Some new classes of (almost) perfect cc-nonlinear permutations

The concept of differential uniformity was recently extended to the $c$-differential uniformity. An interesting problem in this area is the construction of functions with low $c$-differential uniformity and a lot of research has been done in this direction in the recent past. Here, we present three classes of (almost) perfect $c$-nonlinear permutations over finite fields of even characteristic

Forest Tree Algorithm- An Efficient Approach of Data Mining Over Decision Tree

Mining of Data (DM) is a way to display different models, summaries and values derived from a given data collected. The DM itself works in the process of searching for analytical information on the large number of available databases. An example of a predictive enigma is targeted marketing. There are many factors that affect data mining performance in large data sets. In this article we will use the forest tree technique to improve performance in search for data and implementation, surely overcome the previous work performance that includes the approach of the existing tree decision tree algorithm

The c-differential uniformity and boomerang uniformity of two classes of permutation polynomials

The article of record as published may be found at http://dx.doi.org/10.1109/TIT.2021.3123104The Difference Distribution Table (DDT) and the differential uniformity play a major role for the design of substitution boxes in block ciphers, since they indicate the func- tion’s resistance against differential cryptanalysis. This concept was extended recently to c-DDT and c-differential uniformity, which have the potential of extending differential cryptanalysis. Recently, a new theoretical tool, the Boomerang Connectivity Table (BCT) and the corresponding boomerang uniformity were introduced to quantify the resistance of a block cipher against boomerang-style attacks. Here we concentrate on two classes (introduced recently) of permutation polynomials over finite fields of even characteristic. For one of these, which is an involution used to construct a 4-uniform permutation, we explicitly determine the c-DDT entries and BCT entries. For the second type of function, which is a differentially 4-uniform function, we give bounds for its c-differential and boomerang uniformities.The research of Sartaj Ul Hasan is partially supported by MATRICS grant MTR/2019/000744 from the Science and Engineering Research Board, Government of India. Pantelimon Stănică acknowledges the sabbatical support from Naval Postgraduate School from September 2020 to July 2021

Forest Tree- An Efficient Proposal Approach for Data Mining

Data Mining (DM) is a way of looking on different models, summaries, & derived values from a given gathered data. DM itself work on the process of looking for analytical information in huge amount of available databases. An illustration of a predictive riddle is targeted marketing. There are many factors that influence the performance of mining on large data sets. In this paper we are going to use forest tree technique in order to improve the way of performance of how the data is to be fetched and when on implementation it will definitely overcome the performance of previous work which includes existing approach decision tree algorithm