{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:24:10Z","timestamp":1783009450073,"version":"3.54.5"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T00:00:00Z","timestamp":1652486400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T00:00:00Z","timestamp":1652486400000},"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":["Cluster Comput"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s10586-022-03604-4","type":"journal-article","created":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T08:03:01Z","timestamp":1652515381000},"page":"3819-3828","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":126,"title":["An intelligent cyber security phishing detection system using deep learning techniques"],"prefix":"10.1007","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1298-6933","authenticated-orcid":false,"given":"Ala","family":"Mughaid","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shadi","family":"AlZu\u2019bi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adnan","family":"Hnaif","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salah","family":"Taamneh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asma","family":"Alnajjar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Esraa Abu","family":"Elsoud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,5,14]]},"reference":[{"issue":"3","key":"3604_CR1","first-page":"123","volume":"12","author":"H Al-Masalha","year":"2020","unstructured":"Al-Masalha, H., Hnaif, A.A., Kanan, T.: Cyber-crime effect on Jordanian society. Int. J. Adv. Soft Comput. Appl. 12(3), 123\u2013139 (2020)","journal-title":"Int. J. Adv. Soft Comput. Appl."},{"issue":"2","key":"3604_CR2","first-page":"22","volume":"12","author":"B Saini","year":"2020","unstructured":"Saini, B., Srivastava, S., Bajpai, A.: Deep CNN model for nanotoxicity classification using microscopic images. Int. J. Adv. Soft Comput. Appl. 12(2), 22 (2020)","journal-title":"Int. J. Adv. Soft Comput. Appl."},{"key":"3604_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10586-022-03594-3","volume":"2022","author":"S Al-Zubi","year":"2022","unstructured":"Al-Zubi, S., Aqel, D., Lafi, M.: An intelligent system for blood donation process optimization-smart techniques for minimizing blood wastages. Clust. Comput. 2022, 1\u201311 (2022). https:\/\/doi.org\/10.1007\/s10586-022-03594-3","journal-title":"Clust. Comput."},{"key":"3604_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10586-021-03397-y","volume":"2021","author":"D Aqel","year":"2021","unstructured":"Aqel, D., Al-Zubi, S., Mughaid, A., Jararweh, Y.: Extreme learning machine for plant diseases classification: a sustainable approach for smart agriculture. Clust. Comput. 2021, 1\u201314 (2021). https:\/\/doi.org\/10.1007\/s10586-021-03397-y","journal-title":"Clust. Comput."},{"key":"3604_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10586-022-03540-3","volume":"2022","author":"S Srivastava","year":"2022","unstructured":"Srivastava, S., Singh, A.K.: Fraud detection in the distributed graph database. Clust. Comput. 2022, 1\u201323 (2022). https:\/\/doi.org\/10.1007\/s10586-022-03540-3","journal-title":"Clust. Comput."},{"issue":"1","key":"3604_CR6","doi-asserted-by":"publisher","first-page":"1827","DOI":"10.1007\/s10586-018-2269-x","volume":"22","author":"D Kim","year":"2019","unstructured":"Kim, D., Kim, Y.-H., Shin, D., Shin, D.: Fast attack detection system using log analysis and attack tree generation. Clust. Comput. 22(1), 1827\u20131835 (2019)","journal-title":"Clust. Comput."},{"issue":"4","key":"3604_CR7","doi-asserted-by":"publisher","first-page":"3011","DOI":"10.1007\/s10586-021-03309-0","volume":"24","author":"H Aldabbas","year":"2021","unstructured":"Aldabbas, H., Amin, R.: A novel mechanism to handle address spoofing attacks in sdn based iot. Clust. Comput. 24(4), 3011\u20133026 (2021)","journal-title":"Clust. Comput."