Detection of Social Media Exploitation via SMS and Camera

Mohamad Adib Azhar,Azuan Ahmad,Azreena Abu Bakar,Madihah Mohd Saudi

doi:10.3991/ijim.v13i04.10521

Abstract

Internet users all over the world are highly exposed to social media exploitation, where they are vulnerable to be targeted by this cyber-attack. Furthermore, excessive use of social media leads to Internet Addiction Disorder (IAD). Fortunately, social media exploitation and IAD can be monitored and controlled closely based on user’s mobile phone surveillance features which are camera, SMS, audio, geolocation (GPS) and call log. Hence to overcome these challenges, this paper presents five (5) Application Programming Interfaces (APIs) and four (4) permissions for SMS and camera that are mostly and widely used with the social media applications. These 9 APIs and permissions matched with 2.7% of the APIs and permissions training dataset that are related with SMS and camera. This experiment was conducted by using hybrid analysis, which inclusive of static analysis and dynamic analysis, with 1926 training dataset from Brunswick. These 9 APIs and permissions, if being misused by the attacker, could lead to privacy concerns of a mobile device. The finding from this paper can be used as a guidance and reference for the formation of new mobile malware detection technique and modeling in future.

Highlights

Human emotion or desire to browse social media via mobile phone to get latest information, communicate with friends and play game, is currently becoming a trend
Prior matching step of the extracted Application Programming Interfaces (APIs) and permission, 1926 of dataset from Brunswick have been downloaded for training purpose [18]. 328 of APIs and permissions for mobile botnet have been reverse engineered by using hybrid analysis and being compared with the APIs and permissions extracted from the social media apps
The following are the findings of API and permission classification for Short Message System (SMS) and camera for mobile botnet from the training dataset and possible exploitation of API and permission in social media apps

Summary

Introduction

Human emotion or desire to browse social media via mobile phone to get latest information, communicate with friends and play game, is currently becoming a trend. Excessive use of social media could lead to Internet Addiction Disorder (IAD) and depression. It is not impossible in future that social media addiction will be categorized as mental disorder due to its implications and impacts to serious depression and lifestyle. 5 main surveillance features which are: SMS, camera, call log, geolocation (GPS) and audio could be exploited by the attacker. They can monitor user’s movement and steal confidential information via these surveillance features. SMS is still being used for communication iJIM ‒ Vol 13, No 4, 2019

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