We present a cryptanalysis of a remote user authentication scheme proposed by Hwang and Li (see ibid., vol.46, no.1, p.28-31, 2000). We show that Hwang-Li's scheme is breakable. A legitimate user can impersonate other legal users and pass the system authentication.

In this paper, the security of a modified remote user authentication scheme proposed by Shen, Lin, and Hwang is analyzed. We show that the modified scheme is still vulnerable to the attack proposed by Chan and Cheng. Moreover, the extended attack proposed by Chang and Hwang in 2003 also works well.

An improved data hiding technique by optimal moderately-significant-bit replacement is presented, which can significantly reduce the computational cost and enhance the visual quality of the resulting stego-image.

The use of human biometrics is becoming widespread and their major application is human recognition for controlling unauthorized access to both digital services and physical localities. However, the practical deployment of human biometrics for recognition poses a number of challenges, such as template storage capacity, computational requirements, and privacy of biometric information. These challenges are important considerations, in addition to performance accuracy, especially for authentication systems with limited resources. In this paper, we propose wave atom transform (WAT) based palm-vein recognition scheme. The scheme computes, maintains, and matches palm-vein templates with less computational complexity and less storage requirements under secure and privacy-preserving environment. First, we extract palm-vein traits in the WAT domain, which offers sparser expansion and better capability to extract texture features. Then, randomization and quantization are applied to the extracted features to generate a compact, privacy-preserving palm-vein template. We analyze the proposed scheme for its performance and privacy-preservation. The proposed scheme obtains equal error rates (EER) of 1.98%, 0%, 3.05%, and 1.49 for PolyU, PUT, VERA and our palm-vein datasets, respectively. The extensive experimental results demonstrate comparable matching accuracy of the proposed scheme with a minimum template size and computational time of 280 bytes and 0.43 seconds, respectively.