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Given how smart today’s malware authors have become through employing highly sophisticated techniques, it is only logical that methods be developed to combat the most potent threats, particularly where the malware is stealthy and makes indicators of compromise (IOC) difficult to detect. After the analysis is completed, the output can be employed to detect and then counteract the attack. The goal of this work is to propose a machine learning approach to improve malware detection by combining the strengths of both supervised and unsupervised machine learning techniques. This study is essential as malware has certainly become ubiquitous as cyber-criminals use it to attack systems in cyberspace. Malware analysis is required to reveal hidden IOC, to comprehend the attacker’s goal and the severity of the damage and to find vulnerabilities within the system.

This research proposes a hybrid approach for dynamic and static malware analysis that combines unsupervised and supervised machine learning algorithms and goes on to show how Malware exploiting steganography can be exposed.

The tactics used by malware developers to circumvent detection are becoming more advanced with steganography becoming a popular technique applied in obfuscation to evade mechanisms for detection. Malware analysis continues to call for continuous improvement of existing techniques. State-of-the-art approaches applying machine learning have become increasingly popular with highly promising results.

Cyber security researchers globally are grappling with devising innovative strategies to identify and defend against the threat of extremely sophisticated malware attacks on key infrastructure containing sensitive data. The process of detecting the presence of malware requires expertise in malware analysis. Applying intelligent methods to this process can aid practitioners in identifying malware’s behaviour and features. This is especially expedient where the malware is stealthy, hiding IOC.

The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies.

The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method.

The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach.

One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets.

The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City.

The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice.

The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.

Existence of working poverty reduces the effectiveness of the strategy of “increasing employment to reduce poverty”. Developed countries are already concerned about it but insufficient attention has been made by developing countries. Focusing on developing countries this study identifies (1) the effects of trade openness (TO) on working poverty and (2) whether the working poverty trap exists or not in developing countries. Both objectives are also analyzed for three subsamples of low income, lower-middle income and upper-middle income developing countries.

Panel data for 98 developing countries over the period of 2000–2016 have been collected for the study. Fixed effect and GMM methods are applied for static and dynamic analysis, respectively.

The study finds that TO significantly reduces working poverty rate (WPR) (mainly driven up by upper-middle income developing countries). The positive association between WPR with its previous year's rate proves the existence of working poverty trap.

The study's outcome is subject to selected time, countries and methods. Future research should use more improve methods and should identify the channels through which TO could affect working poverty.

Middle income and upper-middle income developing countries should increase TO to reduce the working poverty. Low income developing countries that have the highest working poverty should search the way to derive beneficial effects of trade on working poverty.

Working poverty is not only a developed country issue rather it is a global phenomenon. Hence, it is expected that the study will raise the social consciousness about this phenomenon in developing countries too.

The study fulfills the gaps of identifying the effects of TO on working poverty and existence of in-work poverty trap in developing countries.

The aim of this research paper is to design a motor holder in order to minimize the weight of the motor and to reduce its vibrations causing noise pollution.

To meet the requirements of the purpose the use of cellular lattice structures is ideal. Lattice structures ensure both low mass and high strength. Moreover, their absorption properties are relatively interesting concerning the attenuation of vibrations.

The result of this paper shows that lattice structure can answer to the need of different fields such as aeronautics in the design of lightweight structures which are strong with a low mass. Indeed, the weight of the final structure of the holder is 0.92 g and its safety factor is 5.1 which met the requirements.

The limitations of the research paper were the RAM capacity of the computer.

To minimize the weight of the holder in a patroller or a plane is to reduce the consumption of fuel. Moreover one of the reasons of optimizing the vibrations is to reduce noise pollution.

This paper is directed to students, designers who want to know more about the use of lattice structure and more precisely honeycomb sandwich structure.

The government of Korea considers the promotion of Free Trade Agreements (FTA) as necessary to develop its economy into an open trading nation. As for the countries with which the Korean government is actively investigating possible FTAs, there are Japan, Singapore, the Association of South East Asian Nations (ASEAN,) and Mexico. For the time-being, the FTA with Japan seems to be a critical one in practicing Korea s FTA policy. Recently, Korean industries show negative positions against a Korea-Japan FTA, with strong opposition from the labor union insisting that it is evident that Korea will sustain damages in the short-run and the dynamic (long-term) benefits are still ambiguous and uncertain. Regardless of whether their argument is correct or not, it will be difficult for Korea to conclude the FTA with Japan unless there is concrete confidence of balanced economic gains through the FTA between the two countries.

In the early 1930s, Nicholas Kaldor could be classified as an Austrian economist. The author reconstructs the intertwined paths of Kaldor and Friedrich A. Hayek to disequilibrium economics through the theoretical deficiencies exposed by the Austrian theory of capital and its consequences on equilibrium analysis.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The integration of capital theory into a business cycle theory by the Austrians and its shortcomings – e.g. criticized by Piero Sraffa and Gunnar Myrdal – called attention to the limitation of the theoretical apparatus of equilibrium analysis in dynamic contexts. This was a central element to Kaldor’s emancipation in 1934 and his subsequent conversion to John Maynard Keynes’ The General Theory of Employment, Interest, and Money (1936). In addition, it was pivotal to Hayek’s reformulation of equilibrium as a social coordination problem in “Economics and Knowledge” (1937). It also had implications for Kaldor’s mature developments, such as the construction of the post-Keynesian models of growth and distribution, the Cambridge capital controversy, and his critique of neoclassical equilibrium economics.

