Comparing Android Applications to Find Copying

The Android smartphone operating system includes a Java virtual machine that enables rapid development and deployment of a wide variety of applications. The open nature of the platform means that reverse engineering of applications is relatively easy, and many developers are concerned as applications similar to their own show up in the Android marketplace and want to know if these applications are pirated. Fortunately, the same characteristics that make an Android application easy to reverse engineer and copy also provide opportunities for Android developers to compare downloaded applications to their own. This paper describes the process for comparing a developer’s application with a downloaded application and defines an identifiability metric to quantify the degree to which an application can be identified by its bytecode

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on four popular obfuscation approaches: identifier renaming, string encryption, Java reflection, and packing. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, malware authors use string encryption more frequently, and more apps on third-party markets than Google Play are packed. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction

Methodological Flaws in Cognitive Animat Research

In the field of convergence between research in autonomous machine construction and biological systems understanding it is usually argued that building robots for research on auton- omy by replicating extant animals is a valuable strategy for engineering autonomous intelligent systems. In this paper we will address the very issue of animat construction, the ratio- nale behind this, their current implementations and the value they are producing. It will be shown that current activity, as it is done today, is deeply flawed and useless as research in the science and engineering of autonomy

Comparison of Forensic Tool Results on Android Smartphone Backup Files Using NIST Method

Smartphone technology currently developing not only has a positive impact but can also have a negative impact if it is used to commit crimes which can be called cybercrime. Choosing the right forensic tools is very important when conducting an investigation. So it is necessary to research the results of the comparative analysis of the performance of forensic tools on android smartphone backup files. The National Institute of Standards and Technology (NIST) method was used in this study as a parameter and for the digital evidence obtained. The results of the extraction of the OPPO A37f android smartphone from the MOBILedit tools acquired android backup files and the analysis results from using the Magnet AXIOM tools with a data accuracy rate of 39.3% from the predetermined variables. The Oxygen Forensic Tools obtained a data accuracy rate of 28.6% from the variable that has been determined. The Belkasoft Evidence Center tools can get a data accuracy rate of 35.7% of the predetermined variables. The results of this study can be concluded that the Magnet Axiom tool has a high level of accuracy compared to the Oxygen Forensic and Belkasoft Evidence Center tools in extracting data from android smartphone backup files

Notes on your desk and in the cloud: comparing Evernote and OneNote

The article presents a comparison of Evernote digital workspace from Evernote Corp. and Microsoft OneNote digital note-taking app from Microsoft Corp

Investigating UI displacements in an Adaptive Mobile Homescreen

The authors present a system that adapts application shortcuts (apps) on the homescreen of an Android smartphone, and investigate the effect of UI displacements that are caused by the choice of adaptive model and the order of apps in the homescreen layout. They define UI displacements to be the distance that items move between adaptations, and they use this as a measure of stability. An experiment with 12 participants is performed to evaluate the impact of UI displacements on the homescreen. To make the distribution of apps in the experiment task less contrived, naturally generated data from a pilot study is used. The authors’ results show that selection time is correlated to the magnitude of the previous UI displacement. Additionally, selection time and subjective rating improve significantly when the model is easy to understand and an alphabetical order is used, conditions that increase stability. However, rank order is preferred when the model updates frequently and is less easy to understand. The authors present their approach to adapting apps on the homescreen, and initial insights into UI displacements