},{"key":"3604_CR8","doi-asserted-by":"crossref","unstructured":"Abusukhon, A., AlZu\u2019bi, S.: New direction of cryptography: a review on text-to-image encryption algorithms based on rgb color value. In: Proceedings of the 2020 Seventh International Conference on Software Defined Systems (SDS), pp. 235\u2013239. IEEE (2020)","DOI":"10.1109\/SDS49854.2020.9143891"},{"key":"3604_CR9","doi-asserted-by":"publisher","first-page":"47","DOI":"10.3991\/ijim.v13i05.9845","volume":"13","author":"I Obeidat","year":"2019","unstructured":"Obeidat, I., Mughaid, A., Alzoubi, S.: A secure encrypted protocol for clients\u2019 handshaking in the same network. Int. J. Interact. Mob. Technol. 13, 47\u201357 (2019)","journal-title":"Int. J. Interact. Mob. Technol."},{"issue":"4","key":"3604_CR10","doi-asserted-by":"publisher","first-page":"89","DOI":"10.3390\/fi11040089","volume":"11","author":"F Salahdine","year":"2019","unstructured":"Salahdine, F., Kaabouch, N.: Social engineering attacks: a survey. Future Internet 11(4), 89 (2019)","journal-title":"Future Internet"},{"issue":"4","key":"3604_CR11","doi-asserted-by":"publisher","first-page":"2091","DOI":"10.1109\/SURV.2013.032213.00009","volume":"15","author":"M Khonji","year":"2013","unstructured":"Khonji, M., Iraqi, Y., Jones, A.: Phishing detection: a literature survey. IEEE Commun. Surv. Tutor. 15(4), 2091\u20132121 (2013)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"3604_CR12","unstructured":"Whittaker, C., Ryner, B., Nazif, M.: Large-scale automatic classification of phishing pages. In: Proceedings of the Network and Distributed System Security Symposium (2010)"},{"issue":"1","key":"3604_CR13","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1145\/2063176.2063197","volume":"55","author":"J Hong","year":"2012","unstructured":"Hong, J.: The state of phishing attacks. Commun. ACM 55(1), 74\u201381 (2012)","journal-title":"Commun. ACM"},{"key":"3604_CR14","doi-asserted-by":"publisher","first-page":"106160","DOI":"10.1016\/j.childyouth.2021.106160","volume":"128","author":"M Maqableh","year":"2021","unstructured":"Maqableh, M., Alia, M.: Evaluation online learning of undergraduate students under lockdown amidst covid-19 pandemic: the online learning experience and students\u2019 satisfaction. Child Youth Serv. Rev. 128, 106160 (2021)","journal-title":"Child Youth Serv. Rev."},{"key":"3604_CR15","doi-asserted-by":"crossref","unstructured":"Zhao, W., Zhu, Y.: An email classification scheme based on decision-theoretic rough set theory and analysis of email security. In: Proceedings of the TENCON 2005-2005 IEEE Region 10 Conference, pp. 1\u20136. IEEE (2005)","DOI":"10.1109\/TENCON.2005.301121"},{"key":"3604_CR16","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/978-3-030-16837-7_6","volume-title":"Cybersecurity and Secure Information Systems","author":"R Vinayakumar","year":"2019","unstructured":"Vinayakumar, R., Soman, K., Poornachandran, P., Akarsh, S., Elhoseny, M.: Deep learning framework for cyber threat situational awareness based on email and url data analysis. In: Hassanien, A.E., Elhoseny, M. (eds.) Cybersecurity and Secure Information Systems, pp. 87\u2013124. Springer, New York (2019)"},{"key":"3604_CR17","doi-asserted-by":"crossref","unstructured":"AlZu\u2019bi, S., Al-Qatawneh, S., Alsmirat, M.: Transferable hmm trained matrices for accelerating statistical segmentation time. In: Proceedings of the 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS), pp. 172\u2013176. IEEE (2018)","DOI":"10.1109\/SNAMS.2018.8554487"},{"issue":"11","key":"3604_CR18","doi-asserted-by":"publisher","first-page":"16887","DOI":"10.1007\/s11042-020-09160-6","volume":"80","author":"S Al-Zubi","year":"2021","unstructured":"Al-Zubi, S., Hawashin, B., Mughaid, A., Baker, T.: Efficient 3d medical image segmentation algorithm over a secured multimedia network. Multimed. Tools Appl. 80(11), 16887\u201316905 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"3604_CR19","doi-asserted-by":"crossref","unstructured":"AlZu\u2019bi, S., Jararweh, Y.: