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ZENODO
Dataset . 2015
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2015
License: CC BY
Data sources: ZENODO
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Flowpermissions

Authors: Feng Shen; Namita Vishnubhotla; Chirag Todarka; Mohit Arora; Babu Dhandapani; Eric John Lehner; Steven Y. Ko; +1 Authors

Flowpermissions

Abstract

* Distinct Flow Graphs and Data (Using Categories) * *Distinct Flows by Malicious Category Using Full Flow Names* This graph depicts the frequency of flows appearing within each Malicious cateogry defined by the MalGenome project, and includes the popular applications we processed under the "Normal" category for comparison purposes. The frequency is defined by the number of applications within a category that use a particular flow, divided by the total number of applications in that category, and is represented by the size of the marks in the scatter plot. * *Distinct Flow Categories by Malicious Category, Level 1* This graph, similar to the one described above, depicts the frequency of flow minus one level of distinction. For example, the flow sources android.location.Location:getLatitude and android.location.Location:getLongitude are now grouped under android.location.Location, as are their corresponding sinks. * *Distinct Flow Categories by Malicious Category, Level 2* This graph, similar to the first one described above, depicts the frequency of flow minus two levels of distinction. For example, the flow sources android.location.Location:getLatitude and android.location.Location:getLongitude are now grouped under android.location, as are their corresponding sinks. * *Distinct Flow Categories by Malicious Category, Level 3* This graph, similar to the first one described above, depicts the frequency of flow minus three levels of distinction. For example, the flow sources android.location.Location:getLatitude and android.location.Location:getLongitude are now grouped under android, as are their corresponding sinks. * Distinct Flow Graphs and Data (General Malware Vs. Normal) * *Distinct Flows Using Full Flow Names* This graph depicts the frequency of flows appearing within each Malicious cateogry defined by the MalGenome project, and includes the popular applications we processed under the "Normal" category for comparison purposes. The frequency is defined by the number of applications within a category that use a particular flow, divided by the total number of applications in that category, and is represented by the size of the marks in the scatter plot. * *Distinct Flows Cateogories, Level 1* This graph, similar to the first graph, depicts the frequency of flow minus one level of distinction. For example, the flow sources android.location.Location:getLatitude and android.location.Location:getLongitude are now grouped under android.location.Location, as are their corresponding sinks. * *Distinct Flows Cateogories, Level 2* This graph, similar to the first graph, depicts the frequency of flow minus one level of distinction. For example, the flow sources android.location.Location:getLatitude and android.location.Location:getLongitude are now grouped under android.location, as are their corresponding sinks. * *Distinct Flows Categories, Level 3* This graph, similar to the first graph, depicts the frequency of flow minus one level of distinction. For example, the flow sources android.location.Location:getLatitude and android.location.Location:getLongitude are now grouped under android, as are their corresponding sinks. Attribute info 1. Category 2. Flow Source 3. Flow Sink 4. Distinct APK count 5. Total Distinct APKs

Keywords

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  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 9
    download downloads 7
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    downloads
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visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
9
7