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Название: Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities
Автор: Sanjay Misra, Amit Kumar Tyagi
Издательство: Springer
Год: 2021
Страниц: 467
Язык: английский
Формат: pdf (true), epub
Размер: 55.9 MB

This book provides stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation results (using several analytics tools), and an application-oriented approach that can be demonstrated with respect to data analytics using Artificial Intelligence (AI) to make systems stronger (i.e., impossible to breach). We can see many serious cyber breaches on Government databases or public profiles at online social networking in the recent decade. Today Artificial Intelligence or Machine Learning (ML) is redefining every aspect of cyber security. From improving organizations’ ability to anticipate and thwart breaches, protecting the proliferating number of threat surfaces with Zero Trust Security frameworks to making passwords obsolete, AI and Machine Learning are essential to securing the perimeters of any business. The book is useful for researchers, academics, industry players, data engineers, data scientists, governmental organizations, and non-governmental organizations.

A malicious packet attack is defined as a severe attack created or received over the network. Recently, researchers have made modern intrusion detection systems in order to detect advanced and custom malicious attacks. Meanwhile, it is essential to efficiently distinguish from normal network packets to malicious packets with a high positive detection rate. The work proposes a system to identify and detect malicious packets over a wide range of attacks using a machine learning classifier model. The KDD dataset is trained and evaluated for performance in terms of accuracy to provide a high-quality detection system. The proposed work uses machine learning algorithms such as Support Vector Machine (SVM) and Naïve Bayesian to train the model and validated using incoming live network packets for Denial of Service (DoS) type of attack.





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