scholarly journals Deterministic Model Investigation of Processes in a Heterogeneous e-Learning Environment

The investigation of characteristics of access and use of resources in different distributed environments in the network space is aimed at determining optimal levels for the basic parameters of the supported processes. On the other hand, with the development of the possibilities of the digital space and the significant change in the level of informatization of the society, it is necessary to take the necessary measures to ensure secure access to information resources and in particular to the profiles of personal data. In this respect, the purpose of the article is to propose an organization of heterogeneous environment with resources stored in different places (own memories and cloud data centres). A general architecture and functionality of the main sub-systems are presented. Deterministic model investigation by using Petri Net apparatus based on preliminary formalization is provided to analyse the effectiveness of the processes for regulated and secure access to resources.

Author(s):  
Radi Romansky ◽  
Irina Noninska

The contemporary digital world based on network communications, globalization and information sharing outlines new important targets in the area of privacy and personal data protection which reflect to applied principles of secure access to proposed information structures. In this reason the aim of secure access to all resources of an e-learning environment is very important and adequate technological and organizational measures for authentication, authorization and protection of personal data must be applied. Strong security procedures should be proposed to protect user's profiles, designed after successful registration and all personal information collected by educational processes. The goal of this article is to present an idea to combine traditional e-learning technologies with new opportunities that give mobile applications, cloud services and social computing. These technologies can endanger data security since they make possible remote access to resources, sharing information between participants by network communications. In order to avoid data vulnerabilities users must be identified and authenticated before, i.e. to be allowed to access information resources otherwise integrity and confidentiality of e-learning system could be destroyed. In order to propose solution basic principles of information security and privacy protection in e-learning processes are discussed in this article. As a result, an organizational scheme of a system for information security and privacy is proposed. Based on these principles a graph formalization of access to the system resources is made and architecture for combined (heterogenic) e-learning architecture with secure access to the resources is designed. Analytical investigation based on designed Markov chain has been carried out and several statistical assessments delivered by Develve software are discussed.


Author(s):  
Radi Petrov Romansky ◽  
Irina Stancheva Noninska

The contemporary digital world based on network communications, globalization and information sharing outlines new important targets in the area of privacy and personal data protection which reflect to applied principles of secure access to proposed information structures. In this reason the aim of secure access to all resources of an e-learning environment is very important and adequate technological and organizational measures for authentication, authorization and protection of personal data must be applied. Strong security procedures should be proposed to protect user's profiles, designed after successful registration and all personal information collected by educational processes. The goal of this article is to present an idea to combine traditional e-learning technologies with new opportunities that give mobile applications, cloud services and social computing. These technologies can endanger data security since they make possible remote access to resources, sharing information between participants by network communications. In order to avoid data vulnerabilities users must be identified and authenticated before, i.e. to be allowed to access information resources otherwise integrity and confidentiality of e-learning system could be destroyed. In order to propose solution basic principles of information security and privacy protection in e-learning processes are discussed in this article. As a result, an organizational scheme of a system for information security and privacy is proposed. Based on these principles a graph formalization of access to the system resources is made and architecture for combined (heterogenic) e-learning architecture with secure access to the resources is designed. Analytical investigation based on designed Markov chain has been carried out and several statistical assessments delivered by Develve software are discussed.


2021 ◽  
Author(s):  
Thomas Weripuo Gyeera

<div>The National Institute of Standards and Technology defines the fundamental characteristics of cloud computing as: on-demand computing, offered via the network, using pooled resources, with rapid elastic scaling and metered charging. The rapid dynamic allocation and release of resources on demand to meet heterogeneous computing needs is particularly challenging for data centres, which process a huge amount of data characterised by its high volume, velocity, variety and veracity (4Vs model). Data centres seek to regulate this by monitoring and adaptation, typically reacting to service failures after the fact. We present a real cloud test bed with the capabilities of proactively monitoring and gathering cloud resource information for making predictions and forecasts. This contrasts with the state-of-the-art reactive monitoring of cloud data centres. We argue that the behavioural patterns and Key Performance Indicators (KPIs) characterizing virtualized servers, networks, and database applications can best be studied and analysed with predictive models. Specifically, we applied the Boosted Decision Tree machine learning algorithm in making future predictions on the KPIs of a cloud server and virtual infrastructure network, yielding an R-Square of 0.9991 at a 0.2 learning rate. This predictive framework is beneficial for making short- and long-term predictions for cloud resources.</div>


