Please use this identifier to cite or link to this item: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/3715
Title: Android Smart Phone Contact Analyzer
Authors: Jayasinghe, C.A.
Issue Date: 15-Sep-2016
Abstract: Smart phones are one of the most troublesome technologies that exist today and steadily gaining popularity with better connectivity, functionality and productivity. The ever-increasing complexity of these smart phones gives a new level of threats. Android is one of the operating systems based on smart phones, is emerging as a significant force within the highly competitive smart phone market. Android phones stores an enormous amount of data that can be stored locally or remotely and allows forensic analysts to acquire these data and evidence, collecting this valuable information with regard to the investigation. When analyzing mobile phone data, it is easier to have an overview / abstract view of the logged data obtained directly from an Android smart phone. It would reveal the patterns of data and direct computer forensic investigators to locate their points of interest. The key focus of this project is to implement a tool to rate phone book contacts / relationships with the phone user by analyzing Android logs and publicly available data in social media websites. Also, it visualizes and presents an abstract view of the people connected with the phone user. This research project reviews the literature in the field of Android forensic methods of retrieving stored data and discusses the criteria and methodology to analyze and rate contacts based on the extracted logged data as well as publicly available data in social media websites with the Mobile Phone User. This will speed-up the investigation process and reduces the time taken for a digital investigation. Also it will improve the quality of the information associated with the data analysis and release the investigator from most low level tasks that they currently have to do.
URI: http://hdl.handle.net/123456789/3715
Appears in Collections:Master of Science in Information Security - 2016

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