Data Mining - Concepts and Techniques.

Expert Cloud

Security of financial transaction in e-commerce is difficult to implement and there is a risk that users confidential data over the internet may be accessed by hackers. Unfortunately, interacting with an online service such as a banking web application often requires certain degree of technical sophistication that not all Internet users possess. For the last couple of years such naive users have been increasingly targeted by phishing attacks that are launched by miscreants who are aiming to make an easy profit by means of illegal financial transactions. In this paper, we have proposed an idea for securing e-commerce transaction from phishing attack. An approach already exists where phishing attack is prevented using one time password which is sent on users registered mobile via SMS for authentication.But this method can be counter attacked by man in the middle.In our paper, a new idea is proposed which is more secure compared to the existing online payment system using OTP. In this mechanism, OTP is combined with the secure key and is then passed through RSA algorithm to generate the Transaction password. A copy of this password is maintained at the server side and is being generated at the user side using a mobile application.So that it is not transferred over the insecure network leading to a fraudulent transaction.

Securing SMS Based One Time Password Technique from Man in the Middle Attack

Non-terrestrial networks (NTNs) traditionally had certain limited applications. However, the recent technological advancements opened up myriad applications of NTNs for 5G and beyond networks, especially when integrated into terrestrial networks (TNs). This article comprehensively surveys the evolution of NTNs highlighting its relevance to 5G networks and essentially, how it will play a pivotal role in the development of 6G and beyond wireless networks. The survey discusses important features of NTNs integration into TNs by delving into the new range of services and use cases, various architectures, and new approaches being adopted to develop a new wireless ecosystem. Our survey includes the major progresses and outcomes from academic research as well as industrial efforts. We first start with introducing the relevant 5G use cases and general integration challenges such as handover and deployment difficulties. Then, we review the NTNs operations in mmWave and their potential for the internet of things (IoT). Further, we discuss the significance of mobile edge computing (MEC) and machine learning (ML) in NTNs by reviewing the relevant research works. Furthermore, we also discuss the corresponding higher layer advancements and relevant field trials/prototyping at both academic and industrial levels. Finally, we identify and review 6G and beyond application scenarios, novel architectures, technological enablers, and higher layer aspects pertinent to NTNs integration.

Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey.

In this paper we present MD, a logical model for OLAP systems, and show how it can be used in the design of multidimensional databases. Unlike other models for multidimensional databases, MD is independent of any specific implementation (relational or proprietary multidimensional) and as such it provides a clear separation between practical and conceptual aspects. In this framework, we present a design methodology, to obtain an MD scheme from an operational database. We then show how an MD database can be implemented, describing translations into relational tables and into multidimensional arrays.

A logical approach to multidimensional databases

Alzheimer's disease is characterized by the presence of abnormal protein bundles in the brain tissue, but experts are not yet sure what is causing the condition. To find a cure or aversion, researchers need to know more than just that there are protein differences from the usual; they also need to know how these brain nerves form so that a remedy may be discovered. Machine learning is the study of computational approaches for enhancing performance on a specific task through the process of learning. This article presents an Alzheimer's disease detection framework consisting of image denoising of an MRI input data set using an adaptive mean filter, preprocessing using histogram equalization, and feature extraction by Haar wavelet transform. Classification is performed using LS-SVM-RBF, SVM, KNN, and random forest classifier. An adaptive mean filter removes noise from the existing MRI images. Image quality is enhanced by histogram equalization. Experimental results are compared using parameters such as accuracy, sensitivity, specificity, precision, and recall.

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Machine Learning and Image Processing Enabled Evolutionary Framework for Brain MRI Analysis for Alzheimer's Disease Detection

In this paper, we have provided a brief literature survey of object recognition & detection in remote sensing. These scene recognition images have more components and more challenging issues in the range of aerial image resolutions. It also shows a critical act as a limited area based on functions. The object detection in optical remote sensing has the best critical part of over supposing conditions of characteristic against affecting a model inputs. Certain moving characteristic act as a set of quality to define a based on personal action. This paper provides a brief summary of different object detection in remote sensing images and also discuss about their strength and limitation. The main focus of this review paper is on the satellite image. A subsists in patent of scene recognition of current model act on a freshly process. Inter relates to the land uses analysis system, other model analysis process as well as turn to the appropriate function. We have also discussed the problems and advancement of current scenario and give three research directions for deep learning for medical image recognition, image classification, and health care. We ensure this review article will provide adequate directions and scope for the betterment of the research community in the field of object recognition & detection in remote sensing.

Object Recognition and Detection in Remote Sensing Images: A Comparative Study

An Object-Oriented database can utilize the benefits of both the design and implementation of any application. Due to the increased popularity of database systems many new database systems based on varying data model and implementation have entered in the market. Database systems have complex architecture but they are the key factors behind the business transformations. Choosing the best one in any category is an important task based on performance analysis. This chapter deals with the database estimation methodology which integrates the database analysis task and performance analysis task. There are three major techniques for the performance estimation which are analytical modeling, simulation modeling and benchmarking.

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Performance Comparison between Relational and Object-Oriented Databases

In the current scenario, the size of database related to any organization is rapidly increasing and due to evolution of the object-oriented approach, many of the Software Industries are converting the old structured approach based softwares into the object-oriented based softwares. Therefore, for the large amount of database, it is necessary to study the faster retrieval system as On-Line Analytical Processing (OLAP) which was introduced by E.Codd in 1993. The present paper is an attempt in this direction and object-oriented approach with the help of Unified Modeling Language (UML) is used to create OLAP cube which supports three dimensional data. A real case study of Indian Postal Services is considered to store large amount of data in the OLAP cube and can be easily used for the analysis purpose. UML class model, sequence diagram and star schema of object-oriented database are designed along with the OLAP cube. For testing purpose, some sample queries are also performed on the object-oriented database.

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Olap cube representation for object - oriented database

Due to the evolution of the Electronic Learning (E-Learning), one can easily get desired information on computer or mobile system connected through Internet. Currently, E-Learning materials are easily accessible on the desktop computer system, but, in future, most of the information shall also be available on small digital devices like Mobile, PDA, etc. Most of the E-Learning materials are paid and customer has to pay entire amount through credit/debit card system. Therefore, it is very important to study about the security of the credit/debit card numbers. The present paper is an attempt in this direction and a security technique is presented to secure the credit/debit card numbers supplied over the Internet to access the E-Learning materials or any kind of purchase through Internet. A well known method i.e. Data Cube Technique is used to design the security model of the credit/debit card system. The major objective of this paper is to design a practical electronic payment protocol which is the safest and most secured mode of transaction. This technique may reduce fake transactions which are above 20% at the global level, al beit, it shows a declining trend in the recent past.

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Ajay Pratap

Papers

Machine Learning and Image Processing Enabled Evolutionary Framework for Brain MRI Analysis for Alzheimer's Disease Detection

Object Recognition and Detection in Remote Sensing Images: A Comparative Study

Performance Comparison between Relational and Object-Oriented Databases

Olap cube representation for object - oriented database

A Data Mining Technique for a Secure Electronic Payment Transaction