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1 – 10 of over 1000Prudence Kadebu, Robert T.R. Shoniwa, Kudakwashe Zvarevashe, Addlight Mukwazvure, Innocent Mapanga, Nyasha Fadzai Thusabantu and Tatenda Trust Gotora
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Claudia Presti, Federica De Santis and Francesca Bernini
This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of…
Abstract
Purpose
This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.
Design/methodology/approach
This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.
Findings
ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.
Originality/value
The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.
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Hazera-Tun- Nessa and Katsushi S. Imai
Existence of working poverty reduces the effectiveness of the strategy of “increasing employment to reduce poverty”. Developed countries are already concerned about it but…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Social implications
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.
Originality/value
The study fulfills the gaps of identifying the effects of TO on working poverty and existence of in-work poverty trap in developing countries.
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Nsikak P. Owoh and M. Mahinderjit Singh
The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of…
Abstract
The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of users such as their real-time location. When such information are not effectively secured, users’ privacy can be violated due to eavesdropping and information disclosure. In this paper, we demonstrated the possibility of unauthorized access to location information of a user during sensing due to the ineffective security mechanisms in most sensing applications. We analyzed 40 apps downloaded from Google Play Store and results showed a 100% success rate in traffic interception and disclosure of sensitive information of users. As a countermeasure, a security scheme which ensures encryption and authentication of sensed data using Advanced Encryption Standard 256-Galois Counter Mode was proposed. End-to-end security of location and motion data from smartphone sensors are ensured using the proposed security scheme. Security analysis of the proposed scheme showed it to be effective in protecting Android based sensor data against eavesdropping, information disclosure and data modification.
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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…
Abstract
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.
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Abstract
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Guoquan Xu, Shiwei Feng, Shucen Guo and Xiaolan Ye
China has proposed two-stage goals of carbon peaking by 2030 and carbon neutralization by 2060. The carbon emission reduction effect of the power industry, especially the thermal…
Abstract
Purpose
China has proposed two-stage goals of carbon peaking by 2030 and carbon neutralization by 2060. The carbon emission reduction effect of the power industry, especially the thermal power industry, will directly affect the progress of the goal. This paper aims to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency of the thermal power industry and proposes policy suggestions for realizing China’s carbon peak and carbon neutralization goals.
Design/methodology/approach
This paper evaluates and compares the carbon emission efficiency of the thermal power industry in 29 provinces and regions in China from 2014 to 2019 based on the three-stage slacks-based measure (SBM) of efficiency in data envelopment analysis (DEA) model of undesired output, excluding the influence of environmental factors and random errors.
Findings
Empirical results show that during the sample period, the carbon emission efficiency of China’s thermal power industry shows a fluctuating upward trend, and the carbon emission efficiency varies greatly among the provincial regions. The carbon emission efficiency of the interregional thermal power industry presents a pattern of “eastern > central > western,” which is consistent with the level of regional economic development. Environmental factors such as economic level and environmental regulation level are conducive to the improvement of carbon emission efficiency of the thermal power industry, but the proportion of thermal power generation and industrial structure is the opposite.
Originality/value
This paper adopts the three-stage SBM–DEA model of undesired output and takes CO2 as the undesired output to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency in China’s thermal power industry. The results provide a more comprehensive perspective for regional comparative evaluation and influencing factors of carbon emission efficiency in China’s thermal power industry.
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Guido Migliaccio and Andrea De Palma
This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real…
Abstract
Purpose
This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.
Design/methodology/approach
The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.
Findings
The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.
Research limitations/implications
In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.
Practical implications
Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.
Social implications
The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.
Originality/value
The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.
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