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Malware Detection Techniques using Machine Learning Classifiers

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Android Malware Detection using Machine Learning

obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques;

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Android Malware Detection using Machine Learning

obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques;

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Machine Learning for Cybersecurity Cookbook

intrusion detection Key Features Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware;

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Classification of Malware

unknown complex malware. In this work, a new approach to detect malware, which uses reverse engineering and machine learning techniques;

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EEG Brain Signal Classification for Epileptic Seizure Disorder Detection

to detect epileptic seizures using machine learning techniques. Chapters present an overview of machine learning techniques and the tools;

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Classification Methods for Internet Applications

, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can be solved using various;

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Classification Methods for Internet Applications

, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can be solved using various;

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Data Science in Cybersecurity and Cyberthreat Intelligence

. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to;

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Machine Learning and Security

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and;

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Big Data Analytics with Applications in Insider Threat Detection

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new;

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Machine Learning for Biometrics

learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local;

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Machine Learning for Cyber Security

machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.;

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Machine Learning for Cyber Security

machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.;

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Machine Learning for Cyber Security

machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.;

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Guide to Convolutional Neural Networks

on using libraries to implement ConvNets in applications of traffic sign detection and classification. The work presents techniques for;

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Guide to Convolutional Neural Networks

on using libraries to implement ConvNets in applications of traffic sign detection and classification. The work presents techniques for;

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Mastering Machine Learning for Penetration Testing

Become a master at penetration testing using machine learning with Python Key Features Identify ambiguities and breach intelligent security;

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Detection of Intrusions and Malware, and Vulnerability Assessment

assessment, dealing with novel ideas, techniques, and applications in important areas of computer security including vulnerability detection, attack;

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An Introduction to Machine Learning

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using;

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Machine Learning and Cognitive Science Applications in Cyber Security

In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a;

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Machine Learning with TensorFlow

matrices. About the technology TensorFlow, Google's library for large-scale machine learning, makes powerful ML techniques easily;

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Information and Communications Security

in topics on malware analysis and detection, IoT and CPS security enterprise network security, software security, system security, authentication;

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Hands-On Neural Networks with TensorFlow 2.0

transition to TF 2.0 Solve any deep learning problem by developing neural network-based solutions using TF 2.0 Book DescriptionTensorFlow, the most;

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Data Mining Tools for Malware Detection

-step breakdown of how to develop data mining tools for malware detection. Integrating theory with practical techniques and experimental results;

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An Introduction to Machine Learning

This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches;

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Handbook of Big Data Analytics and Forensics

learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the;

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