A graph-based model for malware detection and classification using system-call groups

In this paper we present a graph-based model that, utilizing relations between groups of System-calls, detects whether an unknown software sample is malicious or benign, and classifies a malicious software to one of a set of known malware families. More precisely, we utilize the System-call Dependency Graphs (or, for short, ScD-graphs), obtained by traces captured through dynamic taint analysis. We design our model to be resistant against strong mutations applying our detection and classification techniques on a weighted directed graph, namely Group Relation Graph, or Gr-graph for short, resulting from ScD-graph after grouping disjoint subsets of its vertices. For the detection process, we propose the \(\Delta \)-similarity metric, and for the process of classification, we propose the SaMe-similarity and NP-similarity metrics consisting the SaMe-NP similarity. Finally, we evaluate our model for malware detection and classification showing its potentials against malicious software measuring its detection rates and classification accuracy.     

An empirical study on green practices of mobile phone users

Given the market’s saturation with smartphones and the increased power needs that these have as compared with older feature phones, the users’ green practices and behavior is emerging as an important research topic. The environmental aspects and general awareness issues are not addressed in this study; however, the limited battery life of smartphones is a decisive factor that shapes the users’ behavior, practices and preferences. As such, the users need to follow green practices and carefully assess the energy related characteristics (speed, screen size, weight, and price) that they value the most in a smartphone, to maximize their experience. Based on our previous work that gathered relevant data from 313 users, we extended the analysis in order to examine the user battery life and charging practices, buying habits, green practices and preferences. To that end, we used quantitative statistics and Fuzzy Decision Tree analysis to propose relevant Fuzzy Decision Rules that can classify the results and profile the users.     

Dual-phase polyphenylene oxide membranes with copolyimide branched modifiers

Poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) membranes are attractive due to high permeability for gases; however, the selectivity of these membranes is insufficient. In this work, the gas selectivity was improved without significant loss of the permeability. For this purpose, PPO was modified via incorporation of the branched copolyimide filler–grafted copolyimide (PI-g-PMMA) with polymethyl methacrylate (PMMA) side chains. Two series of mixed self-supporting PPO/PI-g-PMMA films (with variation of the filler content) were prepared and studied as gas separation membranes. The length of the polymide (PI) chain and the density of PMMA grafting were the same in both series, however, in one series the grafted chains contained 50 MMA units, and in the other 150 units. The intermolecular interactions between the PPO matrix and the PI-g-PMMA fillers were investigated using viscometry, infrared (IR) spectroscopy, and scanning electron microscopy. The compatibility of the polymer components is limited; however, for both series, the contents of the respective filler are found, which ensures phase segregation only in a microscale. Therefore, the mechanical properties of the films allow their use as gas separation membranes. It is shown that the degree of the segregation as well as the mechanical and gas transport properties of the membranes depend on the length of the PMMA chains, and the membranes with filler-containing shorter branches (50 MMA units) show better selectivity.     

Perovskite type lanthanum manganite: Morpho-structural analysis and electrical investigations

Perovskite-type oxides of LaMnO_3 were synthesized by means of the sol-gel method, in the presence of citric acid as gelling agent. The precursors used were Mn(NO_3)_2·H_2O, La_2O_3, and NaOH,mixed in the stoichiometric ratio to obtain perovskite materials. The obtained gel was heat-treated at 400, 600 and 800 ℃ respectively, for 6 h. X-ray diffraction and FT-IR spectroscopy were used to analyze the phase transformation as a function of temperature, and the Rietveld refinement was used in order to characterize the materials obtained structurally. The average crystallite size of the products was calculated from XRD data and the average particle size was measured from the TEM micrographs. At 600 ℃, the synthesized compound is well-crystallized, showcases a perovskite structure(Pm-3m space group), and exhibits uniform and homogeneous hexagonally-shaped particles, with sizes in the 20-50 nm range.Complex impedance measurements in the 20-2 × 10~6 Hz frequency range were carried out at different temperatures(26-115 ℃), and the electrical conduction mechanism is discussed.     

Simple model of the optical characteristics of bubbles and sediments in seawater of the surf zone

The development of a simple model of the seawater inherent optical properties (IOPs) associated with bubbles and sediments would represent a great advance in surf zone optics. We present one solution for this problem using a combination of geometrical optics and Fraunhofer diffraction. An analytic model of the IOPs of bubbles and sediments (the extinction and absorption coefficients, and phase function) is developed in terms of the moments of the particle size distribution and the complex refractive index of particles.     

Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive Maps

Computational Economics - One of the most important environmental problems of our era is Global Warming (GW), which derives its roots mainly from anthropogenic activities and is expected to cause...     

