Social network usage has increased exponentially in recent years. Platforms like Facebook, Twitter, Google+, LinkedIn and Instagram, not only facilitate sharing of personal data but also connect people professionally. However, development of these platforms with more enhanced features like HTML5, CSS, XHTML and Java Script expose these sites to various vulnerabilities that may be the root cause of various threats. Therefore, social networking sites have become an attack surface for various cyber-attacks such as XSS attack and SQL Injection. Numerous defensive techniques have been proposed, yet with technology up-gradation current scenarios demand for more efficient and robust solutions.

Cross-Site Scripting Attacks: Classification, Attack, and Countermeasures is a comprehensive source which provides an overview of web-based vulnerabilities and explores XSS attack in detail. This book provides a detailed overview of the XSS attack; its classification, recent incidences on various web applications, and impacts of the XSS attack on the target victim. This book addresses the main contributions of various researchers in XSS domain. It provides in-depth analysis of these methods along with their comparative study. The main focus is a novel framework which is based on Clustering and Context based sanitization approach to protect against XSS attack on social network. The implementation details conclude that it is an effective technique to thwart XSS attack. The open challenges and future research direction discussed in this book will help further to the academic researchers and industry specific persons in the domain of security.

Social network usage has increased exponentially in recent years. Platforms like Facebook, Twitter, Google+, LinkedIn and Instagram, not only facilitate sharing of personal data but also connect people professionally. However, development of these platforms with more enhanced features like HTML5, CSS, XHTML and Java Script expose these sites to various vulnerabilities that may be the root cause of various threats. Therefore, social networking sites have become an attack surface for various cyber-attacks such as XSS attack and SQL Injection. Numerous defensive techniques have been proposed, yet with technology up-gradation current scenarios demand for more efficient and robust solutions.

Cross-Site Scripting Attacks: Classification, Attack, and Countermeasures is a comprehensive source which provides an overview of web-based vulnerabilities and explores XSS attack in detail. This book provides a detailed overview of the XSS attack; its classification, recent incidences on various web applications, and impacts of the XSS attack on the target victim. This book addresses the main contributions of various researchers in XSS domain. It provides in-depth analysis of these methods along with their comparative study. The main focus is a novel framework which is based on Clustering and Context based sanitization approach to protect against XSS attack on social network. The implementation details conclude that it is an effective technique to thwart XSS attack. The open challenges and future research direction discussed in this book will help further to the academic researchers and industry specific persons in the domain of security.

Social network usage has increased exponentially in recent years. Platforms like Facebook, Twitter, Google+, LinkedIn and Instagram, not only facilitate sharing of personal data but also connect people professionally. However, development of these platforms with more enhanced features like HTML5, CSS, XHTML and Java Script expose these sites to various vulnerabilities that may be the root cause of various threats. Therefore, social networking sites have become an attack surface for various cyber-attacks such as XSS attack and SQL Injection. Numerous defensive techniques have been proposed, yet with technology up-gradation current scenarios demand for more efficient and robust solutions.

Cross-Site Scripting Attacks: Classification, Attack, and Countermeasures is a comprehensive source which provides an overview of web-based vulnerabilities and explores XSS attack in detail. This book provides a detailed overview of the XSS attack; its classification, recent incidences on various web applications, and impacts of the XSS attack on the target victim. This book addresses the main contributions of various researchers in XSS domain. It provides in-depth analysis of these methods along with their comparative study. The main focus is a novel framework which is based on Clustering and Context based sanitization approach to protect against XSS attack on social network. The implementation details conclude that it is an effective technique to thwart XSS attack. The open challenges and future research direction discussed in this book will help further to the academic researchers and industry specific persons in the domain of security.

Social network usage has increased exponentially in recent years. Platforms like Facebook, Twitter, Google+, LinkedIn and Instagram, not only facilitate sharing of personal data but also connect people professionally. However, development of these platforms with more enhanced features like HTML5, CSS, XHTML and Java Script expose these sites to various vulnerabilities that may be the root cause of various threats. Therefore, social networking sites have become an attack surface for various cyber-attacks such as XSS attack and SQL Injection. Numerous defensive techniques have been proposed, yet with technology up-gradation current scenarios demand for more efficient and robust solutions.

Cross-Site Scripting Attacks: Classification, Attack, and Countermeasures is a comprehensive source which provides an overview of web-based vulnerabilities and explores XSS attack in detail. This book provides a detailed overview of the XSS attack; its classification, recent incidences on various web applications, and impacts of the XSS attack on the target victim. This book addresses the main contributions of various researchers in XSS domain. It provides in-depth analysis of these methods along with their comparative study. The main focus is a novel framework which is based on Clustering and Context based sanitization approach to protect against XSS attack on social network. The implementation details conclude that it is an effective technique to thwart XSS attack. The open challenges and future research direction discussed in this book will help further to the academic researchers and industry specific persons in the domain of security.