Malware Analysis and Detection on Android: The Big Challenge

The popularization of the use of mobile devices, such as smartphones and tablets, has accelerated in recent years, as these devices have experienced a reduction in cost together with an increase in functionality and services availability. In this context, due to its openness and free availability, Android operating system (OS) has become not only a major stakeholder in the market of mobile devices but has also become an attractive target for cybercriminals. In this chapter, we advocate to present some current trends and results in the Android malware analysis and detection research area. We start by briefly describing the Android’s security model, followed by a discussion of the static and dynamic malware analysis techniques in order to provide a general view of the analysis and detection process to the reader. After that, a description of a particular set of software developments, which exemplify some of the discussed techniques, is presented accompanied by a set of practical results. Finally, we draw some conclusions about the future development of the Android malware analysis area. The main contribution of this chapter is a description of the realization of static and dynamic malware analysis techniques and principles that can be automated and mapped to software system tools in order to simplify analyses. Moreover, some details about the use of machine learning algorithms for malware classifications and the use of the hooking software techniques for dynamic analysis execution are provided

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Temario Tópicos Selectos de la Computación: Introducción a la Criptografía

Temario de Curso 2012 de Introducción a la Criptografía (Temas selectos de la computació

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Relationship of Serum Levels of IL-17, IL-18, TNF-α, and Lung Function Parameters in Patients with COPD, Asthma-COPD Overlap, and Bronchial Asthma

Determination of markers of systemic inflammation is one of the important directions in the study of pathogenesis and improvement of diagnosis of chronic obstructive pulmonary disease (COPD), asthma-COPD overlap (ACO), and bronchial asthma (BA). The aim of our work was a comparative study of the features of changes in serum levels of IL-17, IL-18, and TNF-α in patients with COPD, ACO, and BA with various severity of the disease, as well as evaluation of the relationship between the level of these cytokines and lung ventilation function. A total of 147 patients with COPD (n=58), ACO (n=57), and BA (n=32) during a stable period have been examined in this study. The control group included 21 healthy nonsmokers with similar sex-age indicators. Serum levels of IL-17, IL-18, and TNF-α were determined by ELISA. The concentrations of these cytokines in the circulation in the studied patients with COPD, ACO, and BA were higher than those in healthy nonsmokers (p≤0.001). IL-17 and IL-18 levels in the blood serum were comparable in all examined patients. The mean TNF-α concentrations in the circulation in COPD and ACO were significantly higher than those in BA (p<0.001). In patients with COPD, the levels of IL-17 and TNF-α increased progressively against the background of a decrease in numerous spirometric indicators, which allows us to consider these cytokines as systemic biomarkers of disease severity. In BA, the inverse correlations between the level of IL-17 and FEV1/FVC (%) and FEV1 have been found. In patients with ACO, the increase in IL-18 levels was associated with a decrease in FEV1 and TNF-α with FEV1/FVC (%). These findings indicate that IL-17, IL-18, and TNF-α can participate in the mechanisms of systemic inflammation and the genesis of disorders of airway obstruction in COPD, AСO, and BA. An increase in the levels of IL-17 and TNF-α may be associated with impaired bronchial patency in COPD and BA. The established associations of the IL-18 concentration in the blood serum and FEV1 only in patients with ACO allow using the level of IL-18 as a potential marker of the degree of impaired airway obstruction in this disease