MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Computer Engineering & Technology

When the data transferred to the Cloud we use standard encryption methods to secure this data, but when we want to do the calculations on data located on a remote server, it is necessary that the Cloud provider has access to the raw data and then it will decrypt them. In this paper we propose the application of a method to perform the operation on encrypted data without decrypted and provide the same result as well that the calculations were carried out on raw data. {\textcopyright} 2012 IEEE.

World University root node

Engineering and Technology

Proceedings of the 2nd National Days of Network Security and Systems, JNS2 2012

Homomorphic encryption method applied to cloud computing

International Journal of Scientific Engineering and Technology

An Efficient Method for face Recognition Using Kernel Discriminant Analysis

CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) are widespread security measures on the World Wide Web that prevent automated programs from abusing online services. CAPTCHAs are designed to be easy for humans but hard for machines. Academic research into CAPTCHAs takes the form of a friendly 'arms race', with some researchers acting as 'malicious users' that try to attack and defeat the latest CAPTCHA systems automatically. Defeating a CAPTCHA requires two procedures: segmentation and recognition. Recent research shows that the problem of segmentation is much harder than recognition. The efforts to break the CAPTCHA determine its strength & thus in turn help the researcher to build stronger CAPTCHA. In order to test the strength of a particular CAPTCHA, in this paper, we have developed a universal algorithm that measures one of the parameters to measure strength of CAPTCHA. The proposed algorithm can adapt to various cases for segmenting characters from CAPTCHA image. The said algorithm is inspired from projection value of characters, concept of snake game and typical patterns of touching the characters. Experimental results prove that the proposed algorithm has improved correct segmentation rates giving accuracy of 85%. © 2012 Springer-Verlag.

Communications in Computer and Information Science

A new approach towards segmentation for breaking CAPTCHA

CAPTCHA stands for Completely Automated Public Turing test to distinguish Computers and Humans apart. CAPTCHA is a program which can generate and grade the tests that it itself cannot pass. The security aspect of CAPTCHA should be such that none of the computer program should be able to pass the tests generated by it even if the knowledge of the exact working of the CAPTCHA is known. The effectiveness of CAPTCHA of a given strength is determined by how frequently the guesses of CAPTCHA can be tested by an attacker. This paper proposes a simple and uniform framework for the assessment of security and usability of CAPTCHA that arbitrary compositions of security measures can provide". In this sentence instead of "a simple and uniform framework", use "parameters". This paper proposes parameters for the assessment of security and usability of CAPTCHA that arbitrary compositions of security measures can provide.The pre-processing attack on targeted CAPTCHA is demonstrated having success rate of approximately 97% which in turn helps to build more robust and human friendly CAPTCHA. The universal structure for segmentation attack is framed to analyze security of CAPTCHA. © 2012 Springer-Verlag.

Security analysis of CAPTCHA

This paper presents a novel technique for colour image annotation based on neural networks and fuzzy logic. Neural network is proposed for classifying the images based on their contents and fuzzy logic is proposed for interpreting the content of an image in terms of natural language. One of the main aspects of this research is to avoid re-training of the neural networks by training the content of the image. Neural network is not trained on database of images; therefore image can be added or deleted from image database without affecting the training. The proposed hybrid technique is tested on real world colour image dataset and promising results are obtained. © 2012 IEEE.

Proceedings of the 2012 12th International Conference on Hybrid Intelligent Systems, HIS 2012

Colour image annotation using hybrid intelligent techniques for image retrieval

Content-based image retrieval is a difficult area of research in multimedia systems. The research has proven extremely difficult because of the inherent problems in proper automated analysis and feature extraction of the image to facilitate proper classification of various objects. An image may contain more than one object, and to segment the image in line with object features to extract meaningful objects and then classify it in high-level like table, chair, car and so on has become a challenge to the researchers in the field. The latter part of the problem, the gap between low-level features like colour, shape, texture, spatial relationships, and high-level definitions of the images is called the semantic gap. Until this problem is solved in an effective way, the efficient processing and retrieval of information from images will be difficult to achieve. In this chapter, the authors explore the possibilities of how emergence phenomena and fuzzy logic can help solve these problems of image segmentation and semantic gap. © 2012, IGI Global.

Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques

Emergence phenomenon and fuzzy logic in meaningful image segmentation and retrieval

Numerous researches have been conducted for content based representation, analysis and retrieval but mainly for the professionally edited videos such as news, & sports videos not on animation video. The objective is to adapt existing image based information retrieval technique to work efficiently on animation video. This paper shows the use of color feature information when used for the animation video search system. In this proposed work, video clip is accepted as query-by-example and matched video clips are retrieved from animation video database. During the retrieval the color feature is extracted for input video clip using RGB2GRAY, RGB2HSV and RGB2YCBCR color space algorithm and compared with feature vector database in order to rank each video clip according to its distance to the query. We use the Euclidean Distance, City Block Distance and Canberra Distance measures to compute the similarity between the query video clip and each video clip in database. We report experimental result and validate the method on new large database of real animation video. © 2012 ACM.

ACM International Conference Proceeding Series

Feature based retrieval for animation video

International Journal of Computational Biology

The appraisal and Judgment of Nimbus, OpenNebula and Eucalyptus

International Journal of Communication Network Security

Efficient Probe Station Placement and Probe set selection for Fault Localization

Machine learning is an emerging area of computer science that deals with the design and development of new algorithms based on various types of data. Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques addresses the complex realm of machine learning and its applications for solving various real-world problems in a variety of disciplines, such as manufacturing, business, information retrieval, and security. This premier reference source is essential for professors, researchers, and students in artificial intelligence as well as computer science and engineering. © 2012 by IGI Global. All rights reserved.