{"title":"PassGAN-Based Honeywords System","authors":"M. Fauzi, Bian Yang, Edlira Martiri","doi":"10.1109/CSCI49370.2019.00037","DOIUrl":null,"url":null,"abstract":"In this work, we simulate a game between the attacker and the defender to evaluate their possible strategies in a honeyword system. For the attacker's guessing strategy, the Top-PW attack is used and a novel PassGAN-based attack is proposed. Meanwhile, for the defender's honeywords generation strategy, a PassGAN-based method is implemented and a novel two-stages PassGAN-based generation strategy is proposed. The experiment results show that the Top-PW attack is generally more successful than the PassGAN-based attack for the attacker while the proposed two-stages PassGAN-based approach is proven to be the most suitable honeyword generation strategy for the defender. The proposed two-stages PassGAN-based method for the defender's generation strategy can decrease the attacker's success rate to 9% and surpass some previous honeywords generation methods.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI49370.2019.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this work, we simulate a game between the attacker and the defender to evaluate their possible strategies in a honeyword system. For the attacker's guessing strategy, the Top-PW attack is used and a novel PassGAN-based attack is proposed. Meanwhile, for the defender's honeywords generation strategy, a PassGAN-based method is implemented and a novel two-stages PassGAN-based generation strategy is proposed. The experiment results show that the Top-PW attack is generally more successful than the PassGAN-based attack for the attacker while the proposed two-stages PassGAN-based approach is proven to be the most suitable honeyword generation strategy for the defender. The proposed two-stages PassGAN-based method for the defender's generation strategy can decrease the attacker's success rate to 9% and surpass some previous honeywords generation methods.