Matching Items (3)
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- All Subjects: graph
- Creators: Bazzi, Rida
Description
On Android, existing security procedures require apps to request permissions for access to sensitive resources.
Only when the user approves the requested permissions will the app be installed.
However, permissions are an incomplete security mechanism.
In addition to a user's limited understanding of permissions, the mechanism does not account for the possibility that different permissions used together have the ability to be more dangerous than any single permission alone.
Even if users did understand the nature of an app's requested permissions, this mechanism is still not enough to guarantee that a user's information is protected.
Applications can potentially send or receive sensitive information from other applications without the required permissions by using intents.
In other words, applications can potentially collaborate in ways unforeseen by the user, even if the user understands the permissions of each app independently.
In this thesis, we present several graph-based approaches to address these issues.
We determine the permissions of an app and generate scores based on our assigned value of certain resources.
We analyze these scores overall, as well as in the context of the app's category as determined by Google Play.
We show that these scores can be used to identify overzealous apps, as well as apps that do not properly fit within their category.
We analyze potential interactions between different applications using intents, and identify several promiscuous apps with low permission scores, showing that permissions alone are not sufficient to evaluate the security risks of an app.
Our analyses can form the basis of a system to assist users in identifying apps that can potentially compromise user privacy.
Only when the user approves the requested permissions will the app be installed.
However, permissions are an incomplete security mechanism.
In addition to a user's limited understanding of permissions, the mechanism does not account for the possibility that different permissions used together have the ability to be more dangerous than any single permission alone.
Even if users did understand the nature of an app's requested permissions, this mechanism is still not enough to guarantee that a user's information is protected.
Applications can potentially send or receive sensitive information from other applications without the required permissions by using intents.
In other words, applications can potentially collaborate in ways unforeseen by the user, even if the user understands the permissions of each app independently.
In this thesis, we present several graph-based approaches to address these issues.
We determine the permissions of an app and generate scores based on our assigned value of certain resources.
We analyze these scores overall, as well as in the context of the app's category as determined by Google Play.
We show that these scores can be used to identify overzealous apps, as well as apps that do not properly fit within their category.
We analyze potential interactions between different applications using intents, and identify several promiscuous apps with low permission scores, showing that permissions alone are not sufficient to evaluate the security risks of an app.
Our analyses can form the basis of a system to assist users in identifying apps that can potentially compromise user privacy.
ContributorsGibson, Aaron (Author) / Bazzi, Rida (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2015
Description
Secure Scuttlebutt is a digital social network in which the network data is distributed among the users.<br/>This is done to secure several benefits, like offline browsing, censorship resistance, and to imitate natural social networks, but it comes with downsides, like the lack of an obvious implementation of a recommendation algorithm.<br/>This paper proposes Whuffie, an algorithm that tracks each user's reputation for having information that is interesting to a user using conditional probabilities.<br/>Some errors in the main Secure Scuttlebutt network prevent current large-scale testing of the usefulness of the algorithm, but testing on my own personal account led me to believe it a success.
ContributorsVermillion, Alexander J (Author) / Bazzi, Rida (Thesis director) / Richa, Andrea (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
DescriptionThe goal of this study is to equip administrators and instructors with a deeper understanding of the apparent cheating problem in Computer Science courses, with proposed solutions to lower academic dishonesty from the students’ perspective.
ContributorsAl Yasari, Farah (Co-author) / Alyasari, Farah (Co-author) / Tadayon-Navabi, Farideh (Thesis director) / Bazzi, Rida (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05