Privacy protection method for ADS-B air traffic control data based on convolutional neural network and symmetric encryption
Changsheng Ma, Ruchun Jia, Jing Lou, Mingqian Wang · 2025
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Description
Changsheng Ma and co-authors present a privacy shield for aircraft tracking data in a 2025 paper. Planes broadcast their position, speed, and height in the open, which aids safety but lets anyone intercept private details. The team aimed to spot the sensitive parts fast and scramble them before misuse.
Their method pairs a neural network that flags private fields with a symmetric cipher that locks them. Tests on data sets from ten to forty gigabytes showed no theft or tampering in trials. Locking times stayed low, rising only slightly with size, and beat rival methods on speed. The authors suggest pairing newer ciphers with stronger networks next.
Catalog record
| CREATOR | Changsheng Ma, Ruchun Jia, Jing Lou, Mingqian Wang |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 62 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |