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21 changes: 21 additions & 0 deletions LICENSE
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MIT License

Copyright (c) 2018 K N Dheeraj

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
32 changes: 32 additions & 0 deletions README.md
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# Web-Content-Authenticator
This is a Firefox plugin which gives a confidence score to each of the links returned by the Google Search Engine.

### Contents
- [Introduction](#introduction)
- [Factors Considered](#factor-considered)
- [Technologies and Languages](#technologies-and-languages-used-in-development)
- [Future Developments](#future-developments)

### Introduction
With advent of Internet, many things have changed for users. Like ablility to shop Online, book for Online Services, Mobile Payment Services and able to fetch or read data from any place on the world. But still the **Integrity of data** that the user is having is still under compromise. So this Project gave birth!!
This project is based on the fact of how much we can trust a link found over the Internet. This is a *Firefox plugin powered by a python Django framework* in the backend which calculates a score for each link returned by the Google search engine after considering various factors.

### Factors Considered
The factors which are considered now is whether the links is using https or http protocol and the domain of the links.

* The domains in the list [org,edu etc] are given higher priorities if found in the links, then comes the government websites such as [in,uk, etc] followed by the commcercial websites.
* Then a correlation function is applied on these resultset to generate a score which is in between 0 and 1 . Higher the score, better trust worthy are the links.

### Technologies and Languages used in Development
1. At the Frontlevel, we developed a JavaScript file that works as a plugin in the FireFox Browser which helps in sending the links retrieved by google search to your Django Server.
2. At the BackEnd, the links sent to Server are reached via AJAX call and then the values of each Factor are retrieved by operating on each link.
3. Then each parameter is stored in the Database.
4. Logic of Correlation is the performed over the Parameter Values to develop the Confidence Score.
5. These Computed Scores are then retrieved from server and displayed on the browser using JavaScript.

### Future developments
We have planned to consider various number of factors to contribute to give a more appropriate score. Such as number of web trackers working in the websites, number of out going links, Using sentimental analysis to get the motive of the content, do a back ground search of the author who wrote it etc.

## Important Note
Any user using this Repo should include this Git link and Contributor's name in their work.

## Contributors
K. N. Dheeraj (kndheeraj0@gmail.com)