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Chakraborty, Sanjay
- Study and Analysis of a New Data Encryption Technique Using Special Symbols Shifting
Authors
1 RERF, Kolkata (WB), IN
Source
Networking and Communication Engineering, Vol 4, No 6 (2012), Pagination: 311-315Abstract
This paper is a contribution to the field of network security.It states a new technique named “Symbol Shifting Cipher” for encryption and decryption to prevent unauthorized access of data.It states a new encryption technique for secure data transmission.This paper describes that the alphabets, digits and space between the words of the plain text are replaced by their corresponding ASCII values and by some assigned symbols.These symbols are then represented in (nXn) matrix where each elements of the matrix are shifted to their corresponding columns.Then the elements of the (nXn) matrix are written in a sequence and again are replaced by corresponding ASCII values and alphabets, digits, space to create the final cipher text.This paper also compares this new cipher technique with some others renowned cipher techniques (such as Ceaser cipher, Vernam cipher) with respect to their complexity of the techniques and the probability to break the cipher code.Keywords
Cryptography, Symbol Shifting, Encryption, Decryption.- Weather Forecasting Using Incremental K-Means Clustering
Authors
1 National Institute of Technology (NIT), Raipur, CG, IN
2 University of Kalyani, Kalyani, W.B., IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 5 (2012), Pagination: 214-219Abstract
Clustering has wide application areas in several research fields. Clustering is a powerful tool which has been used in several forecasting works, such as time series forecasting, real time storm detection, flood forecasting and so on. In this paper, a generic methodology for weather forecasting is proposed by the help of incremental K-means clustering algorithm. Weather forecasting plays an important role in day to day applications. Weather forecasting of this paper is done based on the incremental air pollution database of west Bengal in the years of 2009 and 2010. This paper generally uses typical K-means clustering on the main air pollution database and a list of weather category will be developed based on the maximum mean values of the clusters.Now when the new data are coming, the incremental K-means is used to group those data into those clusters whose weather category has been already defined. Thus it builds up a strategy to predict the weather of the upcoming data of the upcoming days. This forecasting database is totally based on the weather of west Bengal and this forecasting methodology is developed to mitigating the impacts of air pollutions and launch focused modeling computations for prediction and forecasts of weather events. Here accuracy of this approach is also measured.Keywords
Air-Pollution Dataset, Clustering, Forecasting, Incremental K-Means, Weather.- An Advanced Dictionary Based Lossless Compression Technique for English Text Data
Authors
1 IEM, Kolkata, IN
Source
Biometrics and Bioinformatics, Vol 7, No 1 (2015), Pagination: 4-11Abstract
Data compression technique helps us to reduce the size of such large volumes of data that reduces network bandwidth and the storage spaces as well. So text compression is a very important concept in Data Management. The research aim of this paper is to present a new lossless data compression technique for English text compression. It is basically a two steps process. Firstly, there is a reduction using a Dictionary-based lookup table. The dictionary based look-up table is made of as a part of the operating system. The dictionary based look-up table replaces the word by an 18-bit address. The reduction using the look-up table gives us a compression of more than 50% in most cases and the result is stored in a binary file. It is then followed by a compression using a modified Huffman Algorithm, which takes 6 bit data block at a time to build up the Huffman tree. This step together with the reduction, compresses the file to around 32-38% of its original size. Beside this approach, this paper also describes the comparison of this new technique with other well-known compression methods.