• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.659-667
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• 2005

A Mobile Ad Hoc Network(MANET) is a multi hop wireless network with no prepared base stations or centralized administrations, where flocks of peer systems gather and compose a network. Each node operates as a normal end system in public networks. In addition to it, a MANET node is required to work as a router to forward traffic from a source or intermediate node to others. Each node operates as a normal end system in public networks, and further a MANET node work as a router to forward traffic from a source or intermediate node to the next node via routing path. Applications of MANET are extensively wide, such as battle field or any unwired place; however, these are exposed to critical problems related to network management, node's capability, and security because of frequent and dynamic changes in network topology, absence of centralized controls, restricted usage on network resources, and vulnerability oi mobile nodes which results from the special MANET's character, shared wireless media. These problems induce MANET to be weak from security attacks from eavesdropping to DoS. To guarantee secure authentication is the main part of security service In MANET because networks without secure authentication are exposed to exterior attacks. In this paper, a multistage authentication strategy based on CGSR is proposed to guarantee that only genuine and veritable nodes participate in communications. The proposed authentication model is composed of key manager, cluster head and common nodes. The cluster head is elected from secure nodes, and key manager is elected from cluster heads. The cluster head will verify other common nodes within its cluster range in MANET. Especially, ID of each node is used on communication, which allows digital signature and blocks non repudiation. For performance evaluation, attacks against node authentication are analyzed. Based on security parameters, strategies to resolve these attacks are drawn up.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.563-577
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• 2017

Due to the Internet and computing capability, new and variant malware are discovered around 1 Million per day. Companies use dynamic analysis such as behavior analysis on virtual machines for unknown malware detection because attackers use unknown malware which is not detected by signature based AV effectively. But growing number of malware types are not only PE(Portable Executable) but also non-PE such as MS word or PDF therefore dynamic analysis must need more resources and computing powers to improve detection effectiveness. This study elicits the pre-filtering system evaluation factor to improve effective dynamic malware analysis system and presents and verifies the decision making model and the formula for solution selection using AHP(Analytics Hierarchy Process)

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.6
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• pp.27-35
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• 2005

While the current world wide network offers an incredibly rich base of information, it causes network management problem because users should have many independent IDs and passwords for accessing different sewers located in many places. In order to solve this problem users have employed single circle of trust(COT) ID management system, but it is still not sufficient for clearing the problem because the coming ubiquitous network computing environment will be integrated and complex networks combined with wired and wireless network devices. The purpose of this paper is to describe the employment and evaluation of federated ID interoperability method for solving the problem. The use of the proposed model can be a solution for solving network management problem in the age of mobile computing environment as well as wired network computing environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.35-45
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• 2011

The Salsa20/12 stream cipher selected for the final eSTREAM portfolio has a better performance than software implementation of AES using an 8-bit microprocessor with restricted memory space, In the theoretical approach, the evaluation of exploitable timing vulnerability was 'none' and the complexity of side-channel analysis was 'low', but there is no literature of the practical result of power analysis attack. Thus we propose the correlation power analysis attack method and prove the feasibility of our proposed method by practical experiments, We used an 8-bit RISC AVR microprocessor (ATmegal128L chip) to implement Salsa20/12 stream cipher without any countermeasures, and performed the experiments of power analysis based on Hamming weight model.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.346-356
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• 2022

The jurisprudential legal rules govern the way Muslims react and interact to daily life. This creates a huge stream of questions, that require highly qualified and well-educated individuals, called Muftis. With Muslims representing almost 25% of the planet population, and the scarcity of qualified Muftis, this creates a demand supply problem calling for Automation solutions. This motivates the application of Artificial Intelligence (AI) to solve this problem, which requires a well-designed Question-Answering (QA) system to solve it. In this work, we propose a QA system, based on retrieval augmented generative transformer model for jurisprudential legal question. The main idea in the proposed architecture is the leverage of both state-of-the art transformer models, and the existing knowledge base of legal sources and question-answers. With the sensitivity of the domain in mind, due to its importance in Muslims daily lives, our design balances between exploitation of knowledge bases, and exploration provided by the generative transformer models. We collect a custom data set of 850,000 entries, that includes the question, answer, and category of the question. Our evaluation methodology is based on both quantitative and qualitative methods. We use metrics like BERTScore and METEOR to evaluate the precision and recall of the system. We also provide many qualitative results that show the quality of the generated answers, and how relevant they are to the asked questions.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.37-44
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• 2022

Plug-in Hybrid electric vehicles (PHEV) show great potential to reduce gas emission, improve fuel efficiency and offer more driving range flexibility. Moreover, PHEV help to preserve the eco-system, climate changes and reduce the high demand for fossil fuels. To address this; some basic components and energy resources have been used, such as batteries and proton exchange membrane (PEM) fuel cells (FCs). However, the FC remains unsatisfactory in terms of power density and response. In light of the above, an electric storage system (ESS) seems to be a promising solution to resolve this issue, especially when it comes to the transient phase. In addition to the FC, a storage system made-up of an ultra-battery UB is proposed within this paper. The association of the FC and the UB lead to the so-called Fuel Cell Battery Electric Vehicle (FCBEV). The energy consumption model of a FCBEV has been built considering the power losses of the fuel cell, electric motor, the state of charge (SOC) of the battery, and brakes. To do so, the implementing a reinforcement-learning energy management strategy (EMS) has been carried out and the fuel cell efficiency has been optimized while minimizing the hydrogen fuel consummation per 100km. Within this paper the adopted approach over numerous driving cycles of the FCBEV has shown promising results.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.1-9
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• 2023

The practical courses are considered as a model for the courses taught by the student of the Department of Physical Education at different levels of study, during which he employs his mental, physical and skill abilities to understand and master the motor skills and develop his physical abilities to be able to master them and later teach and train them, so this study was conducted with the aim of identifying the perceived mental image For the practical courses of the students of the Department of Physical Education at Umm Al-Qura University, by designing a scale for the perceived mental image of the practical courses, and identifying the percentages and the extent of their prevalence for each of the positive mental image, the nonperceived mental image, and the negative mental image of the practical courses among the students of the Department of Physical Education at Umm Al-Qura University, The researcher used the descriptive approach from the survey studies by designing a measure of the perceived mental image on a sample of (175) students, and they were chosen by the intentional method from the fourth level students who studied all the practical courses in the department, whether for the first or second semester of the academic year 2021 /2022. Data using frequencies, percentages and the test of significance of the ratio, and one of the most important results was the validity of the scale used in measuring the mental image perceived by students of the Department of Physical Education about practical courses. Realizing a positive mental image that is statistically significant about the practical courses of (53.20%) of the students of the Department of Physical Education, the sample of this study. And realizing a positive mental image that is statistically significant for students about the axes of the nature of studying practical courses, their abilities in practical performance, the method of implementing lectures, the lecturer, and their evaluation methods. The mental image of the student, and taking appropriate measures to develop the practical courses and academic programs, applying similar studies to measure the mental image of the department's graduates on the specialized tracks in the Department of Physical Education, reviewing the number of hours for some practical courses so that they are not less than two hours for all practical courses.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.