Securing the Web: Machine Learning for CSRF Vulnerability Detection: Harnessing Machine Learning Algorithms for Accurate Detection and Prevention - Pallavi Reddy
-40% ar kodu BOOKS
Piegāde 15-21 darba dienu laikā
30 dienu atgriešanas politika
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 ass ... Pilns apraksts
Jums varētu patikt arī
TOP
INCOSE Systems Engineering Handbook
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI
Eliezer Yudkowsky, Nate Soares
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Open Circuits: The Inner Beauty of Electronic Components
Eric Schlaepfer, Windell Oskay
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Get started with MicroPython on Raspberry Pi Pico: The Official Raspberry Pi Pico Guide
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
We Are Not Machines: The Fight for the Future of Work
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Foundations of Flavor: The Noma Guide to Fermentation: Including Step-By-Step Information on Making and Cooking with: Koji, Kombuchas, Shoyus, Misos, Vinegars, Garums, Lacto-Ferments and black Fruits Vegetables
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Nucleo Boards Programming with the STM32CubeIDE: Hands-on in more than 50 projects
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Steven L. Brunton, J. Nathan Kutz
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Black Holes: The Key to Understanding the Universe
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Practical Electronics for Inventors
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Flowers For Algernon: A Modern Literary Classic
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Human Compatible: Artificial Intelligence and the Problem of Control
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How To Read Water: Clues & Patterns from Puddles to the Sea
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Make: Electronics: Learning by Discovery: A hands-on primer for the new electronics enthusiast
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Mastering the Arduino Uno R4: Programming and Projects for the Minima and WiFi
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Idea Factory: Bell Labs and the Great Age of American Innovation
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Fundamentals of Aerodynamics ISE
Christopher Cadou, John D. Anderson
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Foundation Design and Construction
-40% ar kodu BOOKS
Piegādātāja noliktavā
Aprašymas
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.
Vairāk informācijas
| Autors | Pallavi Reddy |
|---|---|
| Izdevējs | LAP LAMBERT Academic Publishing |
| Izlaides gads | 2023 |
| Vāka tips | Mīkstais vāks |
| EAN | 9786206686712 |