Kids Cybersecurity Using Computational Intelligence Techniques PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Kids Cybersecurity Using Computational Intelligence Techniques PDF full book. Access full book title Kids Cybersecurity Using Computational Intelligence Techniques by Wael M. S. Yafooz. Download full books in PDF and EPUB format.
Author: Wael M. S. Yafooz
Publisher: Springer Nature
ISBN: 3031211995
Category : Technology & Engineering
Languages : en
Pages : 279
Get Book Here
Book Description
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.
Author: Wael M. S. Yafooz
Publisher: Springer Nature
ISBN: 3031211995
Category : Technology & Engineering
Languages : en
Pages : 279
Get Book Here
Book Description
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.
Author: Mohamed Lahby
Publisher: CRC Press
ISBN: 1003825036
Category : Computers
Languages : en
Pages : 303
Get Book Here
Book Description
Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide. Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts. Key Features: Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms. Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence. Includes many case studies and applications of machine intelligence for combating cyberbullying.
Author: Alex Khang
Publisher: CRC Press
ISBN: 1040088465
Category : Computers
Languages : en
Pages : 443
Get Book Here
Book Description
Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.
Author: Debasis Giri
Publisher: Springer Nature
ISBN: 9811931828
Category : Technology & Engineering
Languages : en
Pages : 415
Get Book Here
Book Description
The book is a collection of best selected research papers presented at International Conference on Network Security and Blockchain Technology (ICNSBT 2021), organized by Computer Society of India—Kolkata Chapter, India, during December 2–4, 2021. The book discusses recent developments and contemporary research in cryptography, network security, cyber security, and blockchain technology. Authors are eminent academicians, scientists, researchers, and scholars in their respective fields from across the world.
Author: Sita Rani
Publisher: CRC Press
ISBN: 1000862372
Category : Computers
Languages : en
Pages : 337
Get Book Here
Book Description
Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues. Features: Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findings Provides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problems Ideal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges
Author: Emmanuel Tsukerman
Publisher: Packt Publishing Ltd
ISBN: 1838556346
Category : Computers
Languages : en
Pages : 338
Get Book Here
Book Description
Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key FeaturesManage data of varying complexity to protect your system using the Python ecosystemApply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineeringAutomate your daily workflow by addressing various security challenges using the recipes covered in the bookBook Description Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference. With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers. You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models. By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach. What you will learnLearn how to build malware classifiers to detect suspicious activitiesApply ML to generate custom malware to pentest your securityUse ML algorithms with complex datasets to implement cybersecurity conceptsCreate neural networks to identify fake videos and imagesSecure your organization from one of the most popular threats – insider threatsDefend against zero-day threats by constructing an anomaly detection systemDetect web vulnerabilities effectively by combining Metasploit and MLUnderstand how to train a model without exposing the training dataWho this book is for This book is for cybersecurity professionals and security researchers who are looking to implement the latest machine learning techniques to boost computer security, and gain insights into securing an organization using red and blue team ML. This recipe-based book will also be useful for data scientists and machine learning developers who want to experiment with smart techniques in the cybersecurity domain. Working knowledge of Python programming and familiarity with cybersecurity fundamentals will help you get the most out of this book.
Author: Murugan, Thangavel
Publisher: IGI Global
ISBN: 1668481472
Category : Computers
Languages : en
Pages : 649
Get Book Here
Book Description
Disruptive innovations are now propelling Industry 4.0 (I4.0) and presenting new opportunities for value generation in all major industry segments. I4.0 technologies' innovations in cybersecurity and data science provide smart apps and services with accurate real-time monitoring and control. Through enhanced access to real-time information, it also aims to increase overall effectiveness, lower costs, and increase the efficiency of people, processes, and technology. The Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies discusses the technological foundations of cybersecurity and data science within the scope of the I4.0 landscape and details the existing cybersecurity and data science innovations with I4.0 applications, as well as state-of-the-art solutions with regard to both academic research and practical implementations. Covering key topics such as data science, blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, computer scientists, scholars, researchers, academicians, practitioners, instructors, and students.
Author: Radek Silhavy
Publisher: Springer Nature
ISBN: 3031702859
Category :
Languages : en
Pages : 799
Get Book Here
Book Description
Author: Soma Halder
Publisher: Packt Publishing Ltd
ISBN: 178899096X
Category : Computers
Languages : en
Pages : 306
Get Book Here
Book Description
Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book
Author: Clarence Chio
Publisher: "O'Reilly Media, Inc."
ISBN: 1491979852
Category : Computers
Languages : en
Pages : 394
Get Book Here
Book Description
Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
