-asserted-by":"publisher","first-page":"62317","DOI":"10.1103\/PhysRevA.95.062317","volume":"95","author":"Z Jiang","year":"2017","unstructured":"Jiang Z, Zhihui W, Rieffel EG (2017) Near-optimal quantum circuit for Grover's unstructured search using a transverse field. Phys Rev A 95(6):62317","journal-title":"Phys Rev A"},{"key":"4542_CR11","doi-asserted-by":"publisher","first-page":"5585","DOI":"10.1109\/TIT.2020.3004427","volume":"69","author":"C Huang","year":"2020","unstructured":"Huang C, Newman M SM (2020) Explicit lower bounds on strong quantum simulation. IEEE Trans Inf Theory 69:5585\u20135600","journal-title":"IEEE Trans Inf Theory"},{"key":"4542_CR12","doi-asserted-by":"publisher","first-page":"999","DOI":"10.1109\/TCAD.2020.3019987","volume":"40","author":"A Cintas Canto","year":"2021","unstructured":"Cintas Canto A, Kermani MM, Azarderakhsh R (2021) Reliable architectures for composite-field-oriented constructions of McEliece post-quantum cryptography on FPGA. IEEE Trans Comput Aided Des Integr Circuits Syst 40:999\u20131003","journal-title":"IEEE Trans Comput Aided Des Integr Circuits Syst"},{"key":"4542_CR13","doi-asserted-by":"publisher","first-page":"94015","DOI":"10.1103\/PhysRevD.101.094015","volume":"101","author":"AY Wei","year":"2020","unstructured":"Wei AY, Wea HA, Naik P (2020) Quantum algorithms for jet clustering. Phys Rev D 101:94015","journal-title":"Phys Rev D"},{"key":"4542_CR14","doi-asserted-by":"publisher","first-page":"94310","DOI":"10.1109\/ACCESS.2019.2929084","volume":"7","author":"P-H Qiu","year":"2019","unstructured":"Qiu P-H, SY M, Chen XG (2019) Detecting entanglement with deep quantum neural networks. IEEE Access 7:94310\u201394320","journal-title":"IEEE Access"},{"key":"4542_CR15","doi-asserted-by":"publisher","first-page":"828","DOI":"10.3390\/e22080828","volume":"22","author":"RKS Xia","year":"2020","unstructured":"Xia RKS (2020) Hybrid quantum-classical neural network for calculating ground state energies of molecules. Entropy 22:828","journal-title":"Entropy"},{"key":"4542_CR16","doi-asserted-by":"publisher","first-page":"124114","DOI":"10.1063\/1.5141458","volume":"152","author":"IAF VerteletskyiV","year":"2020","unstructured":"VerteletskyiV IAF, Yen TC (2020) Measurement optimization in the variational quantum eigensolver using a minimum clique cover. J Chem Phys 152:124114","journal-title":"J Chem Phys"},{"key":"4542_CR17","doi-asserted-by":"publisher","first-page":"60501","DOI":"10.1103\/PhysRevLett.122.060501","volume":"122","author":"PGJ PepperA","year":"2019","unstructured":"PepperA PGJ, Tischler N (2019) Experimental realization of a quantum autoencoder: the compression of qutrits via machine learning. Phys Rev Lett 122:60501","journal-title":"Phys Rev Lett"},{"key":"4542_CR18","first-page":"21067","volume":"10","author":"L Zhou","year":"2020","unstructured":"Zhou L, Sea C, Wang ST (2020) Quantum approximate optimization algorithm: performance, mechanism, and implementation on near-term devices. Phys Rev X 10:21067","journal-title":"Phys Rev X"},{"key":"4542_CR19","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1038\/s41567-019-0648-8","volume":"15","author":"I Cong","year":"2019","unstructured":"Cong I, Choi LMDS (2019) Quantum convolutional neural networks. Nat Phys 15:1273\u20131278","journal-title":"Nat Phys"},{"key":"4542_CR20","first-page":"13","volume":"634","author":"C Dubosq","year":"2020","unstructured":"Dubosq C, Calvo RMEAF (2020) Quantum modeling of the optical spectra of carbon cluster structural families and relation to the interstellar extinction uv bump. Astromy Astrophyscs 634:13","journal-title":"Astromy Astrophyscs"},{"key":"4542_CR21","volume-title":"A hybrid quantum-classical neural network with deep residual learning","author":"WP YanyingLiang","year":"2021","unstructured":"YanyingLiang WP, Zhu-JunZheng OS, Zhao G (2021) A hybrid quantum-classical neural network with deep residual learning. Elsevier, New York"},{"key":"4542_CR22","doi-asserted-by":"crossref","unstructured":"SteveAbel JCC, Spannowsky M (2022) Completely quantum neural networks. CoRR","DOI":"10.1103\/PhysRevA.106.022601"},{"key":"4542_CR23","unstructured":"Yevhenii T, SergiiStirenko OROAEP, Gordienko Y (2021) Hybrid classic-quantum neural networks for image classification. In: The 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications"},{"key":"4542_CR24","unstructured":"JunQi CHHY, Chen P (2021) Qtn-vqc: an end-to-end learning framework for quantum neural networks. CoRR"},{"key":"4542_CR25","doi-asserted-by":"crossref","unstructured":"Jiang W, Xiong J, Shi Y (2020) Can quantum computers learn like classical computers? a co-design framework for machine learning and quantum circuits. arXiv:2006.14815","DOI":"10.21203\/rs.3.rs-38495\/v1"},{"key":"4542_CR26","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.neunet.2020.07.003","volume":"130","author":"P