An important part of natural, and therefore effective, communication is facial motion. The android Repliee Q2 should therefore display realistic facial motion. In computer graphics animation, such motion is created by mapping human motion to the animated character. This paper proposes a method for mapping human facial motion to the android. This is done using a linear model of the android, based on blendshape models used in computer graphics. The model is derived from motion capture of the android and therefore also models the android's physical limitations. The paper shows that the blendshape method can be successfully applied to the android. Also, it is shown that a linear model is sufficient for representing android facial motion, which means control can be very straightforward. Measurements of the produced motion identify the physical limitations of the android and allow identifying the main areas for improvement of the android design. Read More»
This paper discusses the basic concepts involved in porting android to any hardware. In this paper, we discuss in detail the layered architecture of Android, the layer to which developers gain access and the working of the architecture. Here, we also discuss how Android works on any hardware and the concepts that outline the porting of Android onto any hardware. This paper discusses about the linux kernel used for Android and the Android file system made with Android images. Read More»
In this paper we apply Machine Learning (ML) techniques on static features that are extracted from Android's application files for the classification of the files. Features are extracted from Android's Java byte-code (i.e.,.dex files) and other file types such as XML-files. Our evaluation focused on classifying two types of Android applications: tools and games. Successful differentiation between games and tools is expected to provide positive indication about the ability of such methods to learn and model Android benign applications and potentially detect malware files. The results of an evaluation, performed using a test collection comprising 2,285 Android .apk files, indicate that features, extracted statically from .apk files, coupled with ML classification algorithms can provide good indication about the nature of an Android application without running the application, and may assist in detecting malicious applications. This method can be used for rapid examination of Android .apks and informing of suspicious applications. Read More»
From the end of 2007, the open-source characteristic of Android platform has been the most competitive one in the smart phone market. According to recent statistics from Gartner, Android's market share in February 2010 is 3.9%, rises to 17.2% in August in the same year, and reaches 22.7% in February 2011, which only falls behind Nokia's by 14.9%. From its skyrocketing growth rate, it can be expected that Google's Android operating system would become the dominate mobile platform. However, high market share comes with problems. For instance, in March 2011, Lookout, an information security company shows Dorid Dream will make the Android phones become the media of Bot Network. The ever-changing criminal conduct continuously challenges how well the present digital forensics could react. Data acquisition is an important part in mobile phone forensics. As the mobile forensic software becomes more mature and popular, most of them are now facing the same problem where the internal collecting tools must be installed in the mobile phones first so the data collecting could be started in turn. Whether this process is against the concept of protecting the original crime scene in forensics is questionable. A new concept called Live SD is therefore introduced in this work. It utilizes the concept of data recovery to perform physical data acquisition in Android smart phones. This data-acquisition methodology differs from the current ones in most mobile forensics software and can effectively perform the recovery of the deleted data. Read More»