• ETRI Journal
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• v.37 no.2
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• pp.222-232
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• 2015

In this paper, we propose a dual-phase approach to improve the process of heart disease prediction in a mobile environment. Firstly, only the confident frequent rules are extracted from a patient's clinical information. These are then used to foretell the possibility of the presence of heart disease. However, in some cases, subjects cannot describe exactly what has happened to them or they may have a silent disease - in which case it won't be possible to detect any symptoms at this stage. To address these problems, data records collected over a long period of time of a patient's heart rate variability (HRV) are used to predict whether the patient is suffering from heart disease. By analyzing HRV patterns, doctors can determine whether a patient is suffering from heart disease. The task of collecting HRV patterns is done by an online artificial neural network, which as well as learning knew knowledge, is able to store and preserve all previously learned knowledge. An experiment is conducted to evaluate the performance of the proposed heart disease prediction process under different settings. The results show that the process's performance outperforms existing techniques such as that of the self-organizing map and gas neural growing in terms of classification and diagnostic accuracy, and network structure.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.54-65
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• 2021

The movement control order and shutting down educational institution in Saudi Arabia has jeopardized the teaching and learning process. Education was shifted to distance learning in order to avoid any academic loss. In the middle of the Covid-19 crisis, there is a need to assess the full image of e-learning in Saudi Arabia. To investigate student and teachers' perception and acceptance, parents' attitudes and believes about distance education are the main goals of the study. The mix-method research design was employed to collect data. Three surveys were distributed to 100 students and 50 teachers and 50 parents from different educational institutions in Saudi Arabia, while semi-structured interviews were conducted with 10 parents. Random stratified and convenient sampling methods were adopted. Both descriptive and content analysis was conducted using SPSS25.0 and NVIVO software for quantitative and qualitative data accordingly. The findings showed that students are comfortable with remote education and are receiving enough support from schools and instructors but they think online education can't replace conventional face-to-face learning. Moreover, the results showed that teachers are having challenges in preparing online classes because of the development of conducting online classes and the lack of training. However, parents showed negative attitudes regarding the benefits and values of remote education and preferred conventional learning styles in elementary schools. Parents tended to reject and resist distance learning for several reasons: professional knowledge and lack of time to support their young kids in online classes, the shortcomings of e-learning, young children's inadequate self-regulation. Saudi parents are neither trained nor ready to use e-learning. The study provided suggestion and implications for teacher education and policymakers.

• Asia Marketing Journal
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• v.22 no.3
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• pp.71-85
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• 2020

Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.229-237
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• 2021

Our modern 'information-hungry' age demands delivery of information at unprecedented fast rates. Timely delivery of noteworthy information about recent events can help people from different segments of life in number of ways. As world has become global village, the flow of news in terms of volume and speed demands involvement of machines to help humans to handle the enormous data. News are presented to public in forms of video, audio, image and text. News text available on internet is a source of knowledge for billions of internet users. Urdu language is spoken and understood by millions of people from Indian subcontinent. Availability of online Urdu news enable this branch of humanity to improve their understandings of the world and make their decisions. This paper uses available online Urdu news data to train machines to automatically categorize provided news. Various machine learning algorithms were used on news headline for training purpose and the results demonstrate that Bernoulli Naïve Bayes (Bernoulli NB) and Multinomial Naïve Bayes (Multinomial NB) algorithm outperformed other algorithms in terms of all performance parameters. The maximum level of accuracy achieved for the dataset was 94.278% by multinomial NB classifier followed by Bernoulli NB classifier with accuracy of 94.274% when Urdu stop words were removed from dataset. The results suggest that short text of headlines of news can be used as an input for text categorization process.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.127-133
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• 2021

Today, phishing attacks represent one of the biggest security threats targeting users of the digital world. They consist of an attempt to steal sensitive information, such as a user's identity or credit and debit card details, using various methods that include fake emails, fake websites, and fake social media messages. Protecting the user's security and privacy therefore becomes complex, especially when those users are children. Currently, children are participating in Internet activity more frequently than ever before. This activity includes, for example, online gaming, communication, and schoolwork. However, children tend to have a less well-developed knowledge of privacy and security concepts, compared to adults. Consequently, they often become victims of cybercrime. In this paper, the effects of security awareness on users who are children are investigated, looking at their ability to detect phishing attacks in social media. In this approach, two Experiments were conducted to evaluate the effects of security awareness on WhatsApp application users in their daily communication. The results of the Experiments revealed that phishing awareness training has a significant positive effect on the ability of children using WhatsApp to identify phishing messages and thereby avoid attacks.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.18-26
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• 2011

Social network services whose users increase rapidly is the online services that reflect social network. They are used for various purposes such as strategy of election, commercial advertisement and marketing, educational information sharing and exchange of medical knowledge and opinions. These services make users form social networks with other users who have common interests and expand their relationships by releasing their personal information and utilizing other users' social networks. However, the social network services based on open and sharing of information raise various security threats such as violation of privacy and phishing. In this paper, we propose a group key management scheme and protocols using key rings to protect communication of small groups in social network services.

