9786206686712 - Securing the Web: Machine Learning for CSRF Vulnerability Detection: Harnessing Machine Learning Algorithms for Accurate Detection and Prevention de Reddy, Pallavi (8 resultados)

Condición: New.

Taschenbuch. Condición: Neu. Securing the Web: Machine Learning for CSRF Vulnerability Detection | Harnessing Machine Learning Algorithms for Accurate Detection and Prevention | Pallavi Reddy | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206686712 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Web Vulnerability Detection of Cross-Site Request Forgery Using Machine Learning Algorithm' is a book that focuses on the detection and prevention of Cross-Site Request Forgery (CSRF) vulnerabilities in web applications. The book presents a precise and practical approach to leveraging machine learning algorithms for identifying and mitigating these web security threats. It offers insights into the risks associated with CSRF attacks, explains the fundamentals of machine learning, and demonstrates how machine learning algorithms can be trained to detect and prevent CSRF vulnerabilities in real-time. This book is a valuable resource for web developers, security professionals, and researchers interested in fortifying web applications against CSRF attacks using advanced machine learning techniques. 64 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Web Vulnerability Detection of Cross-Site Request Forgery Using Machine Learning Algorithm is a book that focuses on the detection and prevention of Cross-Site Request Forgery (CSRF) vulnerabilities in web applications. The book presents a precise and prac.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Web Vulnerability Detection of Cross-Site Request Forgery Using Machine Learning Algorithm' is a book that focuses on the detection and prevention of Cross-Site Request Forgery (CSRF) vulnerabilities in web applications. The book presents a precise and practical approach to leveraging machine learning algorithms for identifying and mitigating these web security threats. It offers insights into the risks associated with CSRF attacks, explains the fundamentals of machine learning, and demonstrates how machine learning algorithms can be trained to detect and prevent CSRF vulnerabilities in real-time. This book is a valuable resource for web developers, security professionals, and researchers interested in fortifying web applications against CSRF attacks using advanced machine learning techniques.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Web Vulnerability Detection of Cross-Site Request Forgery Using Machine Learning Algorithm' is a book that focuses on the detection and prevention of Cross-Site Request Forgery (CSRF) vulnerabilities in web applications. The book presents a precise and practical approach to leveraging machine learning algorithms for identifying and mitigating these web security threats. It offers insights into the risks associated with CSRF attacks, explains the fundamentals of machine learning, and demonstrates how machine learning algorithms can be trained to detect and prevent CSRF vulnerabilities in real-time. This book is a valuable resource for web developers, security professionals, and researchers interested in fortifying web applications against CSRF attacks using advanced machine learning techniques.