{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T06:47:18Z","timestamp":1783147638111,"version":"3.54.6"},"reference-count":35,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,5,6]],"date-time":"2023-05-06T00:00:00Z","timestamp":1683331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>Spammers have created a new kind of electronic mail (e-mail) called image-based spam to bypass text-based spam filters. Unfortunately, these images contain harmful links that can infect the user\u2019s computer system and take a long time to be deleted, which can hamper users\u2019 productivity and security. In this paper, a hybrid deep neural network architecture is suggested to address this problem. It is based on the convolution neural network (CNN), which has been enhanced with the convolutional block attention module (CBAM). Initially, CNN enhanced with CBAM is used to extract the most crucial information from each image-based e-mail. Then, the generated feature vectors are fed to the support vector machine (SVM) model to classify them as either spam or ham. Four datasets\u2014including Image Spam Hunter (ISH), Annadatha, Chavda Approach 1, and Chavda Approach 2\u2014are used in the experiments. The obtained results demonstrated that in terms of accuracy, our model exceeds the existing state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/bdcc7020087","type":"journal-article","created":{"date-parts":[[2023,5,8]],"date-time":"2023-05-08T04:04:48Z","timestamp":1683518688000},"page":"87","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Attention Mechanism and Support Vector Machine for Image-Based E-Mail Spam Filtering"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4225-0334","authenticated-orcid":false,"given":"Ghizlane","family":"Hnini","sequence":"first","affiliation":[{"name":"Laboratory of Computer Science, Signals, Automation and Cognitivism (LISAC), University Sidi Mohamed Ben Abdellah, Fez 30000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jamal","family":"Riffi","sequence":"additional","affiliation":[{"name":"Laboratory of Computer Science, Signals, Automation and Cognitivism (LISAC), University Sidi Mohamed Ben Abdellah, Fez 30000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed Adnane","family":"Mahraz","sequence":"additional","affiliation":[{"name":"Laboratory of Computer Science, Signals, Automation and Cognitivism (LISAC), University Sidi Mohamed Ben Abdellah, Fez 30000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Yahyaouy","sequence":"additional","affiliation":[{"name":"Laboratory of Computer Science, Signals, Automation and Cognitivism (LISAC), University Sidi Mohamed Ben Abdellah, Fez 30000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamid","family":"Tairi","sequence":"additional","affiliation":[{"name":"Laboratory of Computer Science, Signals, Automation and Cognitivism (LISAC), University Sidi Mohamed Ben Abdellah, Fez 30000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,6]]},"reference":[{"key":"ref_1","unstructured":"Kim, B., Abuadbba, S., and Kim, H. 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