Android Malware Family Classification Based on Resource Consumption over Time

The vast majority of today's mobile malware targets Android devices. This has pushed the research effort in Android malware analysis in the last years. An important task of malware analysis is the classification of malware samples into known families. Static malware analysis is known to fall short against techniques that change static characteristics of the malware (e.g. code obfuscation), while dynamic analysis has proven effective against such techniques. To the best of our knowledge, the most notable work on Android malware family classification purely based on dynamic analysis is DroidScribe. With respect to DroidScribe, our approach is easier to reproduce. Our methodology only employs publicly available tools, does not require any modification to the emulated environment or Android OS, and can collect data from physical devices. The latter is a key factor, since modern mobile malware can detect the emulated environment and hide their malicious behavior. Our approach relies on resource consumption metrics available from the proc file system. Features are extracted through detrended fluctuation analysis and correlation. Finally, a SVM is employed to classify malware into families. We provide an experimental evaluation on malware samples from the Drebin dataset, where we obtain a classification accuracy of 82%, proving that our methodology achieves an accuracy comparable to that of DroidScribe. Furthermore, we make the software we developed publicly available, to ease the reproducibility of our results.Comment: Extended Versio

A New Approach for Quality Management in Pervasive Computing Environments

This paper provides an extension of MDA called Context-aware Quality Model Driven Architecture (CQ-MDA) which can be used for quality control in pervasive computing environments. The proposed CQ-MDA approach based on ContextualArchRQMM (Contextual ARCHitecture Quality Requirement MetaModel), being an extension to the MDA, allows for considering quality and resources-awareness while conducting the design process. The contributions of this paper are a meta-model for architecture quality control of context-aware applications and a model driven approach to separate architecture concerns from context and quality concerns and to configure reconfigurable software architectures of distributed systems. To demonstrate the utility of our approach, we use a videoconference system.Comment: 10 pages, 10 Figures, Oral Presentation in ECSA 201

The Reality of Measuring Human Service Programs: Results of a Survey

In the summer of 2013, Idealware created and distributed a survey to learn how human service organizations from their own mailing list are actually using technology to measure and evaluate the outcomes of their programs. The suvey looked at a general overview of outcomes measurement and program evaluation topics, from how frequently they look at data and how much time they spend doing so to what types of metrics the organizations were tracking. To further understand the realities of measuring program effectiveness, Idealware conducted a site visit and interview of three human service organizations in Portland, Maine. The results clearly show that the respondents are struggling to measure their programs