Data fusion in autonomous vehicles research, literature tracing from imaginary idea to smart surrounding community. In: Proceedings of the 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC), pp. 306\u2013311. IEEE (2020)","DOI":"10.1109\/FMEC49853.2020.9144916"},{"key":"3604_CR20","doi-asserted-by":"crossref","unstructured":"AlKhatib, A.A., Sawalha, T., AlZu\u2019bi, S.: Load balancing techniques in software-defined cloud computing: an overview. In: Proceedings of the 2020 Seventh International Conference on Software Defined Systems (SDS), pp. 240\u2013244. IEEE (2020)","DOI":"10.1109\/SDS49854.2020.9143874"},{"key":"3604_CR21","doi-asserted-by":"crossref","unstructured":"Fette, I., Sadeh, N., Tomasic, A.: Learning to detect phishing emails. In: Proceedings of the 16th international conference on World Wide Web, pp. 649\u2013656 (2007)","DOI":"10.1145\/1242572.1242660"},{"key":"3604_CR22","doi-asserted-by":"crossref","unstructured":"Bhat, V.H., Malkani, V.R., Shenoy, P.D., Venugopal, K., Patnaik, L.: Classification of email using beaks: behavior and keyword stemming. In: Proceedings of the TENCON 2011-2011 IEEE Region 10 Conference, pp. 1139\u20131143. IEEE (2011)","DOI":"10.1109\/TENCON.2011.6129290"},{"key":"3604_CR23","doi-asserted-by":"crossref","unstructured":"Form, L.M., Chiew, K.L., Tiong, W.K.: Phishing email detection technique by using hybrid features. In: Proceedings of the 2015 9th International Conference on IT in Asia (CITA), pp. 1\u20135. IEEE (2015)","DOI":"10.1109\/CITA.2015.7349818"},{"key":"3604_CR24","doi-asserted-by":"crossref","first-page":"e3867","DOI":"10.1002\/ett.3867","volume":"33","author":"M Elbes","year":"2020","unstructured":"Elbes, M., Alrawashdeh, T., Almaita, E., AlZu\u2019bi, S., Jararweh, Y.: A platform for power management based on indoor localization in smart buildings using long short-term neural networks\u2019\u2019. Trans. Emerg. Telecommun. Technol. 33, e3867 (2020)","journal-title":"Trans. Emerg. Telecommun. Technol."},{"key":"3604_CR25","doi-asserted-by":"crossref","unstructured":"AlZu\u2019bi, S., Shehab, M.A., Al-Ayyoub, M., Benkhelifa, E., Jararweh, Y.: Parallel implementation of fcm-based volume segmentation of 3d images. In: Proceedings of the IEEE\/ACS 13th International Conference of Computer Systems and Applications (AICCSA), 2016, pp. 1\u20136. IEEE (2016)","DOI":"10.1109\/AICCSA.2016.7945811"},{"key":"3604_CR26","first-page":"2014","volume":"4","author":"SP Teli","year":"2014","unstructured":"Teli, S.P., Biradar, S.K.: Effective email classification for spam and non-spam. Int. J. Adv. Res. Comput. Softw. Eng. 4, 2014 (2014)","journal-title":"Int. J. Adv. Res. Comput. Softw. Eng."},{"key":"3604_CR27","doi-asserted-by":"crossref","unstructured":"Basnet, R., Mukkamala, S., Sung, A.H.: Detection of phishing attacks: a machine learning approach. In: Proceedings of the Soft computing applications in industry, pp. 373\u2013383. Springer (2008)","DOI":"10.1007\/978-3-540-77465-5_19"},{"key":"3604_CR28","first-page":"149","volume":"2017","author":"N Moradpoor","year":"2017","unstructured":"Moradpoor, N., Clavie, B., Buchanan, B.: Employing machine learning techniques for detection and classification of phishing emails. Comput. Conf. 2017, 149\u2013156 (2017)","journal-title":"Comput. Conf."},{"key":"3604_CR29","doi-asserted-by":"crossref","unstructured":"Smadi, S., Aslam, N., Zhang, L., Alasem, R., Hossain, M.A.: Detection of phishing emails using data mining algorithms. In: Proceedings of the 2015 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp. 1\u20138. IEEE (2015)","DOI":"10.1109\/SKIMA.2015.7399985"},{"key":"3604_CR30","doi-asserted-by":"crossref","unstructured":"Sheng, S., Holbrook, M., Kumaraguru, P., Cranor, L.F., Downs, J.: Who falls for phish? a demographic analysis of phishing susceptibility and effectiveness of interventions. In: Proceedings of the SIGCHI conference on human factors in computing systems, pp. 373\u2013382 (2010)","DOI":"10.1145\/1753326.1753383"},{"issue":"10","key":"3604_CR31","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1145\/1290958.1290968","volume":"50","author":"TN Jagatic","year":"2007","unstructured":"Jagatic, T.N., Johnson, N.A., Jakobsson, M., Menczer, F.: Social phishing. Commun. ACM 50(10), 94\u2013100 (2007)","journal-title":"Commun. ACM"},{"issue":"2","key":"3604_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1754393.1754396","volume":"10","author":"P Kumaraguru","year":"2010","unstructured":"Kumaraguru, P., Sheng, S., Acquisti, A., Cranor, L.F., Hong, J.: Teaching johnny not to fall for phish. ACM Trans. Internet Technol. 10(2), 1\u201331 (2010)","journal-title":"ACM Trans. Internet Technol."},{"key":"3604_CR33","doi-asserted-by":"crossref","unstructured":"Kumaraguru, P., Cranshaw, J., Acquisti, A., Cranor,L., Hong, J., Blair, M.A., Pham, T.: School of phish: a real-world evaluation of anti-phishing training. In: Proceedings of the 5th Symposium on Usable Privacy and Security, pp. 1\u201312 (2009)","DOI":"10.1145\/1572532.1572536"},{"key":"3604_CR34","doi-asserted-by":"crossref","unstructured":"Kumaraguru, P., Rhee, Y., Sheng, S., Hasan, S., Acquisti, A., Cranor, L.F., Hong, J.: Getting users to pay attention to anti-phishing education: evaluation of retention and transfer. In Proceedings of the Anti-phishing Working Groups 2nd Annual eCrime Researchers Summit, pp. 70\u201381 (2007)","DOI":"10.1145\/1299015.1299022"},{"key":"3604_CR35","first-page":"285","volume-title":"A Personality Based Model for Determining Susceptibility to Phishing Attacks","author":"JL Parrish Jr","year":"2009","unstructured":"Parrish, J.L., Jr., Bailey, J.L., Courtney, J.F.: A Personality Based Model for Determining Susceptibility to Phishing Attacks, pp. 285\u2013296. University of Arkansas, Little Rock (2009)"},{"issue":"6","key":"3604_CR36","doi-asserted-by":"publisher","first-page":"1044","DOI":"10.1542\/peds.2015-2151","volume":"136","author":"HK Kabali","year":"2015","unstructured":"Kabali, H.K., Irigoyen, M.M., Nunez-Davis, R., Budacki, J.G., Mohanty, S.H., Leister, K.P., Bonner, R.L.: Exposure and use of mobile media devices by young children. Pediatrics 136(6), 1044\u20131050 (2015)","journal-title":"Pediatrics"},{"issue":"11","key":"3604_CR37","doi-asserted-by":"publisher","first-page":"3423","DOI":"10.1007\/s10826-015-0144-4","volume":"24","author":"P Nikken","year":"2015","unstructured":"Nikken, P., Schols, M.: How and why parents guide the media use of young children. J. Child Fam. Stud. 24(11), 3423\u20133435 (2015)","journal-title":"J. Child Fam. Stud."},{"key":"3604_CR38","doi-asserted-by":"crossref","unstructured":"Nicholson, J., Javed, Y., Dixon, M., Coventry, L., Ajayi, O.D., Anderson, P.: Investigating teenagers ability to detect phishing messages. In: Proceedings of the IEEE European Symposium on Security and Privacy Workshops (EuroS &PW). IEEE 2020, pp. 140\u2013149 (2020)","DOI":"10.1109\/EuroSPW51379.2020.00027"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-022-03604-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-022-03604-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-022-03604-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T21:05:28Z","timestamp":1744146328000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-022-03604-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,14]]},"references-count":38,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["3604"],"URL":"https:\/\/doi.org\/10.1007\/s10586-022-03604-4","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,14]]},"assertion":[{"value":"17 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have not disclosed any competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"I have read and I understand the journal information and have agreed to all mentioned terms and conditions.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}