Detection of clone scammers in Android markets using IoT‐based edge computing. Issue 6 (11th November 2019)
- Record Type:
- Journal Article
- Title:
- Detection of clone scammers in Android markets using IoT‐based edge computing. Issue 6 (11th November 2019)
- Main Title:
- Detection of clone scammers in Android markets using IoT‐based edge computing
- Authors:
- Ullah, Farhan
Naeem, Hamad
Naeem, Muhammad Rashid
Jabbar, Sohail
Khalid, Shehazad
Al‐Turjman, Fadi
Abuarqoub, Abdelrahman - Abstract:
- Abstract: Pirated application developers find an alternate way to publish pirated versions of the same Android mobile applications (apps) on different Android markets. Therefore, a centralized, automated scrutiny system among multiple app stores is inevitable to prevent publishing pirated or cloned version of these Android applications. In this paper, we proposed an Android clone detection system for Internet of things (IoT) (Droid‐IoT) devices. First, the proposed system receives an original Android application package (APK) file along with possible candidate cloned APKs over the cloud network. The system uses an apkExtractor tool to extract Dalvik Executable (DEX) files for each subject program. The Jdex decompiler is used to extract Java source files from DEXs. Then, the bag‐of‐word model is used to extract tokenized features from source files. Further, the weighting filters are used to zoom the importance of each token. Moreover, Synthetic Minority Oversampling is applied to retrieve balanced features for better training of data. Finally, TensorFlow with Keras deep learning model is designed to predict clones in Android applications. The experimental results have shown that Droid‐IoT can successfully detect cloned apps with an accuracy of up to 96%. The primary purpose of this system is to prevent the publishing of pirated apps among different app stores under different pirated names. Abstract : App cloning is a process of creating similar apps availablein any app storeAbstract: Pirated application developers find an alternate way to publish pirated versions of the same Android mobile applications (apps) on different Android markets. Therefore, a centralized, automated scrutiny system among multiple app stores is inevitable to prevent publishing pirated or cloned version of these Android applications. In this paper, we proposed an Android clone detection system for Internet of things (IoT) (Droid‐IoT) devices. First, the proposed system receives an original Android application package (APK) file along with possible candidate cloned APKs over the cloud network. The system uses an apkExtractor tool to extract Dalvik Executable (DEX) files for each subject program. The Jdex decompiler is used to extract Java source files from DEXs. Then, the bag‐of‐word model is used to extract tokenized features from source files. Further, the weighting filters are used to zoom the importance of each token. Moreover, Synthetic Minority Oversampling is applied to retrieve balanced features for better training of data. Finally, TensorFlow with Keras deep learning model is designed to predict clones in Android applications. The experimental results have shown that Droid‐IoT can successfully detect cloned apps with an accuracy of up to 96%. The primary purpose of this system is to prevent the publishing of pirated apps among different app stores under different pirated names. Abstract : App cloning is a process of creating similar apps availablein any app store by different developer name and therefore, a centralized, automated scrutiny system is required to prevent publishing pirated or cloned version of android applications. This paper presented an android clone scammers detection Android clone detection system for Internet of things (IoT)(Droid‐IoT) devices. The primary purpose of this system is to prevent the publishing of pirated apps among different app stores under different pirated names will send through email. … (more)
- Is Part Of:
- Transactions on emerging telecommunications technologies. Volume 33:Issue 6(2022)
- Journal:
- Transactions on emerging telecommunications technologies
- Issue:
- Volume 33:Issue 6(2022)
- Issue Display:
- Volume 33, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 33
- Issue:
- 6
- Issue Sort Value:
- 2022-0033-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2019-11-11
- Subjects:
- Telecommunication -- Periodicals
384.05 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1541-8251 ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2161-3915 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/ett.3791 ↗
- Languages:
- English
- ISSNs:
- 2161-5748
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22071.xml