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No Bot Expects the DeepCAPTCHA! Introducing Immutable Adversarial Examples, With Applications to CAPTCHA Generation
2017
IEEE Transactions on Information Forensics and Security
Preserved Fulltext
Recent advances in Deep Learning (DL) allow for solving complex AI problems that used to be considered very hard. ...
ACKNOWLEDGEMENTS The authors thank Daniel Osadchy for his worthy contributions to the paper and the anonymous reviewers for their ideas and suggestions. ...
This research was supported by UK Engineering and Physical Sciences Research Council project EP/M013375/1 and by the Israeli Ministry of Science and Technology project 3-11858. ...
doi:10.1109/tifs.2017.2718479
fatcat:t2e5kcddcbaezb6bswdtqfeweq
A Survey of Adversarial CAPTCHAs on its History, Classification and Generation
[article]
2023
arXiv
pre-print
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The discovery of adversarial examples provides an ideal solution to the security and usability trade-off by integrating adversarial examples and CAPTCHAs to generate adversarial CAPTCHAs that can fool ...
Then we systematically review some commonly used methods to generate adversarial examples and methods that are successfully used to generate adversarial CAPTCHAs. ...
ACKNOWLEDGMENTS This work is supported by the National Natural Science Foundation of China (61976142) and Shenzhen Science and Technology Plan Project (JCYJ20210324093609025). ...
arXiv:2311.13233v1
fatcat:goqidd3b7zelvatwh3jigrci2u
Adversarial CAPTCHAs
[article]
2019
arXiv
pre-print
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We first identify the similarity and difference between adversarial CAPTCHA generation and existing hot adversarial example (image) generation research. ...
Following the principle of to set one's own spear against one's own shield, we study how to design adversarial CAPTCHAs in this paper. ...
Therefore, we believe aCAPTCHA has a great applicability. Actually, we have contacted with several Internet companies to introduce aCAPTCHA. ...
arXiv:1901.01107v1
fatcat:la4pc6q2t5cfzljvxogn53suge
Deep Learning in Information Security
[article]
2018
arXiv
pre-print
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Other advantages of DL methods are unrivaled scalability and efficiency, both regarding the number of examples that can be analyzed as well as with respect of dimensionality of the input data. ...
DL methods generally are capable of achieving high-performance and generalize well. However, information security is a domain with unique requirements and challenges. ...
No Bot
Expects the DeepCAPTCHA! Introducing Immutable Adversarial Examples, with Applications to CAPTCHA
Generation. ...
arXiv:1809.04332v1
fatcat:xfb7lgrkw5cirdl3qvmg3ssnbi
New Cognitive Deep-Learning CAPTCHA
2023
Preserved Fulltext
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CNN/DNN have recently been shown to be extremely vulnerable to adversarial examples, which can consistently deceive neural networks by introducing noise that humans are incapable of detecting. ...
suggest a promising direction for designing CAPTCHAs with the concept of the proposed CAPTCHA. ...
[27] , introduces immutable adversarial noise (IAN) deceiving deep-learning techniques. ...
doi:10.3390/s23042338
pmid:36850935
pmcid:PMC9965441
fatcat:2cfo3mdv3fgvjjpgzht4zv72s4