The close encounter between Kaldor and Hayek in the early 1930s, the developments during that decade and its mature consequences are unexplored in the secondary literature. The author attempts to construct a coherent historical narrative that integrates many intertwined elements and personas (e.g. the reception of Knut Wicksell in the English-speaking world; Piero Sraffa’s critique of Hayek; Gunnar Myrdal’s critique of Wicksell, Hayek, and Keynes; the Hayek-Knight-Kaldor debate; the Kaldor-Hayek debate, etc.) that were not connected until now by previous commentators.

The aim of this study was to investigate how the productivity spillover effects of foreign direct investment (FDI) in the Latin American economies are manifested. Specifically, the paper sought to identify the role of foreign presence and government intervention through an industrial policy on total factor productivity in Latin American countries.

The analyses in this study were performed in two stages. The first step consisted of decomposing the total factor productivity growth, in technical efficiency change (EC) and technological efficiency change (TC), using the Malmquist Productivity Index (MPI). In the second stage of this research, the specific EC and TC indexes of each country – obtained with the MPI – are used alternately as a dependent variable in a regression analysis with dynamic panel data. The variables were collected from the World Development Indicators database, available in the World Bank database, and cover the period from 1994 to 2014.

FDI has contributed to not only the catch-up effect – i.e. to continuous improvements in production processes and products using the same technology – but also in terms of productivity, due to technological innovations and the frontier-shift effect. Industrial policies, such as the FDI attraction, when established in isolation, are not able to contribute to the generation of productivity spillovers, measured in terms of technical and technological efficiency.

The limitation of the present study lies precisely in the nature of data aggregation that actually limits a more in-depth analysis of the object of study. The available data set for the analysis in this study does not provide a detailed examination of the domestic corporations’ characteristics, the sectors and motivations of multinational corporations of each one of the analyzed economies.

The outcomes of this research present several practical implications, as its development is based on the recognition that productivity is essential for the development of a country. It remains the Achilles' heel of the Latin American economies, and therefore, it is necessary and essential to move toward a change in its development model and, more specifically, in its industrial policies, with a focus on investment and innovation to achieve the new sustainable development objectives. Among the main challenges presented to governments in the region is the emergence of policies aimed at establishing a sustainable development path through industrial policies capable of accelerating productivity growth.

The evidence presented in this study highlights the importance of better understanding the real effects of state intervention through the use of industrial policy instruments and how they affect foreigners’ investment decisions, as the lack of clear industrial policy orientation that is systematically integrated with MNEs’ operations may result in economic development opportunities below the ideal.

The research results corroborate the foundations of spillover effects theory and with the recognition that the intensity of the effect of the foreign participation on the performance of economies will depend on the absorption capacity of host economies.

This paper aims to describe an effort to provide for a robust and secure software development paradigm intended to support DevSecOps in a naval aviation enterprise (NAE) software support activity (SSA), with said paradigm supporting strong traceability and provability concerning the SSA’s output product, known as an operational flight program (OFP). Through a secure development environment (SDE), each critical software development function performed on said OFP during its development has a corresponding record represented on a blockchain.

An SDE is implemented as a virtual machine or container incorporating software development tools that are modified to support blockchain transactions. Each critical software development function, e.g. editing, compiling, linking, generates a blockchain transaction message with associated information embedded in the output of a said function that, together, can be used to prove integrity and support traceability. An attestation process is used to provide proof that the toolchain containing SDE is not subject to unauthorized modification at the time said critical function is performed.

Blockchain methods are shown to be a viable approach for supporting exhaustive traceability and strong provability of development system integrity for mission-critical software produced by an NAE SSA for NAE embedded systems software.

A blockchain-based authentication approach that could be implemented at the OFP point-of-load would provide for fine-grain authentication of all OFP software components, with each component or module having its own proof-of-integrity (including the integrity of the used development tools) over its entire development history.

Many SSAs have established control procedures for development such as check-out/check-in. This does not prove the SSA output software is secure. For one thing, a build system does not necessarily enforce procedures in a way that is determinable from the output. Furthermore, the SSA toolchain itself could be attacked. The approach described in this paper enforces security policy and embeds information into the output of every development function that can be cross-referenced to blockchain transaction records for provability and traceability that only trusted tools, free from unauthorized modifications, are used in software development. A key original concept of this approach is that it treats assigned developer time as a transferable digital currency.

The purpose of this paper is to present the result of calculations that were performed to estimate the structural weight of the passenger aircraft using novel technological solution. Mass penalty resulting from the installation of the fuselage boundary layer ingestion device was needed in the CENTRELINE project to be able to estimate the real benefits of the applied technology.

This paper focusses on the finite element analysis (FEA) of the fuselage and wing primary load-carrying structures. Masses obtained in these analyses were used as an input for the total structural mass calculation based on semi-empirical equations.

Combining FEA with semi-empirical equations makes it possible to estimate the mass of structures at an early technology readiness level and gives the possibility of obtaining more accurate results than those obtained using only empirical formulas. The applied methodology allows estimating the mass in case of using unusual structural solutions, which are not covered by formulas available in the literature.

Accurate structural mass estimation is possible at an earlier design stage of the project based on the presented methodology, which allows for easier and less costly changes in designed aircrafts.

The presented methodology is an original method of mass estimation based on a two-track approach. The analytical formulas available in the literature have worked well for aeroplanes of conventional design, but thanks to the connection with FEA presented in this paper, it is possible to estimate the structure mass of aeroplanes using unconventional technological solutions.