{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:28:17Z","timestamp":1791394097757,"version":"4.3.3"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"21","license":[{"start":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T00:00:00Z","timestamp":1589155200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T00:00:00Z","timestamp":1589155200000},"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":["Soft Comput"],"published-print":{"date-parts":[[2020,11]]},"DOI":"10.1007\/s00500-020-04963-z","type":"journal-article","created":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T08:03:04Z","timestamp":1589184184000},"page":"16605-16616","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["DeepBot: a time-based botnet detection with deep learning"],"prefix":"10.1007","volume":"24","author":[{"given":"Wan-Chen","family":"Shi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hung-Min","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,5,11]]},"reference":[{"key":"4963_CR1","unstructured":"Bai S, Kolter JZ, Koltun V (2018) An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. CoRR, vol abs\/1803.01271 [Online]. arXiv:1803.01271"},{"key":"4963_CR2","unstructured":"Behind the numbers: growth in the Internet of Things (2015). https:\/\/cdn.ihs.com\/www\/pdf\/enabling-IOT.pdf"},{"key":"4963_CR3","unstructured":"Binkley JR, Singh S (2006) An algorithm for anomaly-based botnet detection. In: Proceedings of the 2nd conference on steps to reducing unwanted traffic on the internet. USENIX Association [Online]. http:\/\/dl.acm.org\/citation.cfm?id=1251296.1251303"},{"key":"4963_CR4","unstructured":"Botnet topology. https:\/\/www.researchgate.net\/figure\/Typical-Client-Server-Botnet-Command-and-Control-Topology_fig1_266209917"},{"key":"4963_CR5","doi-asserted-by":"crossref","unstructured":"Choi H, Lee H, Lee H, Kim H (Oct 2007) Botnet detection by monitoring group activities in DNS traffic. In: 7th IEEE international conference on computer and information technology","DOI":"10.1109\/CIT.2007.90"},{"key":"4963_CR6","unstructured":"Dynamic generation algorithms. https:\/\/en.wikipedia.org\/wiki\/Domain_generation_algorithm"},{"key":"4963_CR7","doi-asserted-by":"crossref","unstructured":"Feily M, Shahrestani A, Ramadass S (2009) A survey of botnet and botnet detection. In: Third international conference on emerging security information, systems and technologies","DOI":"10.1109\/SECURWARE.2009.48"},{"key":"4963_CR8","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.cose.2014.05.011","volume":"45","author":"S Garc\u00eda","year":"2014","unstructured":"Garc\u00eda S, Grill M, Stiborek J, Zunino A (2014) An empirical comparison of botnet detection methods. Comput Secur 45:100\u2013123. https:\/\/doi.org\/10.1016\/j.cose.2014.05.011","journal-title":"Comput Secur"},{"key":"4963_CR9","unstructured":"Gu G, Perdisci R, Zhang J, Lee W (2008) Botminer: clustering analysis of network traffic for protocol- and structure-independent botnet detection. In: Proceedings of the 17th conference on security symposium, ser. SS\u201908. USENIX Association [Online]. http:\/\/dl.acm.org\/citation.cfm?id=1496711.1496721"},{"key":"4963_CR10","doi-asserted-by":"publisher","DOI":"10.1142\/S0218488598000094","author":"S Hochreiter","year":"1998","unstructured":"Hochreiter S (1998) The vanishing gradient problem during learning recurrent neural nets and problem solutions. Int J Uncertain Fuzziness Knowl-Based Syst. https:\/\/doi.org\/10.1142\/S0218488598000094","journal-title":"Int J Uncertain Fuzziness Knowl-Based Syst"},{"key":"4963_CR11","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput. https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Comput"},{"key":"4963_CR12","first-page":"137","volume-title":"BoTShark: a deep learning approach for botnet traffic detection","author":"S Homayoun","year":"2018","unstructured":"Homayoun S, Ahmadzadeh M, Hashemi S, Dehghantanha A, Khayami R (2018) BoTShark: a deep learning approach for botnet traffic detection. Springer, Cham, pp 137\u2013153"},{"key":"4963_CR13","volume-title":"Recurrent neural networks: design and applications","author":"LC Jain","year":"1999","unstructured":"Jain LC, Medsker LR (1999) Recurrent neural networks: design and applications, 1st edn. CRC Press Inc, Boca Raton","edition":"1"},{"key":"4963_CR14","unstructured":"Karasaridis A, Rexroad B, Hoeflin D (2007) Wide-scale botnet detection and