• Knowledge Management Research
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• v.19 no.2
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• pp.21-45
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• 2018

With the widespread use of smartphones and the development of information technology, an online service called SNS(social network service) has emerged, and as an increasing number of people began to use SNS, extensive research has been conducted on SNS. SNS is an important factor for adolescents who are developing social skills that help them to adapt to the society, and for adults who are stepping into the society. The present study investigates the effects of information search, self-disclosure, interaction, and playfulness, all of which are motivational factors for SNS use, on flow in SNS, and empirically analyzes the degree of these variables influence according to flow in SNS and individual's personal nature(extrovert, introvert). The analysis results showed that information search, self-disclosure, interaction, and playfulness were positively correlated with flow in SNS, and flow in SNS was positively correlated with social skills. The degree of influence varied depending on the individual's personal nature(extrovert, introvert). These findings may provide important insights for researchers studying SNS, SNS managers, and company officials using SNS.

• Knowledge Management Research
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• v.15 no.4
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• pp.171-187
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• 2014

The social network services (SNS) like Facebook, have gained an enormous amount of popularity. However, side-effects of Facebook usage are occasionally reported such as sense of alienation and cyber-bullying. Among these potential factors threatening to the success of SNS, this research focused on alienation and intends to investigate possible factors that affect SNS alienation and how it affects on SNS attachment and proactive use of SNS. Through extensive literature reviews regarding online and offline alienation, SNS characteristics, and SNS usage, we generated the research model and hypotheses. We surveyed 142 Facebook users and empirically proved that among SNS characteristics, complexity increases SNS alienation, and interactivity and social presence positively affect SNS attachment. Offline alienation, one of the personal attributes, increases both SNS alienation and SNS attachment at the same time while the number of SNS friends have no significant effects. In addition, SNS alienation decreases proactive use of Facebook while SNS attachment increases it. Theoretical and practical implications are discussed based on research findings, and we also suggest future research directions to minimize negative consequences due to SNS users' sense of alienation.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.119-124
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• 2021

Today, both sides of modern culture are decisively invaded by digitalization. Authentication is considered to be one of the main components in keeping this process secure. Cyber criminals are working hard in penetrating through the existing network channels to encounter malicious attacks. When it comes to enterprises, the company's information is a major asset. Question here arises is how to protect the vital information. This takes into account various aspects of a society often termed as hyper connected society including online communication, purchases, regulation of access rights and many more. In this research paper, we will discuss about the concepts of MFA and KBA, i.e., Multi-Factor Authentication and Knowledge Based Authentication. The purpose of MFA and KBA its utilization for human.to.everything..interactions, offering easy to be used and secured validation mechanism while having access to the service. In the research, we will also explore the existing yet evolving factor providers (sensors) used for authenticating a user. This is an important tool to protect data from malicious insiders and outsiders. Access Management main goal is to provide authorized users the right to use a service also preventing access to illegal users. Multiple techniques can be implemented to ensure access management. In this paper, we will discuss various techniques to ensure access management suitable for enterprises, primarily focusing/restricting our discussion to multifactor authentication. We will also highlight the role of knowledge-based authentication in multi factor authentication and how it can make enterprises data more secure from Cyber Attack. Lastly, we will also discuss about the future of MFA and KBA.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.222-229
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• 2022

Through this technology development, companies that operate online shopping malls and prospective startups will support education, consulting and expert group matching so that they can solve various issues that may arise in the course of the entire business life cycle, from startups to closures. It is expected that differentiated consulting programs will be designed for companies that currently operate shopping malls and start ups, and customized consulting programs will be provided to improve the effectiveness of consulting while improving customer satisfaction. It is planning to develop a "successful start-up and operation helper" that helps successful start-ups. It is a system that primarily diagnoses problems of prospective entrepreneurs and operators through an automation system at the start-up and operation stage, and professional consultants participate to derive and solve problems, and takes care of all stages of shopping mall birth and growth. In this paper Metaverse based shopping mall Creation is also discussed. Through Big Data creation these accumulated data, we intend to help operators start and operate shopping malls through accurate information by managing all knowledge of shopping malls as a system in the long run.