Securing android applications via edge assistant third-party library detection

2019 ◽  
Vol 80 ◽  
pp. 257-272 ◽  
Author(s):  
Zhushou Tang ◽  
Minhui Xue ◽  
Guozhu Meng ◽  
Chengguo Ying ◽  
Yugeng Liu ◽  
...  
Keyword(s):  
Third Party ◽  
Android Applications

LibSift: Automated Detection of Third-Party Libraries in Android Applications

2016 ◽  
Author(s):  
Charlie Soh ◽  
Hee Beng Kuan Tan ◽  
Yauhen Leanidavich Arnatovich ◽  
Annamalai Narayanan ◽  
Lipo Wang
Keyword(s):  
Automated Detection ◽  
Third Party ◽  
Android Applications

A Survey on Android Malwares and Defense Techniques

2020 ◽  
Vol 17 (4) ◽  
pp. 1557-1565
Author(s):  
Abdesselam Beroual ◽  
Imad Fakhri Al-Shaikhli
Keyword(s):  
Point Of View ◽  
Third Party ◽  
Android Security ◽  
Market Place ◽  
Privacy And Security ◽  
Security Issues ◽  
Android Os ◽  
Android Applications ◽  
Application Developers ◽  
Google Play

Since the last few years, Android is by far the most widely utilized as an operating system for mobile devices, and this is accompanied by the development in terms of number and variety of different Android applications. Android offers a centralized market place maintained by Google named “Google Play Store,” where official and third party application developers can submit their Android applications to make them available for users. The high popularity of Android OS and its market place is becoming a worthy target by hackers and attackers to violate users’ privacy and security. Malwares were also growing in parallel with Android applications growth. It is necessary as a first step to have a solid understanding of malwares’ characteristics to help preventing potential harmful consequences. Whithin this paper, we initially present the general overview for Android OS architecture with application structure, then we highlight the popular Android security issues and focus on the existing solutions to detect and prevent Android malwares, finally, we present our point of view and suggestion for future works on the best solution to overcome the Android malwares.

scholarly journals Deep Learning Based Static Analysis of Malwares in Android Applications

2021 ◽  
Author(s):  
Nivedha K ◽  
Indra Gandhi K ◽  
Shibi S ◽  
Nithesh V ◽  
Ashwin M
Keyword(s):  
Operating System ◽  
Deep Learning ◽  
Open Source ◽  
Text Messages ◽  
Third Party ◽  
Android Application ◽  
Android Malware ◽  
Android Apps ◽  
User Data ◽  
Android Applications

Android is a widely distributed mobile operating system developed especially for mobile devices with touch screens. It is an open source, Google-distributed Linux-based mobile operating system. Since Android is open source, it enables Android devices to be targeted effectively by malware developers. Third-party markets do not search for malicious applications in their databases, so installing Android Application Packages (APKs) from these uncontrolled market places is often risky. Without user’s notice, these malware infected applications gain access to private user data, send text messages that costs the user, or hide malware apk file inside another application. The total number of new samples of Android malware amounted to 482,579 per month as of March 2020. In this paper deep learning approach that focuses on malware detection in android apps to protect data on user devices. We use different static features that are present in an Android application for the implementation of the proposed system. The system extracts various static features and gives them to the classifier for deep learning and shows the results. This proposed system will assist users in checking applications that are not downloaded from the official market.

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