MAXIMUM CONNECTED LOAD BALANCING COVER TREE ALGORITHM FOR WIRELESS SENSOR NETWORK

In wireless sensor network the main problem is in the network lifetime, power transmission, energy consumption, speed and bandwidth for transmitting the packets and another problem is that the sink node can connect only with the limited nodes if more number of nodes is connected means then there may be occurrence of traffic and the data information can be eliminated. In order to overcome this problem maximum connected load balancing cover tree (MCLCT) algorithm is used. In various studies it is observed that the MCLCT has more network lifetime, power transmission and energy consumption when compared to the other methods and also to solve the optimization problem simulated annealing algorithm is used to transmit the data which form minimum movement in wireless sensor network and which can achieve both target coverage (TCOV) and network connectivity (NCON)

An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm

Data stored on physical storage devices and transmitted over communication channels often have a lot of redundant information, which can be reduced through compression techniques to conserve space and reduce the time it takes to transmit the data. The need for adequate security measures, such as secret key control in specific techniques, raises concerns about data exposure to potential attacks. Encryption plays a vital role in safeguarding information and maintaining its confidentiality by utilizing a secret key to make the data unreadable and unalterable. The focus of this paper is to tackle the challenge of simultaneously compressing and encrypting data without affecting the efficacy of either process. The authors propose an efficient and secure compression method incorporating a secret key to accomplish this goal. Encoding input data involves scrambling it with a generated key and then transforming it through the Burrows-Wheeler Transform (BWT). Subsequently, the output from the BWT is compressed through both Move-To-Front Transform and Run-Length Encoding. This method blends the cryptographic principles of confusion and diffusion into the compression process, enhancing its performance. The proposed technique is geared towards providing robust encryption and sufficient compression. Experimentation results show that it outperforms other techniques in terms of compression ratio. A security analysis of the technique has determined that it is susceptible to the secret key and plaintext, as measured by the unicity distance. Additionally, the results of the proposed technique showed a significant improvement with a compression ratio close to 90% after passing all the test text files

Spread Spectrum Audio Watermarking Using Vector Space Projections

Efficient watermarking techniques guarantee inaudibility and robustness against signal degradation. Spread spectrum watermarking technique makes it harder for unauthorized adversary to detect the position of the embedded watermark in the carrier file, because the watermark bits are spread in the carrier medium. Unfortunately, there is a high possibility that synchronization of the watermark bits and carrier bits will go out of phase. This will lead to watermark detection problem in the carrier bit sequence. In this paper, we propose a vector space projections approach on spread spectrum audio watermarking technique, in order to presents both the watermark bits and carrier bits as vectors. Similarities of watermark vector to a carrier vector are resolve by the normalized dot product of the cosine of angle between them for embedding. After embedding and extraction by the technique, signal processing methods in the form of attacks were applied. Our approach proved robust when compared with other audio watermarking techniques. This technique gives good results and was found to be robust on performance test