Indicators for Determining Collaborative Security Level in Organizational Environments

Sbora, Catalin

doi:10.12948/issn14531305/18.4.2014.12

Cited by 3 publications

(2 citation statements)

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“…Privacy is an important challenge in the IoT environment, due to availability of sensory devices, and the speed and volume of information flow [33]. Any compromise of privacy may lead to problems such as eavesdropping [34], [35], unauthorised access to, or alteration or destruction of, information [36], hacking, identity theft, forgery and social engineering [37]. Some organisations are reluctant to adopt the IoT because of fears of privacy compromises [38], [39], particularly in cases that involve medical data, in which maintaining the privacy and anonymity of the user is of the utmost importance [22], [40]- [42] because of legal and statutory requirements, which in turn affect trust to adopt the IoT in the healthcare domain.…”

Section: B Privacymentioning

confidence: 99%

The Effect of Security, Privacy, Familiarity, and Trust on Users’ Attitudes Toward the Use of the IoT-Based Healthcare: The Mediation Role of Risk Perception

2019

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The Internet of Things (IoT) refers to the network of devices which contain electronics, sensors or software that enables them to connect at anytimeand anywhere through a cyber-physical system. Before the establishment of such a system, it should be considered to what extent the users are ready to adopt and use it in their daily routines. Therefore, this paper explores users' attitudestowardsusing IoT technologies to receive healthcare services. This is in contrast to most previous research, which has studied the technical requirements or devices of the IoT that are required in healthcare services, or ways in which connectivity and performance can be improved using the IoT. Based on known models of technology acceptance, an integrated framework was developed to investigate the impact of security and privacy concerns, and familiarity with the technology, on users' trust in the IoT, and then to measure the effect of that trust on Omani users' attitudes regarding use ofIoT technologies to receive healthcare services. This framework enabled the measurement of risk perception as a mediator between user trust and their attitudes towards using the IoT. Data were collected from 387 respondents and were analysed using SPSS 25 and AMOS 25 statistics software. Exploratory and confirmatory analysis and structural equation modelling were applied. The findings showed that levels of security, privacy and familiarity affected trustin the IoT. Furthermore, these levels of trust in the IoT were found to affect both users' perceptions of risk in, and their attitude towards, using the IoT. The users' risk perception partially mediated the relations between users' trustand their attitude regarding use of the IoT. The framework was supported and interpreted by 40 per cent of the variance in the attitude towards usingthe IoT in healthcare, while the mediator showed 47 per cent of the variance in the attitude towards using the IoT inhealthcare.

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Section: B Privacymentioning

confidence: 99%

The Effect of Security, Privacy, Familiarity, and Trust on Users’ Attitudes Toward the Use of the IoT-Based Healthcare: The Mediation Role of Risk Perception

2019

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“…The confidence threshold h c is commonly used to extract high confidence items from frequent items, which are the students' social ties. Support and confidence thresholds are usually set by users or experts in the traditional approach and are usually fixed [31,32]. However, in mining the college students' social network, different students have different check-in data numbers.…”

Section: Social Ties Mining With Association Analysismentioning

confidence: 99%

Finding College Student Social Networks by Mining the Records of Student ID Transactions

Liu

Yang

et al. 2019

Symmetry

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Information about college students’ social networks plays a pivotal role in college students’ mental health monitoring and student management. While there have been many studies to infer social networks by data mining, the mining of college students’ social networks lacks consideration of homophily. College students’ social behaviors show significant homophily in the aspect of major and grade. Consequently, the inferred inter-major and inter-grade social ties will be erroneously omitted without considering such an effect. In this work, we aimed to increase the fidelity of the extracted networks by alleviating the homophily effect. To achieve this goal, we propose a method that combines the sliding time-window method with the hierarchical encounter model based on association rules. Specifically, we first calculated the counts of spatial–temporal co-occurrences of each student pair. The co-occurrences were acquired by the sliding time-window method, which takes advantage of the symmetry of the social ties. We then applied the hierarchical encounter model based on association rules to extract social networks by layer. Furthermore, we propose an adaptive method to set co-occurrence thresholds. Results suggested that our model infers the social networks of students with better fidelity, with the proportion of extracted inter-major social ties in entire social ties increasing from 0.89% to 5.45% and the proportion of inter-grade social ties rising from 0.92% to 4.65%.

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The Awareness of Internet of Things (IoT) Privacy Risk: A Survey Study

Almubark¹,

Masmali²

2022

Lecture Notes in Networks and Systems

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Indicators for Determining Collaborative Security Level in Organizational Environments

Cited by 3 publications

References 0 publications

The Effect of Security, Privacy, Familiarity, and Trust on Users’ Attitudes Toward the Use of the IoT-Based Healthcare: The Mediation Role of Risk Perception

The Effect of Security, Privacy, Familiarity, and Trust on Users’ Attitudes Toward the Use of the IoT-Based Healthcare: The Mediation Role of Risk Perception

Finding College Student Social Networks by Mining the Records of Student ID Transactions

The Awareness of Internet of Things (IoT) Privacy Risk: A Survey Study

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