A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
Every year, phishing results in losses of billions of dollars and is a major threat to the Internet economy. Phishing attacks are now most often carried out by email. To better comprehend the existing research trend of phishing email detection, several review studies have been performed. However, it...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , , |
| منشور في: |
2022
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/3028 https://doi.org/10.1109/ACCESS.2022.3183083. |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| _version_ | 1862980618634133504 |
|---|---|
| author | SALLOUM, SAID |
| author2 | GABER, TAREK VADERA, SUNIL SHAALAN, KHALED |
| author2_role | author author author |
| author_facet | SALLOUM, SAID GABER, TAREK VADERA, SUNIL SHAALAN, KHALED |
| author_role | author |
| dc.creator.none.fl_str_mv | SALLOUM, SAID GABER, TAREK VADERA, SUNIL SHAALAN, KHALED |
| dc.date.none.fl_str_mv | 2022 2025-05-14T10:46:40Z 2025-05-14T10:46:40Z |
| dc.identifier.none.fl_str_mv | Salloum, S. et al. (2022) “A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques,” IEEE Access, 10. 2169-3536 https://bspace.buid.ac.ae/handle/1234/3028 https://doi.org/10.1109/ACCESS.2022.3183083. |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | IEEE Accessv10 (2022): 65703-65727 |
| dc.subject.none.fl_str_mv | Phishing email detection,systematic literature review, natural language processing, machine learning |
| dc.title.none.fl_str_mv | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| dc.type.none.fl_str_mv | Article |
| description | Every year, phishing results in losses of billions of dollars and is a major threat to the Internet economy. Phishing attacks are now most often carried out by email. To better comprehend the existing research trend of phishing email detection, several review studies have been performed. However, it is important to assess this issue from different perspectives. None of the surveys have ever comprehensively studied the use of Natural Language Processing (NLP) techniques for detection of phishing except one that shed light on the use of NLP techniques for classification and training purposes, while exploring a few alternatives. To bridge the gap, this study aims to systematically review and synthesise research on the use of NLP for detecting phishing emails. Based on specific predefined criteria, a total of 100 research articles published between 2006 and 2022 were identified and analysed. We study the key research areas in phishing email detection using NLP, machine learning algorithms used in phishing detection email, text features in phishing emails, datasets and resources that have been used in phishing emails, and the evaluation criteria. The findings include that the main research area in phishing detection studies is feature extraction and selection, followed by methods for classifying and optimizing the detection of phishing emails. Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. The most frequently used NLP techniques are found to be TF-IDF and word embeddings. Furthermore, the most commonly used datasets for benchmarking phishing email detection methods is the Nazario phishing corpus. Also, Python is the most commonly used one for phishing email detection. It is expected that the findings of this paper can be helpful for the scientific community, especially in the field of NLP application in cybersecurity problems. This survey also is unique in the sense that it relates works to their openly available tools and resources. The analysis of the presented works revealed that not much work had been performed on Arabic language phishing emails using NLP techniques. Therefore, many open issues are associated with Arabic phishing email detection. |
| id | budr_0900c33c53a41ddf0cf57e1b90cbfb96 |
| identifier_str_mv | Salloum, S. et al. (2022) “A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques,” IEEE Access, 10. 2169-3536 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/3028 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing TechniquesSALLOUM, SAIDGABER, TAREKVADERA, SUNILSHAALAN, KHALEDPhishing email detection,systematic literature review, natural language processing, machine learningEvery year, phishing results in losses of billions of dollars and is a major threat to the Internet economy. Phishing attacks are now most often carried out by email. To better comprehend the existing research trend of phishing email detection, several review studies have been performed. However, it is important to assess this issue from different perspectives. None of the surveys have ever comprehensively studied the use of Natural Language Processing (NLP) techniques for detection of phishing except one that shed light on the use of NLP techniques for classification and training purposes, while exploring a few alternatives. To bridge the gap, this study aims to systematically review and synthesise research on the use of NLP for detecting phishing emails. Based on specific predefined criteria, a total of 100 research articles published between 2006 and 2022 were identified and analysed. We study the key research areas in phishing email detection using NLP, machine learning algorithms used in phishing detection email, text features in phishing emails, datasets and resources that have been used in phishing emails, and the evaluation criteria. The findings include that the main research area in phishing detection studies is feature extraction and selection, followed by methods for classifying and optimizing the detection of phishing emails. Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. The most frequently used NLP techniques are found to be TF-IDF and word embeddings. Furthermore, the most commonly used datasets for benchmarking phishing email detection methods is the Nazario phishing corpus. Also, Python is the most commonly used one for phishing email detection. It is expected that the findings of this paper can be helpful for the scientific community, especially in the field of NLP application in cybersecurity problems. This survey also is unique in the sense that it relates works to their openly available tools and resources. The analysis of the presented works revealed that not much work had been performed on Arabic language phishing emails using NLP techniques. Therefore, many open issues are associated with Arabic phishing email detection.IEEE2025-05-14T10:46:40Z2025-05-14T10:46:40Z2022ArticleSalloum, S. et al. (2022) “A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques,” IEEE Access, 10.2169-3536https://bspace.buid.ac.ae/handle/1234/3028https://doi.org/10.1109/ACCESS.2022.3183083.enIEEE Accessv10 (2022): 65703-65727oai:bspace.buid.ac.ae:1234/30282025-05-14T10:49:04Z |
| spellingShingle | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques SALLOUM, SAID Phishing email detection,systematic literature review, natural language processing, machine learning |
| title | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| title_full | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| title_fullStr | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| title_full_unstemmed | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| title_short | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| title_sort | A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques |
| topic | Phishing email detection,systematic literature review, natural language processing, machine learning |
| url | https://bspace.buid.ac.ae/handle/1234/3028 https://doi.org/10.1109/ACCESS.2022.3183083. |