Machine Learning and Cognitive Science Applications in Cyber Security
- 5h 27m
- Muhammad Salman Khan
- IGI Global
- 2019
In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a variety of sources have been exposed to possible corruption and hacking. Machine learning, artificial intelligence, predictive analytics, and similar disciplines of cognitive science applications have been found to have significant applications in the domain of cyber security.
Machine Learning and Cognitive Science Applications in Cyber Security examines different applications of cognition that can be used to detect threats and analyze data to capture malware. Highlighting such topics as anomaly detection, intelligent platforms, and triangle scheme, this publication is designed for IT specialists, computer engineers, researchers, academicians, and industry professionals interested in the impact of machine learning in cyber security and the methodologies that can help improve the performance and reliability of machine learning applications.
In this Book
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Healthcare Information Security in the Cyber World
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A Machine Learning Approach for Predicting Bank Customer Behavior in the Banking Industry
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Advanced-Level Security in Network and Real-Time Applications Using Machine Learning Approaches
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New Tools for Cyber Security Using Blockchain Technology and Avatar-Based Management Technique
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Machine Learning Application With Avatar-Based Management Security to Reduce Cyber Threat
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Machine Learning With Avatar-Based Management of Sleptsov Net-Processor Platform to Improve Cyber Security
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Intelligent Log Analysis Using Machine and Deep Learning
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Password-Less Authentication: Methods for User Verification and Identification to Login Securely Over Remote Sites
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A Novel Bat Algorithm for Line-of-Sight Localization in Internet of Things and Wireless Sensor Network
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Ensemble Learning Mechanisms for Threat Detection: A Survey
