Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet
The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of gen...
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| Format: | Article |
| Language: | English |
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College of Education for Pure Sciences
2023-12-01
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| Series: | Wasit Journal for Pure Sciences |
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| Online Access: | https://wjps.uowasit.edu.iq/index.php/wjps/article/view/269 |
| _version_ | 1797288420312088576 |
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| author | Maher A.Ahmed |
| author_facet | Maher A.Ahmed |
| author_sort | Maher A.Ahmed |
| collection | DOAJ |
| description |
The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of generating honeywords involves data sources from WordNet, which contributes to the improvement of authenticity and diversity in the honeywords. The method encompasses a series of consecutive stages, which include the tokenization of passwords, the formation of alphabet tokens using the Meerkat Clan Algorithm (MCA), the handling of digit tokens, the creation of unique character tokens, and the consolidation of honeywords. The optimization of the performance of the Meerkat Clan Algorithm (MCA) involves the careful selection of parameters. The experimental findings have exhibited noteworthy levels of precision and optimum efficacy, particularly in tasks such as proposing words with similar meanings, forecasting numerical values, and producing distinctive symbols. The attainment of this achievement is facilitated by a confluence of factors, encompassing the caliber of data, the judicious use of algorithms or models, and the ongoing process of iterative improvement to consistently enhance outcomes. In order to achieve the appropriate levels of accuracy and functionality, it is crucial to engage in the process of conducting experiments, thoroughly testing the system, and making necessary improvements. The empirical findings provide confirmation of the effectiveness of the MCA in producing a varied and protected collection of honeywords. This is especially evident in the case of alphabet tokens, which are distinguished by their autonomous creation and strong security characteristics. The analysis of correction rates, specifically in relation to the password "Lion1999*," demonstrates the aforementioned results. This study reveals an average accuracy of honeyword production up to 0.729847632111541. In the same manner, the accuracy of the password "house2000" is determined to be 0.761325846711256. Additionally, when considering a sample of 100 passwords, the mean accuracy of honeyword creation is calculated to be 0.7073897168887518. The findings collectively highlight the effectiveness of the MCA in generating honeywords that possess improved security characteristics.
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| first_indexed | 2024-03-07T18:49:13Z |
| format | Article |
| id | doaj.art-334636139f0b47bf86bbc48eb91a3321 |
| institution | Directory Open Access Journal |
| issn | 2790-5233 2790-5241 |
| language | English |
| last_indexed | 2024-03-07T18:49:13Z |
| publishDate | 2023-12-01 |
| publisher | College of Education for Pure Sciences |
| record_format | Article |
| series | Wasit Journal for Pure Sciences |
| spelling | doaj.art-334636139f0b47bf86bbc48eb91a33212024-03-02T02:02:22ZengCollege of Education for Pure SciencesWasit Journal for Pure Sciences2790-52332790-52412023-12-012410.31185/wjps.269Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNetMaher A.Ahmed0Research Iraqi Commission for Computer, Informatics Institute for Post Graduate Studies, Baghdad, IRAQ The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of generating honeywords involves data sources from WordNet, which contributes to the improvement of authenticity and diversity in the honeywords. The method encompasses a series of consecutive stages, which include the tokenization of passwords, the formation of alphabet tokens using the Meerkat Clan Algorithm (MCA), the handling of digit tokens, the creation of unique character tokens, and the consolidation of honeywords. The optimization of the performance of the Meerkat Clan Algorithm (MCA) involves the careful selection of parameters. The experimental findings have exhibited noteworthy levels of precision and optimum efficacy, particularly in tasks such as proposing words with similar meanings, forecasting numerical values, and producing distinctive symbols. The attainment of this achievement is facilitated by a confluence of factors, encompassing the caliber of data, the judicious use of algorithms or models, and the ongoing process of iterative improvement to consistently enhance outcomes. In order to achieve the appropriate levels of accuracy and functionality, it is crucial to engage in the process of conducting experiments, thoroughly testing the system, and making necessary improvements. The empirical findings provide confirmation of the effectiveness of the MCA in producing a varied and protected collection of honeywords. This is especially evident in the case of alphabet tokens, which are distinguished by their autonomous creation and strong security characteristics. The analysis of correction rates, specifically in relation to the password "Lion1999*," demonstrates the aforementioned results. This study reveals an average accuracy of honeyword production up to 0.729847632111541. In the same manner, the accuracy of the password "house2000" is determined to be 0.761325846711256. Additionally, when considering a sample of 100 passwords, the mean accuracy of honeyword creation is calculated to be 0.7073897168887518. The findings collectively highlight the effectiveness of the MCA in generating honeywords that possess improved security characteristics. https://wjps.uowasit.edu.iq/index.php/wjps/article/view/269Honeywords system, Meerkat clan algorithm, Password security, and WordNet. |
| spellingShingle | Maher A.Ahmed Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet Wasit Journal for Pure Sciences Honeywords system, Meerkat clan algorithm, Password security, and WordNet. |
| title | Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet |
| title_full | Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet |
| title_fullStr | Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet |
| title_full_unstemmed | Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet |
| title_short | Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet |
| title_sort | honeywords generation technique based on meerkat clan algorithm and wordnet |
| topic | Honeywords system, Meerkat clan algorithm, Password security, and WordNet. |
| url | https://wjps.uowasit.edu.iq/index.php/wjps/article/view/269 |
| work_keys_str_mv | AT maheraahmed honeywordsgenerationtechniquebasedonmeerkatclanalgorithmandwordnet |