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Full-Text Articles in Engineering
Automated Dynamic Detection Of Self-Hiding Behaviors, Luke Baird
Automated Dynamic Detection Of Self-Hiding Behaviors, Luke Baird
Student Works
Certain Android applications, such as but not limited to malware, conceal their presence from the user, exhibiting a self-hiding behavior. Consequently, these apps put the user’s security and privacy at risk by performing tasks without the user’s awareness. Static analysis has been used to analyze apps for self-hiding behavior, but this approach is prone to false positives and suffers from code obfuscation. This research proposes a set of three tools utilizing a dynamic analysis method of detecting self-hiding behavior of an app in the home, installed, and running application lists on an Android emulator. Our approach proves both highly accurate …
Automated Dynamic Detection Of Self-Hiding Behavior In Android Apps, Luke Baird, Seth Rodgers
Automated Dynamic Detection Of Self-Hiding Behavior In Android Apps, Luke Baird, Seth Rodgers
Student Works
Android applications that conceal themselves from a user, defined as exhibiting a “self-hiding behavior,” pose a threat to the user’s privacy, as these applications can live on a device undetected by the user. Malicious applications can do this to execute without being found by the user. Three lists are analyzed in particular—the home, running, and installed lists—as they are directly related to the typical Android app life cycle. Additionally, self-hiding behavior in the device admin list is analyzed due to the potential for catastrophic actions to be taken by device admin malware. This research proposes four dynamic analysis tools that …
Map My Murder: A Digital Forensic Study Of Mobile Health And Fitness Applications, Courtney Hassenfeldt, Shabana Baig, Ibrahim Baggili, Xiaolu Zhang
Map My Murder: A Digital Forensic Study Of Mobile Health And Fitness Applications, Courtney Hassenfeldt, Shabana Baig, Ibrahim Baggili, Xiaolu Zhang
Electrical & Computer Engineering and Computer Science Faculty Publications
The ongoing popularity of health and fitness applications catalyzes
the need for exploring forensic artifacts produced by them. Sensitive
Personal Identifiable Information (PII) is requested by the applications
during account creation. Augmenting that with ongoing
user activities, such as the user’s walking paths, could potentially
create exculpatory or inculpatory digital evidence. We conducted
extensive manual analysis and explored forensic artifacts produced
by (n = 13) popular Android mobile health and fitness applications.
We also developed and implemented a tool that aided in the timely
acquisition and identification of artifacts from the examined applications.
Additionally, our work explored the type of …
Permission-Based Privacy Analysis For Android Applications, Erza Gashi, Zhilbert Tafa
Permission-Based Privacy Analysis For Android Applications, Erza Gashi, Zhilbert Tafa
International Journal of Business and Technology
While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s safety …