Intersection Attacks on Discrete Epochs
Anonymous messaging systems with churn in the set of online users are vulnerable to intersection attacks. Researchers have evaluated the success of the state of the art intersection attack using a model of user messaging simulated from a generated social graph. This thesis compares the success of th...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/151547 |
| _version_ | 1826213448089862144 |
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| author | Lin, Andrea |
| author2 | Devadas, Srinivas |
| author_facet | Devadas, Srinivas Lin, Andrea |
| author_sort | Lin, Andrea |
| collection | MIT |
| description | Anonymous messaging systems with churn in the set of online users are vulnerable to intersection attacks. Researchers have evaluated the success of the state of the art intersection attack using a model of user messaging simulated from a generated social graph. This thesis compares the success of the state of the art intersection attack using a model simulated from a generated social graph versus models simulated from real social graphs, such as those of Twitter and Google+. We find that users lose anonymity at a slower rate if the model uses a real social graph rather than a generated social graph. |
| first_indexed | 2024-09-23T15:49:22Z |
| format | Thesis |
| id | mit-1721.1/151547 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:49:22Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1515472023-08-01T03:09:12Z Intersection Attacks on Discrete Epochs Lin, Andrea Devadas, Srinivas Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Anonymous messaging systems with churn in the set of online users are vulnerable to intersection attacks. Researchers have evaluated the success of the state of the art intersection attack using a model of user messaging simulated from a generated social graph. This thesis compares the success of the state of the art intersection attack using a model simulated from a generated social graph versus models simulated from real social graphs, such as those of Twitter and Google+. We find that users lose anonymity at a slower rate if the model uses a real social graph rather than a generated social graph. M.Eng. 2023-07-31T19:47:42Z 2023-07-31T19:47:42Z 2023-06 2023-06-06T16:35:54.500Z Thesis https://hdl.handle.net/1721.1/151547 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Lin, Andrea Intersection Attacks on Discrete Epochs |
| title | Intersection Attacks on Discrete Epochs |
| title_full | Intersection Attacks on Discrete Epochs |
| title_fullStr | Intersection Attacks on Discrete Epochs |
| title_full_unstemmed | Intersection Attacks on Discrete Epochs |
| title_short | Intersection Attacks on Discrete Epochs |
| title_sort | intersection attacks on discrete epochs |
| url | https://hdl.handle.net/1721.1/151547 |
| work_keys_str_mv | AT linandrea intersectionattacksondiscreteepochs |