Tapjacking Threats and Mitigation Techniques for Android Applications

<p>With the increased dependency on web applications through mobile devices, malicious attack techniques have now shifted from traditional web applications running on desktop or laptop (allowing mouse click- based interactions) to mobile applications running on mobile devices (allowing touch-based interactions). Clickjacking is a type of malicious attack originating in web applications, where victims are lured to click on seemingly benign objects in web pages. However, when clicked, unintended actions are performed without the user’s knowledge. In particular, it is shown that users are lured to touch an object of an application triggering unintended actions not actually intended by victims. This new form of clickjacking on mobile devices is called tapjacking. There is little research that thoroughly investigates attacks and mitigation techniques due to tapjacking in mobile devices. In this thesis, we identify coding practices that can be helpful for software practitioners to avoid malicious attacks and define a detection techniques to prevent the consequence of malicious attacks for the end users. We first find out where tapjacking attack type falls within the broader literature of malware, in particular for Android malware. In this direction, we propose a classification of Android malware. Then, we propose a novel technique based on Kullback-Leibler Divergence (KLD) to identify possible tapjacking behavior in applications. We validate the approach with a set of benign and malicious android applications. We also implemented a prototype tool for detecting tapjacking attack symptom using the KLD based measurement. The evaluation results show that tapjacking can be detected effectively with KLD.</p>

Name thesis:degree_name

Master of Science in Computer Science (MSCS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2014

Author dc:creator

• Cooper, Vanessa

Contributors dc:contributor

• Dr. Hisham M. Haddad
• Dr. Hossain Shahriar
• Dr. Ken Hoganson

• android
• malware detection
• kull-back leibler divergence
• back-off smoothing
• tapjacking
• Computer Engineering
• Computer Sciences
• Engineering
• Information Security
• Other Computer Engineering
• Other Computer Sciences
• Software Engineering

Repository record dc:identifier

https://digitalcommons.kennesaw.edu/etd/632

OAI identifier oai:identifier

oai:digitalcommons.kennesaw.edu:etd-1632