웨이브렛 변환 계수의 특성을 이용한 생체 영상 암호화 알고리즘
Biometric Image Cryptographic Algorithm Based on the Property of Wavelet Transform Coefficient
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초록
Lossless encryption methods are more applicable than lossy encryption methods when marginal distortion is not tolerable. In this research, the author propose a novel lossless symmetric key encryption/decryption technique. In the proposed algorithm, the image is transformed into the frequency domain using the lifting wavelet transform, then the image sub-bands are encrypted in a such way that guarantees a secure, reliable, and an unbreakable form. The encryption involves scattering the distinguishable frequency data in the image using a reversible weighting factor amongst the rest of the frequencies. The algorithm is designed to shuffle and reverse the sign of each frequency in the transformed image before the image frequencies are transformed back to the pixel domain. The results show a total deviation in pixel values between the original and encrypted image. The decryption algorithm reverses the encryption process and restores the image to its original form. The proposed algorithm is evaluated using standard security and statistical methods; results show that the proposed work is resistant to most known attacks and more secure than other algorithms in the cryptography domain.
Abstract
Lossless encryption methods are more applicable than lossy encryption methods when marginal distortion is not tolerable. In this research, the author propose a novel lossless symmetric key encryption/decryption technique. In the proposed algorithm, the image is transformed into the frequency domain using the lifting wavelet transform, then the image sub-bands are encrypted in a such way that guarantees a secure, reliable, and an unbreakable form. The encryption involves scattering the distinguishable frequency data in the image using a reversible weighting factor amongst the rest of the frequencies. The algorithm is designed to shuffle and reverse the sign of each frequency in the transformed image before the image frequencies are transformed back to the pixel domain. The results show a total deviation in pixel values between the original and encrypted image. The decryption algorithm reverses the encryption process and restores the image to its original form. The proposed algorithm is evaluated using standard security and statistical methods; results show that the proposed work is resistant to most known attacks and more secure than other algorithms in the cryptography domain.
참고문헌 (6)
- Sara Tedmori, "Image Cryptographic Algorithm Based on the Haar Wavelet Transform", Information Sciences, 269, pp.21~34 (2014)
- Y. Chen, "Cheating Prevention in Visual Cryptography", IEEE Trans. Image Process, 21(7), pp.3319~3323 (2012)
- Daubechies, I., "Factoring Wavelet transforms into lifting steps", Asilomar Conference on Signals, Systems, and Computers (1997)
- 신종홍, "Q 인자의 조절이 가능한 이산 웨이브렛 변환을 이용한 디지털 영상처리", (사)디지털산업정보학회 논문지, 10(3), pp.237~247 (2014), (사)디지털산업정보학회
- P. P. Vaidynathan, "Multirate digital filters, filter banks, polyphase network and applications: A Tutorial", Proceedings of the IEEE, 78(1) (1990)
- Park Byeonghoon, "Imaged Cryptographic Algorithm Based on the Lifting Wavelet Transform", 2015The Korea Society of Digital Industry &Information Management Falling Proceeding, pp.47~51 (2015)
