Advanced Monitoring in P2P Botnets Advanced Monitoring in P2P Botnets
SpringerBriefs on Cyber Security Systems and Networks

Advanced Monitoring in P2P Botnets

A Dual Perspective

    • ‏49٫99 US$
    • ‏49٫99 US$

وصف الناشر

This book presents current research in the area of advanced monitoring in P2P botnets, and uses a dual-perspective approach to discuss aspects of botnet monitoring in-depth. First, from the perspective of a defender, e.g. researchers, it introduces advanced approaches to successfully monitor botnets, taking the presence of current botnet anti-monitoring mechanisms into consideration. Then, adopting a botmaster perspective to anticipate the advances in future botnets, it introduces advanced measures to detect and prevent monitoring activities. All the proposed methods were evaluated either using real-world data or in a simulation scenario. In addition to providing readers with an in-depth understanding of P2P botnets, the book also analyzes the implications of the various design choices of recent botnets for effectively monitoring them. It serves as an excellent introduction to new researchers and provides a useful review for specialists in the field.

النوع
كمبيوتر وإنترنت
تاريخ النشر
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١٧ مايو
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer Nature Singapore
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Botnet Detection Botnet Detection
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Intelligent, Secure, and Dependable Systems in Distributed and Cloud Environments Intelligent, Secure, and Dependable Systems in Distributed and Cloud Environments
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Security and Privacy in Communication Networks Security and Privacy in Communication Networks
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Information Security Applications Information Security Applications
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International Conference on Security and Privacy in Communication Networks International Conference on Security and Privacy in Communication Networks
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Security and Privacy in Communication Networks Security and Privacy in Communication Networks
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Big Digital Forensic Data Big Digital Forensic Data
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Honeypot Frameworks and Their Applications: A New Framework Honeypot Frameworks and Their Applications: A New Framework
٢٠١٨
Big Digital Forensic Data Big Digital Forensic Data
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Privacy-Preserving Machine Learning Privacy-Preserving Machine Learning
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Privacy-Preserving Deep Learning Privacy-Preserving Deep Learning
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Design and Cryptanalysis of ZUC Design and Cryptanalysis of ZUC
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