Protection of biometric data is gaining interest and digital watermarking techniques are used to protect the biometric data from either accidental or intentional attacks. Among the various biometrics, fingerprints are more famous in the authentication area, as they are unique to each person and are mainly used for the establishment of instant personal identity. However, they are susceptible to accidental and intentional attacks, when transmitted over network. Thus, a protective scheme is needed which will preserve fidelity and prevent alterations. This paper considers two techniques that protects of fingerprint biometric data using digital watermarking techniques. Both the techniques discussed are based on Discrete Wavelet Transformation (DWT). From the experimental results, it can be concluded that both techniques provide adequate security to the fingerprint data without degrading visual quality. Further, the verification performance after dewatermarking is also analyzed.

Many emerging computer applications require the processing of large numbers, larger than what a CPU can handle. In fact, the top of the line PCs can only manipulate numbers not longer than 32 bits or 64 bits. This is due to the size of the registers and the data-path inside the CPU. As a result, performing arithmetic operations such as subtraction on big-integer numbers is to some extend limited. Different algorithms were designed in an attempt to solve this problem; they all operate on big-integer numbers by first converting them into a binary representation then performing bitwise operations on single bits. Such algorithms are of complexity O(n) where n is the total number of bits in each operand. This paper proposes two new algorithms for performing arithmetic subtraction on big-integer numbers. The two algorithms are different in that one is sequential while the other is parallel. The similarity between them is that both follow the same concept of dividing the big-integer inputs into several blocks or tokens of 60 bits (18 digits) each; thus reducing the input size n in O(n) by a factor of 60. Subtraction of corresponding tokens, one from each operand, is performed as humans perform subtraction, using a pencil and a paper in the decimal system. Both algorithms are to be implemented using MS C#.NET 2005 and tested over a multiple processor system. Further studies can be done on other arithmetic operations such as addition and multiplication.

The wireless networks can be employed to provide network connectivity almost anywhere, it provides large companies the option to connect the current wired networks to the new wireless network without any problems and gives user the option to use any kind of applications regardless of its source or vendors. However, the WLAN performance is a key factor in spreading and usage of such technologies. Also the Wireless local area networks (WLAN) are more bandwidth limited as compared to the wired networks because they rely on an inexpensive, but error prone, physical medium (air).Hence it is important to improve their performance. In this paper the performance optimization methods have been presented using an advanced network simulator, OPNET modeler 9.1. The previous research mainly focused on improving the performance via network layer [1-3]. Here performance optimization has been shown via a series of simulation tests with different parameters such as Data rate, Fragmentation threshold, RTS/CTS threshold, buffer size and the physical characteristics. The different quality of service parameters are chosen to be the throughput, media access delay, the retransmission attempts, dropped data packets and Queue size etc. Then finally the results are compiled to improve the performance of wireless local area networks.