Date of Award


Document Type

Thesis - SCU Access Only


Santa Clara : Santa Clara University, 2018.

Degree Name

Doctor of Philosophy (PhD)


Computer Engineering

First Advisor

Silvia Figueira


The World Wide Web evolved as the single largest platform for information exchange and interaction in this universe. This thesis focuses on its further evolution as entirely truthful and in the process, discusses various topics related to the evolution of the Web, its humanitarian applications, the Cloud Computing and Big Data phenomena that are propelling the evolution. The work covers the entire SMAC space - Social, Mobile, Analytics, and Cloud that have been the primary drivers of technological innovation.

Economy grows as more and more people join its core echelons. People are the most important economic resources at all times. The Web, being humanity's largest source of information and interaction, probably has the most technological potential to get people into mainstream. It can serve as a conduit of humanitarian services to the underprivileged and presents a huge opportunity to meet humanitarian challenges. In this thesis, we discuss the role that a truthful World Wide Web can play in achieving humanitarian goals. The thesis discusses ideas, applications, tools, and techniques to make the Web more robust and truthful in order to meet the humanitarian challenges.

A major humanitarian application of the truthful Web is our idea of medical diagnosis for the masses. Two of the chapters are devoted to how information retrieval techniques can be used to provide medical diagnosis to the millions of underprivileged population across the world who do not have proper access to healthcare. Another example of a humanitarian challenge is good governance, which requires fair election process. Andres Sepulveda created news by rigging elections throughout Latin America for almost a decade by manipulating information on the Web. He proved that fraud on the Web can impact even the most important Presidential elections of a country substantially. The thesis explores ways to detect similar attacks in future, so that they can be prevented. We present a novel framework for using statistical techniques to help in detecting veiled attacks like that of Andres Sepulveda on Online Social Networks (OSN) . We take a specific example, detail how the statistical technique of Cumulative Sum, modified for our purpose, can be applied and present the results of applying the technique to various scenarios. We compare its efficiency with that of Kalman Filter applied to the same problem, data set, and scenarios.

The first scientific step to model complexity in the world has often been to express it in math. Math helps to improve the understanding of matter. We therefore use math where possible to enhance our comprehension of the subject. Algorithms can then be derived from the math, where needed.

An entirely truthful World Wide Web should indeed be the next milestone for the Web. This thesis is hoped to initiate the discussion towards this lofty goal.

SCU Access Only

To access this paper, please log into or create an account in Scholar Commons using your email address.