Name
Abstract | ||
|---|---|---|
This paper proposes a new object-based authenticated encryption scheme with a constant sized signature. We combine the deep learning algorithm and some cryptographic techniques, such as symmetric key encryption and digital signatures, to satisfy the requirements mentioned above. Based on the deep learning algorithm, the objects are detected and each object unit is encrypted with a different key, thereby enabling access per object unit. The applied forward secure digital signature scheme guarantees not to forge a signature on the already captured image frames even if the device is hijacked.
Experimental results show that the proposed scheme is practical in a real-time system due to the high performance of signature generation (10.5ms per frame) and a constant signature size overhead.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3297280.3297594 | SAC |
Keywords | Field | DocType |
authentication, digital signature, forward-secure signature, object detection, privacy, surveillance | Symmetric-key algorithm,Object detection,Authentication,Cryptography,Computer science,Digital signature,Encryption,Artificial intelligence,Deep learning,Computer hardware,Authenticated encryption | Conference |
ISBN | Citations | PageRank |
978-1-4503-5933-7 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jihye Kim | 1 | 2 | 7.46 |
| Hankyung Ko | 2 | 1 | 1.70 |
| Hyunok Oh | 3 | 457 | 40.49 |