乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T16:41:42Z","timestamp":1726245702011},"reference-count":28,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,5,24]],"date-time":"2022-05-24T00:00:00Z","timestamp":1653350400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["ICT Express"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1016\/j.icte.2022.05.009","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T16:25:31Z","timestamp":1654014331000},"page":"168-176","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":14,"title":["SMSPROTECT: An automatic smishing detection mobile application"],"prefix":"10.1016","volume":"9","author":[{"given":"Oluwatobi Noah","family":"Akande","sequence":"first","affiliation":[]},{"given":"Oluwadara","family":"Gbenle","sequence":"additional","affiliation":[]},{"given":"Oluwakemi Christiana","family":"Abikoye","sequence":"additional","affiliation":[]},{"given":"Rasheed Gbenga","family":"Jimoh","sequence":"additional","affiliation":[]},{"given":"Hakeem Babalola","family":"Akande","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-7411-3639","authenticated-orcid":false,"given":"Abdullateef O.","family":"Balogun","sequence":"additional","affiliation":[]},{"given":"Anuoluwapo","family":"Fatokun","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.icte.2022.05.009_b1","unstructured":"Smartphone users in Nigeria, https:\/\/www.statista.com\/statistics\/467187\/forecast-of-smartphone-users-in-nigeria\/."},{"key":"10.1016\/j.icte.2022.05.009_b2","series-title":"GSMA intelligence","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b3","series-title":"The real value of SMS to businesses","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b4","series-title":"Tap into the marketing power of SMS","author":"Pemberton","year":"2016"},{"key":"10.1016\/j.icte.2022.05.009_b5","unstructured":"Verizon mobile security index 2020 report https:\/\/enterprise.verizon.com\/resources\/reports\/2020-msi-report.pdf."},{"key":"10.1016\/j.icte.2022.05.009_b6","series-title":"Feature based approach for detection of smishing messages in the mobile environment","first-page":"17","author":"Jain","year":"2019"},{"key":"10.1016\/j.icte.2022.05.009_b7","doi-asserted-by":"crossref","unstructured":"S. Mishra, D. Soni, A Content-Based Approach for detecting Smishing in Mobile Environment, in: International Conference on Sustainable Computing in Science, Technology & Management (SUSCOM-2019), 2019, pp. 986\u2013993.","DOI":"10.2139\/ssrn.3356256"},{"key":"10.1016\/j.icte.2022.05.009_b8","series-title":"SMS phishing cardless ATM=profit","year":"2020"},{"key":"10.1016\/j.icte.2022.05.009_b9","first-page":"1","article-title":"A novel technique to prevent SQL-injection and cross-site scripting attacks using knuth-morris-pratt string matching algorithm","volume":"14","author":"Christiana","year":"2020","journal-title":"EURASIP J. Inf. Secur."},{"key":"10.1016\/j.icte.2022.05.009_b10","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.future.2019.09.001","article-title":"Deep learning to filter SMS spam","volume":"102","author":"Kumar","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"issue":"156","key":"10.1016\/j.icte.2022.05.009_b11","first-page":"1","article-title":"A hybrid CNN-LSTM model for SMS spam detection in arabic and english messages","volume":"12","author":"Ghourabi","year":"2020","journal-title":"Future Internet"},{"key":"10.1016\/j.icte.2022.05.009_b12","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1016\/j.future.2020.03.021","article-title":"Smishing detector: A security model to detect smishing through SMS content analysis and URL behavior analysis","volume":"108","author":"Mishra","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"key":"10.1016\/j.icte.2022.05.009_b13","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s11277-019-06734-y","article-title":"Predicting spam messages using back propagation neural network","volume":"110","author":"Jain","year":"2020","journal-title":"Wirel. Pers. Commun."},{"issue":"1","key":"10.1016\/j.icte.2022.05.009_b14","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.icte.2020.08.001","article-title":"Securing IoT device communication against network flow attacks with recursive internetworking architecture (RINA)","volume":"7","author":"Bhushana\u00a0Samyuel","year":"2021","journal-title":"ICT Express","ISSN":"http:\/\/id.crossref.org\/issn\/2405-9595","issn-type":"print"},{"issue":"2","key":"10.1016\/j.icte.2022.05.009_b15","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.icte.2018.04.003","article-title":"Intelligent intrusion detection systems using artificial neural networks","volume":"4","author":"Shenfield","year":"2018","journal-title":"ICT Express","ISSN":"http:\/\/id.crossref.org\/issn\/2405-9595","issn-type":"print"},{"issue":"3","key":"10.1016\/j.icte.2022.05.009_b16","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.icte.2018.11.003","article-title":"M-pattern: A novel scheme for improving the security of android pattern unlock against smudge attacks","volume":"5","author":"Zheng","year":"2019","journal-title":"ICT Express","ISSN":"http:\/\/id.crossref.org\/issn\/2405-9595","issn-type":"print"},{"issue":"4","key":"10.1016\/j.icte.2022.05.009_b17","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.icte.2020.11.001","article-title":"Ransomware detection using random forest technique","volume":"6","author":"Khammas","year":"2020","journal-title":"ICT Express"},{"key":"10.1016\/j.icte.2022.05.009_b18","series-title":"Improving the Phishing Website Detection using Empirical Analysis of Function Tree and Its Variants","author":"Balogun","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b19","series-title":"Advances in Cyber Security, Chapter: 41","article-title":"Ensemble-based logistic model trees for website phishing detection","author":"Adeyemo","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b20","series-title":"Freeling english language dictionary","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b21","series-title":"Internet & text slang dictionary","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b22","series-title":"The malwareurl team","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b23","series-title":"Phishing domain database","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b24","series-title":"Fake sites database","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b25","doi-asserted-by":"crossref","unstructured":"T.A. Almeida, J.M. G\u00c33mez\u00a0Hidalgo, A. Yamakami, Contributions to the Study of SMS Spam Filtering: New Collection and Results, in: Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG\u201911), Mountain View, CA, USA, 2011.","DOI":"10.1145\/2034691.2034742"},{"key":"10.1016\/j.icte.2022.05.009_b26","series-title":"Nigerian scam phone numbers","year":"2021"},{"key":"10.1016\/j.icte.2022.05.009_b27","unstructured":"The number of mobile phone users in the world, https:\/\/datareportal. com\/global-digital-overview#:\u00a0:text=There%20are%205.22%20billion %20unique, of%201.8%20percent%20per%20year."},{"key":"10.1016\/j.icte.2022.05.009_b28","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s11235-016-0269-9","article-title":"S-detector: An enhanced security model for detecting smishing attack for mobile computing","volume":"66","author":"Woong","year":"2017","journal-title":"Telecommun. Syst."}],"container-title":["ICT Express"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405959522000868?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405959522000868?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,4,30]],"date-time":"2023-04-30T07:48:19Z","timestamp":1682840899000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405959522000868"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4]]},"references-count":28,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["S2405959522000868"],"URL":"https:\/\/doi.org\/10.1016\/j.icte.2022.05.009","relation":{},"ISSN":["2405-9595"],"issn-type":[{"value":"2405-9595","type":"print"}],"subject":[],"published":{"date-parts":[[2023,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"SMSPROTECT: An automatic smishing detection mobile application","name":"articletitle","label":"Article Title"},{"value":"ICT Express","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.icte.2022.05.009","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences.","name":"copyright","label":"Copyright"}]}}