Programs with lists are counter automata

We address the problem of verifying programs manipulating one-selector linked data structures. We propose and study in detail an application of counter automata as an accurate abstract model for this problem. We let control states of the counter automata correspond to abstract heap graphs where list segments without sharing are collapsed, and use counters to keep track of the number of elements in these segments. As a significant theoretical result, we show that the obtained counter automata are bisimilar to the original programs. Moreover, from a practical point of view, our translation allows one to apply efficient automatic analysis techniques and tools developed for counter automata (integer programs) in order to verify both safety as well as termination of list-manipulating programs. As another theoretical contribution, we prove that if the control of the generated counter automata does not contain nested loops (i.e., these automata are flat), both safety and termination are decidable for the original programs. Subsequently, we generalise our counter-automata-based model to keep track of ordering properties over lists storing ordered data. Finally, we show effectiveness of our approach by verifying automatically safety as well as termination of several sorting programs.     

Context-adaptive pre-processing scheme for robust speech recognition in fast-varying noise environment

Based on the observation that dissimilar speech enhancement algorithms perform differently for different types of interference and noise conditions, we propose a context-adaptive speech pre-processing scheme, which performs adaptive selection of the most advantageous speech enhancement algorithm for each condition. The selection process is based on an unsupervised clustering of the acoustic feature space and a subsequent mapping function that identifies the most appropriate speech enhancement channel for each audio input, corresponding to unknown environmental conditions. Experiments performed on the MoveOn motorcycle speech and noise database validate the practical value of the proposed scheme for speech enhancement and demonstrate a significant improvement in terms of speech recognition accuracy, when compared to the one of the best performing individual speech enhancement algorithm. This is expressed as accuracy gain of 3.3% in terms of word recognition rate. The advance offered in the present work reaches beyond the specifics of the present application, and can be beneficial to spoken interfaces operating in fast-varying noise environments.     

Hierarchical adaptive nanostructured PVD coatings for extreme tribological applications: the quest for nonequilibrium states and emergent behavior

Adaptive wear-resistant coatings produced by physical vapor deposition (PVD) are a relatively new generation of coatings which are attracting attention in the development of nanostructured materials for extreme tribological applications. An excellent example of such extreme operating conditions is high performance machining of hard-to-cut materials. The adaptive characteristics of such coatings develop fully during interaction with the severe environment. Modern adaptive coatings could be regarded as hierarchical surface-engineered nanostructural materials. They exhibit dynamic hierarchy on two major structural scales: (a) nanoscale surface layers of protective tribofilms generated during friction and (b) an underlying nano/microscaled layer. The tribofilms are responsible for some critical nanoscale effects that strongly impact the wear resistance of adaptive coatings. A new direction in nanomaterial research is discussed: compositional and microstructural optimization of the dynamically regenerating nanoscaled tribofilms on the surface of the adaptive coatings during friction. In this review we demonstrate the correlation between the microstructure, physical, chemical and micromechanical properties of hard coatings in their dynamic interaction (adaptation) with environment and the involvement of complex natural processes associated with self-organization during friction. Major physical, chemical and mechanical characteristics of the adaptive coating, which play a significant role in its operating properties, such as enhanced mass transfer, and the ability of the layer to provide dissipation and accumulation of frictional energy during operation are presented as well. Strategies for adaptive nanostructural coating design that enhance beneficial natural processes are outlined. The coatings exhibit emergent behavior during operation when their improved features work as a whole. In this way, as higher-ordered systems, they achieve multifunctionality and high wear resistance under extreme tribological conditions.     

Simultaneous in situ reflectance and probe beam deflection measurements at solid electrode-aqueous electrolyte interfaces

A method is herein described for performing simultaneous in situ normal incidence reflectance spectroscopy (DeltaR/R, lambda = 633 nm) and probe beam deflection (PBD) measurements at solid electrodes in aqueous electrolytes, while scanning the potential linearly between two prescribed limits. Results obtained for Au in 0.1 M HClO4 and for Pt in both 0.1 M HClO4 and 0.1 M NaOH were found to be in excellent agreement with those reported in the literature for each individual spectroelectrochemical technique under otherwise similar conditions. Data collected for Pt electrodes in CO-saturated 0.1 M HClO4 revealed rather sudden changes in both DeltaR/R and PBD signals in the voltammetric region where the characteristic sharp peak associated with the oxidation of adsorbed CO occurs. This behavior was ascribed, respectively, to oxide formation (DeltaR/R) and to changes in the electrolyte composition in region neighboring the electrode, involving predominantly the acid concentration (PBD). In contrast, CO oxidation on Pt in 0.1 M NaOH yielded a PBD response consistent with formation of solution-phase carbonate via the reaction of the product, CO2, with hydroxyl ion. The exquisite sensitivity of DeltaR/R and PBD to interfacial phenomena was further illustrated using a monolayer of hemin irreversibly adsorbed on glassy carbon surfaces in 0.1 M Na2B4O7 (pH approximately 9.2). For this system, DeltaR/R was found to be proportional to the relative fractions of hemin and its reduced counterpart, while the PBD signal could be correlated with corresponding variations in the electrolyte concentration induced by the surface-bound redox process.