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Privacy Control

Online social networks have become an important part of our social lives, and their inherent privacy problems have become a major concern for users. As of March 2016, 142 million Indians maintain a social network profile on Facebook and 30 million on Twitter, which provides them with a convenient way to communicate with family, friends and even total strangers.

The Services provided by social media though add convenience to our life to a great extent and have made the world a much closely connected, this boon comes with few hidden problems. Though social media lets users share a part of our life to the world, it also gives birth to the security threats to our personal information. 

The users are confronted with a dichotomy between sharing information with their loved ones and friends and sharing information with everyone else on the internet. To help users tackle this dilemma, social networks provide a plethora of privacy settings which allow the user to control his/her privacy according to his/her preferences. This is where our tool Privacy Control comes in and provides usable privacy instead of the painstakingly long privacy policies on social networks.

Before we started the project, we conducted a survey in order to get the insights for what people think about their privacy settings on social media. The results helped us get going with the project.

Hypothesis:  ‘People know about what level of privacy they desire, but generally fail to implement it’.
We asked this questions in the conducted survey, the results we got supported this hypothesis, which was a motivating factor for the project.

Figure 1: Confidence level

While only 22.7% of the people surveyed were definitely sure about their implemented settings, most of the population 63.7% were not sure about it.


Privacy Control is a simple dashboard to control the privacy settings of multiple social networks. It recommends settings to most privacy-friendly values. Moreover, as the privacy policies of such websites can be somewhat arduous to understand, we provide a simple and easy to understand analogies for the same.

This utility of the application extends to the extent of recommending privacy settings in accordance with the individuality of each user according to their characteristics, personal preferences and lingo on social media. Such a utility help protect unwanted visited of sensitive data to public which might be visible by default settings by such websites.

Video -
Figure 2: Steps to using Privacy control

Figure 3: Most used social networks
These results motivated us to target Facebook(95.5% votes) and Twitter(45.5% votes).

How are we recommending settings?

Concluding from various research papers and the results we got by conducting multiple surveys allowed us to reach to the best recommended settings. Some results from the surveys are as follows:

We asked people about what all information they are comfortable to give out publicly and what all they prefer to keep private. The results we got were among the many factors which helped us decide the recommended settings on the OSNs.

Figure 2: Preferred post settings
In the above chart, most people (63.6%) responded the audience of their future posts as ‘Friends’, which is the setting we recommend in our application.

For other similar privacy questions, we recorded the following responses:

Figure 3: Preferred public information

Figure 4: Contact permissions

Usability Testing
We wanted to know how much usability we would offer or how often our tool is going to be used. For this purpose, we circulated the chrome extension among 24 people within IIIT-Delhi. We monitored their usage behaviour for 6 days, by recording the facebook settings they changed using our extension. The following were our findings:
Figure 5: Fluctuation from recommended settings

This figure depicts the overall frequency of usage of our chrome extension over the 6 day period. The extension was used the most number of times on day 1 (80 times), day 2 (71 times) and day 4 (57 times). By ‘used the most number of times’, we mean that most numbers of setting changes were made.
Figure 6: Day-wise distribution of settings change

This shows the usage of our extension on daily basis. The graph represents the most changed facebook settings, data captured for 6 days. Future Posts Visibility setting was changed for the highest number of times on the first day(11 times) and the second day (7 times). Settings for reviewing before tagging, deciding who adds on user timeline and linking FB profiles to outside apps were among the top 4 most changed settings on day 3&4. On the last 2 days (5&6) settings for changing reviewing before tagging, controlling tagged posts visibility and linking FB profiles to outside apps were dominant in terms of numbers of times these settings were changed.
Figure 7: Most changed settings

This pie chart gives the top settings which were changed the most number of times. Setting for reviewing tagged posts on user timeline was changed the most - 38 times. Other settings that were changed often are the settings for tagged posts visibility (32 times), linking FB profiles to other apps (31 times). Settings for who can be your follower and who can see your social actions paired with ads were changed the least number of times in the 6 day span - 8 times (not in the graph).


The main challenge in the implementation was that the social networks don’t provide any easy way to alter users’ settings through API calls. So, the only possible solution that left was to open the page manually and alter the DOM element. To achieve this we developed a chrome extension and extensively used its functions for manipulating the tabs.
The following steps are performed when the user clicks apply settings - 

  • Check logged in user using adblockplus.js
  • Open the social network’s settings page
  • XMLHttpRequest to get the page 
  • Secure the account from page
  • Extract the page headers
  • Edit the settings on the page to the submitted ones
  • Send AJAX post request along with
    • Extracted headers
    • New settings


The platform was highly effective. A lot of testing users were satisfied with their new settings while some didn’t notice much change.
As we surveyed at the end of the 6 days about how beneficial our recommendations were to the users, we got the following results:
Figure 8: Satisfaction tally

13 users thought that the recommended settings that we are providing are actually useful. 6 users were neutral on this. While 5 users were not satisfied by the recommended settings.

The benefit of using this utility is 

There are 27 settings (16 Facebook and 11 Twitter) that our app recommends to the user. Suppose it takes 11 minutes and 15 seconds to properly understand and tweak these privacy settings.
Using our extension it merely takes 15 seconds to change settings. Saving 11 minutes per user.
Now, assuming 10,000 new users use our application daily. 
Average Indian wage per hour is Rs 40.
This is how we will be able to save Rs 74,000 per day.


Privacy control team at PSOSM'17 poster presentation (credits: Siddharth Arya)



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