characterization. In: Proceedings of the first conference on first workshop on hot topics in understanding botnets. USENIX Association [Online]. http:\/\/dl.acm.org\/citation.cfm?id=1323128.1323135"},{"key":"4963_CR15","doi-asserted-by":"crossref","unstructured":"Mikolov T, Karafiat M, Burget L, Cernocky J, Khudanpur S (2010) Recurrent neural network based language model. In: International speech communication association, pp 1045\u20131048","DOI":"10.1109\/ICASSP.2011.5947611"},{"key":"4963_CR16","unstructured":"Pysahrk. https:\/\/kiminewt.github.io\/pyshark\/"},{"key":"4963_CR17","doi-asserted-by":"crossref","unstructured":"Siboni S, Cohen A (2014) Botnet identification via universal anomaly detection. In: 2014 IEEE international workshop on information forensics and security (WIFS), pp 101\u2013106","DOI":"10.1109\/WIFS.2014.7084311"},{"key":"4963_CR18","unstructured":"Smominru (2018). https:\/\/www.cyber.nj.gov\/threat-profiles\/botnet-variants\/smominru"},{"key":"4963_CR19","unstructured":"Snort (2016). https:\/\/www.snort.org\/"},{"key":"4963_CR20","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 15(1):1929\u20131958. http:\/\/dl.acm.org\/citation.cfm?id=2627435.2670313"},{"key":"4963_CR21","unstructured":"Sutskever I, Martens J, Hinton G (2011)Generating text with recurrent neural networks. In: Proceedings of the 28th international conference on machine learning (ICML-11), pp 1017\u20131024"},{"key":"4963_CR22","unstructured":"Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. In: Advances in neural information processing systems 27(NIPS 2014), pp 3104\u20131112"},{"key":"4963_CR23","doi-asserted-by":"publisher","first-page":"2401","DOI":"10.1016\/j.neucom.2017.11.018","volume":"275","author":"D Tran","year":"2018","unstructured":"Tran D, Mac H, Tong VT, Tran HA, Nguyen LG (2018) A LSTM based framework for handling multiclass imbalance in dga botnet detection. Neurocomputing 275:2401\u20132413","journal-title":"Neurocomputing"},{"key":"4963_CR24","unstructured":"Tshark. https:\/\/www.wireshark.org\/docs\/man-pages\/tshark.html"},{"key":"4963_CR25","doi-asserted-by":"crossref","unstructured":"Villamarin-Salomon R, Brustoloni JC (2008) Identifying botnets using anomaly detection techniques applied to DNS traffic. In: 2008 5th IEEE consumer communications and networking conference, pp 476\u2013481","DOI":"10.1109\/ccnc08.2007.112"},{"key":"4963_CR26","doi-asserted-by":"crossref","unstructured":"Vinayakumar R, Soman K, Poornachandran P, Alazab M, Jolfaei A (2019) DBD: deep learning dga-based botnet detection. In: Deep learning applications for cyber security. Springer, Cham, Switzerland, 2019, pp 127\u2013149","DOI":"10.1007\/978-3-030-13057-2_6"},{"key":"4963_CR27","unstructured":"Wang W, Zhu M, Zeng X, Ye X, Shengand Y (2017) Malware traffic classification using convolutional neural network for representation learning. In: 2017 International conference on information networking"},{"key":"4963_CR28","unstructured":"Wikipedia: Mirai. https:\/\/en.wikipedia.org\/wiki\/Mirai_(malware)"},{"key":"4963_CR29","unstructured":"Wikipedia: Softmax function. https:\/\/en.wikipedia.org\/wiki\/Softmax_function"},{"key":"4963_CR30","unstructured":"Xu K, Ba J, Kiros R, Cho K, Courville A, Salakhutdinov R, Zemel R, Bengio Y (2015) Show, attend and tell: neural image caption generation with visual attention. In: Proceedings of the 32nd international conference on machine learning, vol 37"},{"key":"4963_CR31","doi-asserted-by":"crossref","unstructured":"Ziv J, Lempel A (978) Compression of individual sequences via variable-rate coding. In: 1978 IEEE transactions on information theory, pp 530\u2013536","DOI":"10.1109\/TIT.1978.1055934"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-020-04963-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00500-020-04963-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-020-04963-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:49:46Z","timestamp":1620694186000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00500-020-04963-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,11]]},"references-count":31,"journal-issue":{"issue":"21","published-print":{"date-parts":[[2020,11]]}},"alternative-id":["4963"],"URL":"https:\/\/doi.org\/10.1007\/s00500-020-04963-z","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,11]]},"assertion":[{"value":"11 May 2020","order":1,"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"}}]}}