casprlab / AbuSniffV1

Adversaries leverage social network friend relationships to collect sensitive data from users and target them with abuse that includes fake news, cyberbullying, malware, and propaganda. Case in point, 71 out of 80 user study participants had at least 1 Facebook friend with whom they never interact, either in Facebook or in real life, or whom they believe is likely to abuse their posted photos or status updates, or post offensive, false or malicious content. We introduce AbuSniff, a system that identifies Facebook friends perceived as strangers or abusive, and protects the user by unfriending, unfollowing, or restricting the access to information for such friends. We develop a questionnaire to detect perceived strangers and friend abuse. We introduce mutual Facebook activity features and show that they can train supervised learning algorithms to predict questionnaire responses.

AbuSniff

The following are included in this repository:

• Source code for AbuSniff mobile app
• Data File for this project

Installation

• In order to compile this project and generate apk file, either git clone this project or download the source code in zipped format.
• Import the project in your Android Studio.
• Make any required changes that is required to make the project compatible to your IDE version.
• Compile the code, generate the signed apk and install it in your device.

Data File

This repository also contains the data file that has been collected for this project.

• The data file contains the data in the csv format in the following order: R_ID,Q1,Q2,Q3,Q4,Q5,RECO,Q1_Time,Q2_Time,Q3_Time,Q4_Time,Q5_Time,RECO,STATUS,Response_Time,REASON,POST,PHOTO,MUTUAL,CUR.CITY,HOMETOWN,CUR.STUDY,PAST.STUDY,COM.STUDY,CUR.WORK,PAST.WORK,COM.WORK

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