AndroParse - An Android Feature Extraction Framework and Dataset

Details

Serval ID
serval:BIB_CE874B8EEF33
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Title
AndroParse - An Android Feature Extraction Framework and Dataset
Title of the conference
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Author(s)
Schmicker Robert, Breitinger Frank, Baggili Ibrahim
Publisher
Springer International Publishing
Address
Cham
ISBN
9783030054861
9783030054878
ISSN
1867-8211
1867-822X
Publication state
Published
Issued date
2019
Editor
Breitinger Frank, Baggili Ibrahim
Pages
66-88
Language
english
Abstract
Android malware has become a major challenge. As a consequence, practitioners and researchers spend a significant time analyzing Android applications (APK). A common procedure (especially for data scientists) is to extract features such as permissions, APIs or strings which can then be analyzed. Current state of the art tools have three major issues: (1) a single tool cannot extract all the significant features used by scientists and practitioners (2) Current tools are not designed to be extensible and (3) Existing parsers can be timely as they are not runtime efficient or scalable. Therefore, this work presents AndroParse which is an open-source Android parser written in Golang that currently extracts the four most common features: Permissions, APIs, Strings and Intents. AndroParse outputs JSON files as they can easily be used by most major programming languages. Constructing the parser allowed us to create an extensive feature dataset which can be accessed by our independent REST API. Our dataset currently has 67,703 benign and 46,683 malicious APK samples.
Keywords
AndroParse, Android, Malware, Dataset, Features, Framework
Create date
06/05/2021 11:01
Last modification date
06/05/2021 11:16
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