Fargana J. Abdullayeva

Work place: Institute of Information Technology, Azerbaijan National Academy of Sciences, Baku, Azerbaijan

E-mail: a_farqana@mail.ru


Research Interests:


Fargana J. Abdullayeva graduated from the ‘Computer Techniques and Technologies’ faculty of the Sumgait State University in 2002. In 2003, she was accepted for employment at the Institute of Information Technology of the ANAS, where she addressed issues of information security provision. In 2004, as a respondent, she commenced his work on the subject of ‘Development of methods and algorithms for providing information security of population and migration system’. In 2010, defense of the thesis took place. At present, she conducts researches on cloud computing security, anomaly detection, load balancing and task scheduling.

Author Articles
Log-File Analysis to Identify Internet-addiction in Children

By Rasim M. Alguliyev Fargana J. Abdullayeva Sabira S. Ojagverdiyeva

DOI: https://doi.org/10.5815/ijmecs.2021.05.03, Pub. Date: 8 Oct. 2021

The problem of the Internet addiction (IA) arose after the rise of the Internet. Some of the Internet users include children and teenagers and they are active in a virtual environment. Most minor users are not well aware of the dangers posed by information abundance. One of these dangers is the IA. Excessive use of the Internet is addictive, and some users experience a high risk of addiction. IA can negatively affect the children's health, psychology, socialization and other activities. There is a great need to the development of forecasting programs and various technological approaches for the identification of IA among Internet users, especially children and adolescents. This article uses machine-learning techniques to detect IA. Activities of children in the Internet environment is analyzed. The log-files of children and their IA problem are explored. To determine the degree of IA among children and adolescents an experiment is conducted on public dataset. The effectiveness of the methods is analyzed by various evaluation metrics and promising results are obtained.The results show better performance of Weighted SVM, compared to BernoulliNB, Logistic Regression, MLPClassifier, SVM classifiers. Acquired results of the research provide kids information security. To evaluate a kids IA helps to identify their psychological conditions, and it creates a better situation for parents, teachers, and other related people to communicate with children and teenagers better way.

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Multicriteria Decision Making using Analytic Hierarchy Process for Child Protection from Malicious Content on the Internet

By Fargana J. Abdullayeva Sabira S. Ojagverdiyeva

DOI: https://doi.org/10.5815/ijcnis.2021.03.05, Pub. Date: 8 Jun. 2021

Modern children are active Internet users. However, in the context of information abundance, they have little knowledge of which information is useful and which is harmful. To make the Internet a safe place for children, various methods are used at the international and national levels, as well as by experts, and the ways to protect children from harmful information are sought. The article proposes an approach using a multi-criteria decision-making process to prevent children from encountering harmful content on the Internet and to make the Internet more secure environment for children. The article highlights the age characteristics of children as criteria. Harmless information, Training information, Entertainment information, News, and Harmful information are considered as alternatives. Here, a decision is made by comparing the alternatives according to the given criteria. According to the trials, harmful information is rated in the last position.
There is no child protection issue on the Internet using the AHP method. This research is important to protect children from harmful information in the virtual space. In the protection of minors Internet users is a reliable approach for educational institutions, parents and other subjects related to child safety.

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Other Articles