Name
Abstract | ||
|---|---|---|
Learning useful representations from unstructured data is one of the core challenges, as well as a driving force, of modern data-driven approaches. Deep learning has demonstrated the broad advantages of learning and harnessing such representations.In this paper, we introduce a deep generative model representation learning approach for password guessing. We show that an abstract password representa... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SP40001.2021.00016 | 2021 IEEE Symposium on Security and Privacy (SP) |
Keywords | DocType | Volume |
Password-Security,Deep-learning | Conference | 2019 |
ISBN | Citations | PageRank |
978-1-7281-8934-5 | 2 | 0.39 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dario Pasquini | 1 | 2 | 1.40 |
| Gangwal Ankit | 2 | 2 | 0.39 |
| Giuseppe Ateniese | 3 | 4380 | 254.66 |
| Massimo Bernaschi | 4 | 504 | 64.27 |
| Mauro Conti | 5 | 2430 | 203.80 |