Master of Computer Application

This is to certify that the thesis entitled Automatic detection of Fake Profiles in Online Social Networks submitted by Ranabothu Nithin Reddy and Nitesh Kumar , in partial fulfillment of the requirements for the award of Bachelor of Technology Degree in Computer Science and Engineering at National Institute of Technology Rourkela is an authentic work carried out by them under my supervision and guidance. To the best of my knowledge, the matter embodied in the thesis has not been submitted to any other university / institution for the award of any Degree or Diploma.

The evolution of the computer world and the proliferation of storage devices has led to an explosion of available information, so that made their exploitation difficult. In addition, it has been found that a large part of this data will not be stored or used; however, it constitutes a precious raw material to understand the activity and anticipate its evolution. To cope with these problems, professionals implemented a decision making support systems (or decision support systems) and which allow a synthetic and multidimensional treatment of all available and stored information, hence the birth of the data warehouse and data mining techniques. This paper introduces the data warehousing, gives researchers terminologies necessary for understanding the process, and summarizes its evolution. It also presents an analysis of the latest research in the field, and explores the future trends. And therefore, this study provides a reference for researchers wishing to contribute in this area.

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. In this paper, we describe the novel techniques we developed to create an Iris Recognition System, in addition to an analysis of our results. We used a fusion mechanism that amalgamates both, a Canny Edge Detection scheme and a Circular Hough Transform, to detect the iris' boundaries in the eye's digital image. We then applied the Haar wavelet in order to extract the deterministic patterns in a person's iris in the form of a feature vector. By comparing the quantized vectors using the Hamming Distance operator, we determine finally whether two irises are similar. Our results show that our system is quite effective.