2018 ◽  
Vol 22 (S5) ◽  
pp. 12857-12862 ◽  
Author(s):  
G. Sahaya Stalin Jose ◽  
C. Seldev Christopher

Author(s):  
K. Chatzara ◽  
C. Karagiannidis ◽  
D. Stamatis

The introduction of emotional reactions to e-Learning environments might offer a more efficient and effective communication between the user and the machine; a more natural and realistic computer interface. Embodied Intelligent Emotional Agents (IEAs) which are highly expressive and show empathy for the users may help learners overcome academic difficulties and may contribute positively to the pedagogical procedure by making it more efficient and enjoyable. IEAs can be programmed to “show” the correct social behaviour and through them a channel of communication might open to serve for better interaction among learners. This could contribute to increase student’s self esteem, help them recover from negative emotions as well as encourage learners to overcome academic problems. In this chapter the authors review existing systems that use emotional agents and analyze their specific characteristics, their advantages and disadvantages. Finally, based on this analysis they enumerate specific requirements for efficient communication between agents and users and we use them to propose a general architecture model upon which the development of future IEAs could be based.


2017 ◽  
Vol 14 (4) ◽  
pp. 1-32 ◽  
Author(s):  
Shashank Gupta ◽  
B. B. Gupta

This article introduces a distributed intelligence network of Fog computing nodes and Cloud data centres for smart devices against XSS vulnerabilities in Online Social Network (OSN). The cloud data centres compute the features of JavaScript, injects them in the form of comments and saved them in the script nodes of Document Object Model (DOM) tree. The network of Fog devices re-executes the feature computation and comment injection process in the HTTP response message and compares such comments with those calculated in the cloud data centres. Any divergence observed will simply alarm the signal of injection of XSS worms on the nodes of fog located at the edge of the network. The mitigation of such worms is done by executing the nested context-sensitive sanitization on the malicious variables of JavaScript code embedded in such worms. The prototype of the authors' work was developed in Java development framework and installed on the virtual machines of Cloud data centres (typically located at the core of network) and the nodes of Fog devices (exclusively positioned at the edge of network). Vulnerable OSN-based web applications were utilized for evaluating the XSS worm detection capability of the authors' framework and evaluation results revealed that their work detects the injection of XSS worms with high precision rate and less rate of false positives and false negatives.


2008 ◽  
pp. 2492-2499 ◽  
Author(s):  
Edgar R. Weippl

Although the roots of e-learning date back to 19th century’s correspondence-based learning, e-learning currently receives an unprecedented impetus by the fact that industry and universities alike strive to streamline the teaching process. Just-in-time (JIT) principles have already been adopted by many corporate training programs; some even advocate the term “just-enough” to consider the specific needs of individual learners in a corporate setting. Considering the enormous costs involved in creating and maintaining courses, it is surprising that security and dependability are not yet considered an important issue by most people involved including teachers and students. Unlike traditional security research, which has largely been driven by military requirements to enforce secrecy, in e-learning it is not the information itself that has to be protected but the way it is presented. Moreover, the privacy of communication between teachers and students. For a long time students and faculty had few concerns about security, mainly because users in academic areas tended not to be malicious. Today, however, campus IT-security is vital. Nearly all institutions install firewalls and anti-virus software to protect campus resources. Even the most common security safeguards have drawbacks that people often fail to see. In Stanford the residential computing office selected an anti-virus program. However, the program can be set to collect data that possibly violates students’ privacy expectations; therefore many students declined using it (Herbert, 2004). Whenever servers that store personal data are not well protected, they are a tempting target for hackers. Social security numbers and credit card information are valuable assets used in identity theft. Such attacks were successful, for instance, at the University of Colorado (Crecente, 2004). A similar incident happened at the University of Texas; the student who committed the crime was later indicted in hacking (Associated Press, 2004). The etymological roots of secure can be found in se which means “without”, or “apart from”, and cura, that is, “to care for”, or “to be concerned about” (Landwehr, 2001). Consequently, secure in our context means that in a secure teaching environment users need not be concerned about threats specific to e-learning platforms and to electronic communication in general. A secure learning platform should incorporate all aspects of security and dependability and make most technical details transparent to the teacher and student. However, rendering a system “totally secure” is too ambitious a goal since no system can ever be totally secure and still remain usable at the same time. The contribution of this chapter is to • Define and identify relevant security and dependability issues. • Provide an overview of assets, threats, risks, and counter measures that are relevant to e-learning. • Point to publications that address the issues in greater detail.


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