Project Dissertation Report

Project Dissertation Report-17
The preparation of these hands-on labs are usually the task of Security Instructors who are required to select and use efficient security solutions for their hands-on experiments; the problem that presents itself is that most of these security instructors lack the sufficient hands-on experience and skills.For this reason and because of the diversity of the available security solutions, the security instructors are having much difficulty when selecting the adequate security solutions for their hands-on labs.

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The experiment were carried on three public domain cancer data sets, viz., Ovarian, Colon and Leukemia cancer data to establish its superiority.

Group signature is an extension of digital signature, which allows a group member to sign anonymously a document on behalf of the group.

In this thesis, we designed a group signature protocol based upon hard computa- tional assumptions such as, Discrete Logarithm Problem (DLP), Integer Factor- ization Problem (IFP), and Computational Die Hellmann (CDH) problem.

The proposed scheme is proved to be resistant against colluding attack.

The performance of the proposed MOGA-SVM, classification and clustering method has been compared to MOGA-BP, SVM, BP.

The performance are measured in terms of Silhoutte Index, ARI Index respectively.In case of a legal dispute, an authorized group member can disclose the identity of the group member from the signed document.Group signature can have wide application to corporate world, banks, and e-commerce applications.This paper is a comparative study for educational purpose.It provides analysis based on practical experiments carried out on a number of security solutions regarding their ability to detect ARP spoofing.It includes unexplored unique topics that we are collected form different online resources.We provide this Master degree project for your guide to complete your thesis or dissertation of Master of Engineering(ME), Master of Technology(MTech) and Master of Science(MS).This technique is implemented on microarray cancer data to select training data using multiobjective genetic algorithm with non-dominated sorting (MOGA-NSGA-II).The two objective functions for this multiobjective techniques are optimization of cluster compactness as well as separation simultaneously. the individual chromosome which gives the optimal value of the compactness and separation.As a solution, we propose the requirements for an ideal algorithm that can be used by security solutions to detect effectively any ARP spoofing attack.Analysis and interpretation of DNA Microarray data is a fundamental task in bioinformatics.

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