Li","year":"2020","unstructured":"Li P, Wang B (2020) Quantum neural networks model based on swap test and phase estimation. Neural Netw 130:152\u2013164","journal-title":"Neural Netw"},{"key":"4542_CR27","unstructured":"Kerstin B, Dmytro B, Terry F, J OT, Robert S, Ramona W (2019) Efficient learning for deep quantum neural networks. arXiv:1902.10445"},{"issue":"7747","key":"4542_CR28","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1038\/s41586-019-0980-2","volume":"567","author":"V Havl\u00ed\u010dek","year":"2019","unstructured":"Havl\u00ed\u010dek V, C\u00f3rcoles AD, Temme K, Harrow AW, Kandala A, Chow JM, Gambetta JM (2019) Supervised learning with quantum-enhanced feature spaces. Nature 567(7747):209\u2013212","journal-title":"Nature"},{"issue":"1","key":"4542_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-018-07090-4","volume":"9","author":"JR McClean","year":"2018","unstructured":"McClean JR, Boixo S, Smelyanskiy VN, Babbush R, Neven H (2018) Barren plateaus in quantum neural network training landscapes. Nat Commun 9(1):1\u20136","journal-title":"Nat Commun"},{"key":"4542_CR30","doi-asserted-by":"publisher","first-page":"94310","DOI":"10.1109\/ACCESS.2019.2929084","volume":"7","author":"P-H Qiu","year":"2019","unstructured":"Qiu P-H, Chen X-G, Shi Y-W (2019) Detecting entanglement with deep quantum neural networks. IEEE Access 7:94310\u201394320","journal-title":"IEEE Access"},{"key":"4542_CR31","unstructured":"Kdd cup 1999 dataset. http:\/\/kdd.ics.uci.edu\/databases\/kddcup99\/kddcup99.html"},{"issue":"1","key":"4542_CR32","first-page":"157","volume":"6","author":"L Khalvati","year":"2018","unstructured":"Khalvati L, Keshtgary M, Rikhtegar N (2018) Intrusion detection based on a novel hybrid learning approach. Nat Commun 6(1):157\u2013162","journal-title":"Nat Commun"},{"key":"4542_CR33","doi-asserted-by":"publisher","first-page":"112845","DOI":"10.1016\/j.eswa.2019.112845","volume":"139","author":"J Liu","year":"2020","unstructured":"Liu J, Zhang W, Tang Z, Xie Y, Ma T, Zhang J, Zhang G, Niyoyita JP (2020) Adaptive intrusion detection via ga-gogmm-based pattern learning with fuzzy rough set-based attribute selection. Expert Syst Appl 139:112845","journal-title":"Expert Syst Appl"},{"key":"4542_CR34","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.jocs.2017.03.006","volume":"25","author":"S Aljawarneh","year":"2018","unstructured":"Aljawarneh S, Aldwairi M, Yassein MB (2018) Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model. J Comput Sci 25:152\u2013160","journal-title":"J Comput Sci"},{"key":"4542_CR35","first-page":"80","volume":"44","author":"S Mohammadi","year":"2019","unstructured":"Mohammadi S, Mirvaziri H, Ghazizadeh-Ahsaee M, Karimipour H (2019) Cyber intrusion detection by combined feature selection algorithm. J Inf Secur Appl 44:80\u201388","journal-title":"J Inf Secur Appl"},{"key":"4542_CR36","doi-asserted-by":"publisher","first-page":"113249","DOI":"10.1016\/j.eswa.2020.113249","volume":"148","author":"H Alazzam","year":"2020","unstructured":"Alazzam H, Sharieh A, Sabri KE (2020) A feature selection algorithm for intrusion detection system based on pigeon inspired optimizer. Expert Syst Appl 148:113249","journal-title":"Expert Syst Appl"},{"key":"4542_CR37","doi-asserted-by":"publisher","first-page":"1900070","DOI":"10.1002\/qute.201900070","volume":"2","author":"S Sim","year":"2019","unstructured":"Sim S, Johnson PD, Aspuru-Guzik A (2019) Expressibility and entangling capability of parameterized quantum circuits for hybrid quantum-classical algorithms. Adv Quantum Technol 2:1900070","journal-title":"Adv Quantum Technol"},{"key":"4542_CR38","doi-asserted-by":"publisher","first-page":"141007","DOI":"10.1109\/ACCESS.2020.3010470","volume":"8","author":"S Yen-Chi Chen","year":"2020","unstructured":"Yen-Chi Chen S, Huck Yang CH, Qi J, Chen PY, Ma X, Goan HS (2020) Variational quantum circuits for deep reinforcement learning. IEEE Access 8:141007\u2013141024","journal-title":"IEEE Access"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-022-04542-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-022-04542-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-022-04542-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,4]],"date-time":"2022-10-04T10:17:41Z","timestamp":1664878661000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-022-04542-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,11]]},"references-count":38,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["4542"],"URL":"https:\/\/doi.org\/10.1007\/s11227-022-04542-z","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,11]]},"assertion":[{"value":"13 April 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}