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

scholarly journals A Highly Efficient Neural Network Solution for Automated Detection of Pointer Meters with Different Analog Scales Operating in Different Conditions

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1104
Author(s):  
Alexey Alexeev ◽  
Georgy Kukharev ◽  
Yuri Matveev ◽  
Anton Matveev
Keyword(s):  
Neural Network ◽  
Automated Detection ◽  
Reference Points ◽  
Training Data ◽  
Third Party ◽  
Linear Network ◽  
Global Regression ◽  
Level Model ◽  
Location Detection ◽  
Common Nature

We investigate a neural network–based solution for the Automatic Meter Reading detection problem, applied to analog dial gauges. We employ a convolutional neural network with a non-linear Network in Network kernel. Presently, there is a significant interest in systems for automatic detection of analog dial gauges, particularly in the energy and household sectors, but the problem is not yet sufficiently addressed in research. Our method is a universal three-level model that takes an image as an input and outputs circular bounding areas, object classes, grids of reference points for all symbols on the front panel of the device and positions of display pointers. Since all analog pointer meters have a common nature, this multi-cascade model can serve various types of devices if its capacity is sufficient. The model is using global regression for locations of symbols, which provides resilient results even for low image quality and overlapping symbols. In this work, we do not focus on the pointer location detection since it heavily depends on the shape of the pointer. We prepare training data and benchmark the algorithm with our own framework a3net, not relying on third-party neural network solutions. The experimental results demonstrate the versatility of the proposed methods, high accuracy, and resilience of reference points detection.

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.

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
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