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Kids cybersecurity using computation...

Yafooz, Wael.

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Kids cybersecurity using computational intelligence techniques

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Kids cybersecurity using computational intelligence techniques/ edited by Wael M. S. Yafooz ... [et al.].
其他作者:	Yafooz, Wael.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	vi, 282 p. :ill., digital ;24 cm.
內容註:	Part 1: State-of-the-art -- Everyday Cyber Safety for Students -- Machine Learning Approaches for Kids' E-learning Monitoring -- Factors influencing on online education outcomes- an empirical study based on Kids' parents -- Review on the Social Media Management Techniques against kids Harmful Information -- Review of Information Security Management Frameworks -- Database Forensics Field and Children Crimes -- From exhibitionism to addiction, or cyber threats among children and adolescents -- Part II: Cyberbullying and Kids cyber security -- Protection of Users Kids on Twitter Platform using Naïve Bayes -- The Impact of Fake News Spread on Social Media on The Children in Indonesia During Covid-19 -- A Preventive Approach to Weapons Detection for Children Using Quantum Deep Learning -- Learning Arabic for Kids online Using Google Classroom -- Child Emotion Recognition Via Custom Lightweight CNN Architecture -- Cybercrime Sentimental Analysis for Child YouTube Video Dataset Using Hybrid Support Vector Machine With Ant Colony Optimization Algorithm -- Cyberbullying Awareness Through Sentiment Analysis Based On Twitter -- The Impact of Fake News on Kid's Life from the Holy Al-Qur'an Perspective -- Early Prediction of Dyslexia Risk Factors in Kids through Machine Learning Techniques -- Development of Metamodel for Information Security Risk Management -- Detecting Kids Cyberbullying Using Transfer Learning Approach from Transformer Fine-Tuning Models -- YouTube Sentiment Analysis: Performance Model Evaluation.
Contained By:	Springer Nature eBook
標題:	Cyberbullying - Prevention. -
電子資源:	https://doi.org/10.1007/978-3-031-21199-7
ISBN:	9783031211997

Kids cybersecurity using computational intelligence techniques
Kids cybersecurity using computational intelligence techniques[electronic resource] /edited by Wael M. S. Yafooz ... [et al.]. - Cham :Springer International Publishing :2023. - vi, 282 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 10801860-9503 ;. - Studies in computational intelligence ;v. 1080..

Part 1: State-of-the-art -- Everyday Cyber Safety for Students -- Machine Learning Approaches for Kids' E-learning Monitoring -- Factors influencing on online education outcomes- an empirical study based on Kids' parents -- Review on the Social Media Management Techniques against kids Harmful Information -- Review of Information Security Management Frameworks -- Database Forensics Field and Children Crimes -- From exhibitionism to addiction, or cyber threats among children and adolescents -- Part II: Cyberbullying and Kids cyber security -- Protection of Users Kids on Twitter Platform using Naïve Bayes -- The Impact of Fake News Spread on Social Media on The Children in Indonesia During Covid-19 -- A Preventive Approach to Weapons Detection for Children Using Quantum Deep Learning -- Learning Arabic for Kids online Using Google Classroom -- Child Emotion Recognition Via Custom Lightweight CNN Architecture -- Cybercrime Sentimental Analysis for Child YouTube Video Dataset Using Hybrid Support Vector Machine With Ant Colony Optimization Algorithm -- Cyberbullying Awareness Through Sentiment Analysis Based On Twitter -- The Impact of Fake News on Kid's Life from the Holy Al-Qur'an Perspective -- Early Prediction of Dyslexia Risk Factors in Kids through Machine Learning Techniques -- Development of Metamodel for Information Security Risk Management -- Detecting Kids Cyberbullying Using Transfer Learning Approach from Transformer Fine-Tuning Models -- YouTube Sentiment Analysis: Performance Model Evaluation.

This book introduces and presents the newest up-to-date methods, approaches and technologies on how to detect child cyberbullying on social media as well as monitor kids E-learning, monitor games designed and social media activities for kids. On a daily basis, children are exposed to harmful content online. There have been many attempts to resolve this issue by conducting methods based on rating and ranking as well as reviewing comments to show the relevancy of these videos to children; unfortunately, there still remains a lack of supervision on videos dedicated to kids. This book also introduces a new algorithm for content analysis against harmful information for kids. Furthermore, it establishes the goal to track useful information of kids and institutes detection of kid's textual aggression through methods of machine and deep learning and natural language processing for a safer space for children on social media and online and to combat problems, such as lack of supervision, cyberbullying, kid's exposure to harmful content. This book is beneficial to postgraduate students and researchers' concerns on recent methods and approaches to kids' cybersecurity.

ISBN: 9783031211997

Standard No.: 10.1007/978-3-031-21199-7doiSubjects--Topical Terms:

2060490
Cyberbullying
--Prevention.

LC Class. No.: HV6773.15.C92 / K53 2023

Dewey Class. No.: 302.34302854678

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520 $a This book introduces and presents the newest up-to-date methods, approaches and technologies on how to detect child cyberbullying on social media as well as monitor kids E-learning, monitor games designed and social media activities for kids. On a daily basis, children are exposed to harmful content online. There have been many attempts to resolve this issue by conducting methods based on rating and ranking as well as reviewing comments to show the relevancy of these videos to children; unfortunately, there still remains a lack of supervision on videos dedicated to kids. This book also introduces a new algorithm for content analysis against harmful information for kids. Furthermore, it establishes the goal to track useful information of kids and institutes detection of kid's textual aggression through methods of machine and deep learning and natural language processing for a safer space for children on social media and online and to combat problems, such as lack of supervision, cyberbullying, kid's exposure to harmful content. This book is beneficial to postgraduate students and researchers' concerns on recent methods and approaches to kids' cybersecurity.
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