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Balduzzi, \u201cEXPOSURE: Finding malicious domains using passive DNS analysis,\u201d NDSS 2011, pp.1-17, San Diego, CA, USA, Feb. 2011. DOI: 10.1145\/ 2584679 10.1145\/2584679","DOI":"10.1145\/2584679"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] K.A. Messabi, M. Aldwairi, A.A. Yousif, A. Thoban, and F. Belqasmi, \u201cMalware detection using DNS records and domain name features,\u201d ICFNDS'18, pp.1-7, Amman, Jordan, June 2018. DOI: 10.1145\/3231053.3231082 10.1145\/3231053.3231082","DOI":"10.1145\/3231053.3231082"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] D. Chiba, T. Yagi, M. Akiyama, T. Shibahara, T. Yada, T. Mori, and S. Goto, \u201cDomainProfiler: Discovering domain names abused in future,\u201d Proc. 2016 46th Annu. IEEE\/IFIP Int. Conf. DSN, pp.491-502, Toulouse, France, June 2016. DOI: 10.1109\/DSN. 2016.51 10.1109\/DSN.2016.51","DOI":"10.1109\/DSN.2016.51"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] I. Khalil, T. Yu, and B. Guan, \u201cDiscovering malicious domains through passive DNS data graph analysis,\u201d ASIA CCS'16, pp.663-674, Xi'an, China, May 2016. DOI: 10.1145\/2897845. 2897877 10.1145\/2897845.2897877","DOI":"10.1145\/2897845"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] Y. Kazato, Y. Nakagawa, and Y. Nakatani, \u201cImproving maliciousness estimation of indicator of compromise using graph convolutional networks,\u201d 2020 IEEE 17th Annu. CCNC, pp.1-7, Las Vegas, NV, USA, Jan. 2020. DOI: 10.1109\/CCNC46108.2020.9045113 10.1109\/CCNC46108.2020.9045113","DOI":"10.1109\/CCNC46108.2020.9045113"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] Y. Zhauniarovich, I. Khalil, T. Yu, and M. Dacier, \u201cA survey on malicious domains detection through DNS data analysis,\u201d ACM Comput. Surv., vol.51, no.4, pp.1-36, 2018. DOI: 10.1145\/3191329 10.1145\/3191329","DOI":"10.1145\/3191329"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] Z. Liu, Y. Zeng, P. Zhang, J. Xue, J. Zhang, and J. Liu, \u201cAn imbalanced malicious domains detection method based on passive DNS traffic analysis,\u201d Secur. Commun. Netw., vol.2018, Article ID 6510381, 2018. DOI: 10.1155\/2018\/6510381 10.1155\/2018\/6510381","DOI":"10.1155\/2018\/6510381"},{"key":"8","unstructured":"[8] \u201cAlexa Top Sites,\u201d https:\/\/www.alexa.com\/topsites, Accessed June, 2020."},{"key":"9","unstructured":"[9] \u201cMalware Domain List,\u201d https:\/\/www.malwaredomainlist.com, Accessed June, 2020."},{"key":"10","unstructured":"[10] \u201cCompromised Domain List,\u201d https:\/\/zonefiles.io\/compromised-domain-list, Accessed June, 2020."},{"key":"11","unstructured":"[11] T. Holz, C. Gorecki, K. Rieck, and F.C. Freiling, \u201cMeasuring and detecting fast-flux service networks,\u201d Ndss, 2008."},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] S. Yadav, A.K.K Reddy, A.L.N. Reddy, and S. Ranjan, \u201cDetecting algorithmically generated malicious domain names,\u201d Proc. 10th ACM SIGCOMM Conference on Internet Measurement, pp.48-61. 2010. 10.1145\/1879141.1879148","DOI":"10.1145\/1879141.1879148"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] S. Yadav, A.K.K Reddy, A.L.N. Reddy, and S. Ranjan, \u201cDetecting algorithmically generated domain-flux attacks with DNS traffic analysis,\u201d IEEE\/ACM Trans. Netw., vol.20, no.5, pp.1663-1677, 2012. 10.1109\/tnet.2012.2184552","DOI":"10.1109\/TNET.2012.2184552"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] A. Kountouras, P. Kintis, C. Lever, Y. Chen, Y. Nadji, D. Dagon, M. Antonakakis, and R. 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