Summary:
The search providers track the user’s browsing behavior to construct his or her activity profile. The tracking helps the search engines to fine-tune the results and presenting user-specific advertising. When a search input matches with some commercial product or service offering, ads based on the previously saved interests, likes, and dislikes are displayed. The number of web searches from mobile devices has exceeded that of desktops. People use mobile devices for critical business tasks like e-commerce, banking transactions, video conferences, email communication, and storing confidential data. Companies are moving towards a mobile app-only strategy. The advertisers are now displaying ads on mobile apps as well. Security incidents on mobile devices are on the rise, and they are frequently being used in committing criminal activities. Ads can often reveal the location, gender, age, and other valuable data about the user. This paper aims to extract ads on mobile devices, retrieve user-specific information to reconstruct the user profile and to predict the user’s identity. The authors have shown that, with their system and method based on ads analysis, a user can be identified even if he or she is using the same device, multiple devices, different networks or following different usage patterns. The proposed system can be used as one of the techniques in the digital forensic readiness framework for mobile devices. The system has a wide range of applications in context-based security and proactive and reactive digital forensic investigation.
Publication Type: Conference
Publication Date: January 6th, 2016
Publisher: Twelfth Annual IFIP WG 11.9 International Conference on Digital Forensics
Author(s): Dr. Gaurav Gupta, Jayaprakash Govindaraj, Dr. Robin Verma
Links:
978-3-319-46279-0_6.pdf (springer.com)