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Subject: search.filters.subject.Social Networks

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    PublicationOpen Access
    A Risk Management Framework for Clouds Using Big Data and Security Informatics usingAttack Trees and Hidden Markov Model in Analysis and Prediction of Risks in Social Media …
    (2014-11) Subasinghe, K. D. B. H; Kodituwakku, S. R; Perera, H. S. C
    Social media refers to the means of interactions among people in which they create, share, and exchange information and ideas in virtual communities and networks. The growth of Information and Communication Technology (ICT) has resulted in an enormous volume of security related information present on the web largely when it comes to social media networks. Therefore, with the changing face of cyber security, although it is difficult, it was found that detecting the potential cyber-attacks or crimes is possible and feasible with the vast improvements in ICT. Cloud computing uses ICT resources that are delivered as a service over a network which has opened a promising opportunity across the globe thus resulting a greater popularity of e-commerce. The proposed framework is developed to manage risks of social media networks using the attack tree method which is used to model the risk of the system and identify the possible attacking strategies which the adversaries may launch. This paper presents the development of a Risk Management Framework by analysis of social media networks through web intelligence and security informatics using attack tree analysis based on the Hidden Markov Model for information extraction and prediction of risk factors of Social Media Networks.
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    The Relationship between Individuals’ Social Networks and Satisfaction with Life: The Mediating Role of Loneliness
    (Faculty of Humanities and Sciences - SLIIT, 2021-03-26) Perera, P.L.; Perera, H.K.
    Humans are social beings, pre-programmed to form connections even before birth. Every individual has a set of connections with a group of people, through whom the need to socially connect with others is satisfied. A failure to satisfy these needs can have detrimental effects on an individual. Commonly known phenomena such as social isolation can be perceived as feelings of loneliness in the absence of adequate social connections. Despite the understanding that loneliness is typically prevalent in the elderly population, recent surveys show that young adults are lonelier than any other age group despite having the highest amount of social connections. Yet a limited number of research has been conducted to date on loneliness among young adults. Therefore, this study aimed to investigate whether loneliness was influenced by social network characteristics, and, in turn, could predict satisfaction with life (SWL). Data was collected using a survey disseminated among young adults aged 19- 24. Using a sample of 194 participants, results revealed that the relationships between two out of four structural characteristics (average closeness and frequency of interaction) and SWL were significantly mediated by loneliness, while the other two (network size and network density) were not. The relationship between the functional network characteristic of perceived social support and SWL was also significantly mediated by loneliness. The paper concludes with a brief discussion of the limitations and implications of these findings.