dc.contributor |
Graduate Program in Computer Engineering. |
|
dc.contributor.advisor |
Alagöz, Fatih. |
|
dc.contributor.author |
Can, Yekta Said. |
|
dc.date.accessioned |
2023-03-16T10:01:46Z |
|
dc.date.available |
2023-03-16T10:01:46Z |
|
dc.date.issued |
2014. |
|
dc.identifier.other |
CMPE 2014 C36 |
|
dc.identifier.uri |
http://digitalarchive.boun.edu.tr/handle/123456789/12264 |
|
dc.description.abstract |
Watermarking has become important in the last decade because of the copyright protection applications. Embedding information into an audio le is more di cult as compared to images, because human auditory system is more sensitive than human visual system. Therefore, the proposed watermarking algorithms for digital audio have been less than those for digital image and video. This thesis presents a biometric authentication scheme based on spread spectrum watermarking technique. We add a biometric authentication system to the Sipdroid open source VoIP program. Firstly, senders must register to the system with their unique biometric features. T.C Identity number, keystroke dynamics and voice are used as biometric features. After registration, these biometric features are used as watermarked material. Before embedding, the watermark is spread with the Direct Sequence Spread Spectrum (DSSS) technique. While talking, this watermark material is embedded to speech and sent to receiver using Frequency Hopping Spread Spectrum(FHSS) technique. The watermarked biometric data is constructed in the receiver's phone after conversation is nished. This method does not need the original audio carrier signal when extracting watermark because it is using the blind extraction. The experimental results demonstrate that the embedding technique is not only less audible but also more robust against the common signal processing attacks like low-pass lter, adding white Gaussian noise, shearing, and compression. In order for receiver to be able to login to the system, biometric features of the user should match with the watermarked biometric data. |
|
dc.format.extent |
30 cm. |
|
dc.publisher |
Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2014. |
|
dc.subject.lcsh |
Biometric identification. |
|
dc.subject.lcsh |
Identification -- Automation. |
|
dc.subject.lcsh |
Pattern recognition systems. |
|
dc.title |
A biometric authentication technique using spread spectrum audio watermarking |
|
dc.format.pages |
xiii, 62 leaves ; |
|