Authors B.Prabhavathi P.D.Chidhambara Rao P.Raja Sekhar Ishrath Jahan G.Murali Mohan
Authors G.V.SURESH Shabbeer Shaik O.Srinivasa Reddy B. Munibhadrayya
Authors Zied TRIFA Mohamed LABIDI Maher KHEMAKHEM
Authors A. Joseph Raphael V. Sundaram
Authors B. I. Ahmad F. Yakubu M. A. Bagiwa U. I. Abdullahi
Authors Abdelali EL BOUCHTI Said EL KAFHALI Abdelkrim HAQIQ
Authors Munisha Kaushal Rakshpal Singh Dehal Mrs.Amrit kaur Zumita Kaushal
Authors Sourabh Rungta Kshitij Verma Neeta Tripathi Anupam Shukla
Authors Eva Cipi Betim Cico
Authors Ravindra Babu Kallam S.Udaya Kumar A.Vinaya babu V.Shravan kumar
A Novel Approach for Security Development for Multimedia System Abstract: Efficient multimedia encryption algorithms play a key role in  multimedia security protection. We introducing multiple Huffman Tables  (MHT), which performs both compression and encryption by using multiple  statistical models (i.e. Huffman coding tables) in the entropy encoder and  multiple Huffman tables are kept secret. A known-plaintext attack is  presented to show that the MHTs used for encryption should be carefully  selected to avoid the weak keys problem.  We then propose chosen-plaintext attacks on the basic MHT algorithm as well as the advanced scheme with random bit insertion. In addition, we suggest two empirical criteria for Huffman table selection, based on which we can simplify the stream cipher integrated scheme, while ensuring a high level of security. Keywords : Cryptanalysis; Encryption; Entropy encoding; Multiple Huffman Tables (MHT); Selective Encryption. Classification of Uncertain data using Fuzzy Neural Networks Abstract: Data mining has emerged to be a very important research area  that helps organizations make good use of the tremendous amount of data  they have. In this data uncertainty is common in real-world applications  due to various causes, including imprecise measurement, network latency,  out-dated sources and sampling errors. These kinds of uncertainty have to  be handled cautiously, or else the mining results could be unreliable or  even wrong. We propose that when data mining is performed on uncertain  data, uncertainty has to be considered in order to obtain high quality data  mining results. In this paper we explores a fuzzy neural network for  classification of uncertain data and suggests how uncertainty can be  incorporated in data mining and how to handle data uncertainty in data  mining by using a Fuzzy neural network.  Keywords : Neural networks; Fuzzy logic; data classification; uncertain  data; fuzzy neural network.  Dynamic Time Warping Algorithm with Distributed Systems Abstract: Distributed computing is the method of splitting a large problem  into s