• ETRI Journal
• /
• v.42 no.2
• /
• pp.205-216
• /
• 2020

An arbiter physical unclonable function (APUF) has exponential challenge-response pairs and is easy to implement on field-programmable gate arrays (FPGAs). However, modeling attacks based on machine learning have become a serious threat to APUFs. Although the modeling-attack resistance of an MA-APUF has been improved considerably by architecture modifications, the response generation method of an MA-APUF results in low uniqueness. In this study, we demonstrate three design problems regarding the low uniqueness that APUF-based strong PUFs may exhibit, and we present several foundational principles to improve the uniqueness of APUF-based strong PUFs. In particular, an improved MA-APUF design is implemented in an FPGA and evaluated using a well-established experimental setup. Two types of evaluation metrics are used for evaluation and comparison. Furthermore, evolution strategies, logistic regression, and K-junta functions are used to evaluate the security of our design. The experiment results reveal that the uniqueness of our improved MA-APUF is 81.29% (compared with that of the MA-APUF, 13.12%), and the prediction rate is approximately 56% (compared with that of the MA-APUF (60%-80%).

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.16 no.10
• /
• pp.969-976
• /
• 2004

Building energy saving is one of the most important issues in these days. Energy saving control strategies should be developed properly to achieve the saving. One of such area we could apply is the HVAC (Heating, Ventilation and Air-Conditioning) system. Through the optimal control algorithm for building energy management system (EMS), you can not only save the cost of building energy, but also protect HVAC system components against the unexpected condition. In order to verify the effectiveness of building energy saving, field test was accomplished for several months at 'A' building. And to get the measured data, remote control was used. If the remote control is used in BAS (Building Automation System), control and monitoring can be done for all of the building systems, such as HVAC, power, lighting, security and fire-alarm etc. anywhere any time. Using the remote control, Control and monitoring is possible for the testing system without going there. As the results of field test, we could reduce $5{\sim}10\%$ of the building energy cost.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.97-104
• /
• 2021

The key challenges and problematic aspects of the formation of intellectually and innovation-oriented strategies of regional entities at the present stage of their development are considered. The main tasks that arise in the process of strategizing the potential-forming development of regional economic systems in the context of digitalization are identified. The list of key organizational and economic directions of strategic character of providing intellectual and innovative development of regional economic systems is formed, which includes clustering of centers of high-tech development of regions, creation of creative hubs, development of knowledge infrastructure and improvement of interregional cooperation; a brief description of each of the presented strategic organizational and economic directions is given. Based on the analysis, the key strategic guidelines for the development of regional economic entities in the context of digitalization under the influence of potential-forming determinants, which form the content basis for further processes of strategizing qualitative aspects of development of specific regional entities.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12spc
• /
• pp.556-564
• /
• 2021

Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.

• Convergence Security Journal
• /
• v.18 no.2
• /
• pp.41-47
• /
• 2018

Theorists of war have often used Clausewitz's trinity theory as a framework for analyzing war strategies and histories. Heretofore, studies on cyber warfare have focused primarily on laws, policies, structuring organizations, manpower, and training pertaining to preparing the cyberspace for war. Currently, studies highlighting the comparative characteristics of war in cyberspace, how it differs from conventional warfare, and analytical frameworks for understanding war in cyberspace are rare. Using Clausewitz's trinity theory, this paper interprets the essence of war from the perspectives of (1) Intellect, (2) Bravery, and (3) Passion, to propose an analytical model for understanding war in cyberspace, one that factors in the intrinsic qualities and characteristics of cyberspace under spatial and temporal constraints. Furthermore, this paper applies the aforementioned analytical model to the Iraq War and concludes with a theoretical illustration that cyber warfare played a significant role in winning the war.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.169-172
• /
• 2021

The article discusses the results of a quantitative analysis of open educational resources in the field of information technology. Study is based on a study of the content of ten platforms that provide access to open resources (OPs). To achieve this goal, we used the following methods: theoretical analysis and generalization of Internet sources to determine the popularity of educational platforms and resources on them; quantitative data analysis to determine the relative proportion of IT courses in various parameters: the relative weight of courses in the IT field in general and on each platform in particular, the language of instruction, the quantitative content by thematic areas. The following platforms providing access to open educational resources were subjected to quantitative analysis: Coursera, Edx, Udemy, MIT OpenCourseWare, OpenLearn, Intuit, Prometheus, UoPeople, Open Learning Initiative, Maidan Open University.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.31-40
• /
• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.286-293
• /
• 2021

Recently, the quick development rate of apps in the Android platform has led to an accelerated increment in creating malware applications by cyber attackers. Numerous Android malware detection tools have utilized conventional signature-based approaches to detect malware apps. However, these conventional strategies can't identify the latest apps on whether applications are malware or not. Many new malware apps are periodically discovered but not all malware Apps can be accurately detected. Hence, there is a need to propose intelligent approaches that are able to detect the newly developed Android malware applications. In this study, Radial Basis Function (RBF) networks are trained using known Android applications and then used to detect the latest and new Android malware applications. Initially, the optimal permission features of Android apps are selected using Information Gain Ratio (IGR). Appropriately, the features selected by IGR are utilized to train the RBF networks in order to detect effectively the new Android malware apps. The empirical results showed that RBF achieved the best detection accuracy (97.20%) among other common machine learning techniques. Furthermore, RBF accomplished the best detection results in most of the other measures.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.199-208
• /
• 2022

The world health organization classified the emerging coronavirus (known as Covid-19) as a pandemic after confirming the extent of spread and scale. As a matter of fact, outbreaks of similar scale or even worse have been witnessed throughout history. Thus, the development of prevention strategies exists to protect against such calamaties. One of the widely proven measures that controls the spread of any contagious diseases is social distancing. As a result, this paper will demonstrate the concept of an application "Be Aware" on enabling the implementation of this preventive measure. In particular "Be aware" evaluates the extent of congestion in public places using current time data. The proposed project will use Global Positioning System (GPS), and Application Programming Interface (API), to ensure information accuracy, and the API use Crowdsourcing to collect Real-Time Data (RTD) from the selected places. One line

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.399-405
• /
• 2022

This article is devoted to the consideration of the image strategies of higher education on the example of a comparison of Ukrainian and foreign experience. The relevance of the chosen topic is as follows. Today, educational institutions need to position, shape and elevate their image. PR helps to solve all these tasks, performing a function that is so necessary for establishing mutual understanding as communication management. The following tasks are solved in the article: originality of definitions was investigated; revealed PR and related concepts; analyzed the role of PR in the information promotion of universities; determined the specifics of information promotion, due to temporary conditions and regional development; considered image materials of Ukrainian and foreign universities; disclosed the specifics of the information promotion of the objects under study; analyzed.