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Privacy and Security Issues in Data Mining and Machine Learning

This book constitutes the refereed proceedings of the International ECML/PKDD Workshop on Privacy and Security Issues in Data Mining and;

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The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the;

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical;

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical;

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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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Advanced Data Mining and Applications

Systems; Privacy and Security; Query Processing; Data Mining Applications.;

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Data Mining and Machine Learning in Cybersecurity

learning and data mining solutions Details privacy-preserving data mining methods This interdisciplinary resource includes technique review;

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Proceedings of ICETIT 2019

This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data;

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Proceedings of ICETIT 2019

This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data;

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Security and Privacy Issues in IoT Devices and Sensor Networks

Security and Privacy Issues in IoT Devices and Sensor Networks investigates security breach issues in IoT and sensor networks;

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Recent Advances in Artificial Intelligence and Data Engineering

, data science, high performance computing, data mining and knowledge discovery, and data privacy and security. The book will be a valuable;

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Privacy, Security, and Trust in KDD

incorporate reviewers' comments and discussions at the workshop and represent the diversity of data mining research issues in privacy, security, and;

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Availability, Reliability, and Security in Information Systems

, Reliability and Security in Information Systems, CD-ARES 2016, and the Workshop on Privacy Aware Machine Learning for Health Data Science, PAML 2016;

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Advances in Knowledge Discovery and Data Mining

in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining;

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Advances in Knowledge Discovery and Data Mining

in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining;

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Machine Learning and Data Mining in Aerospace Technology

This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites;

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Security and Privacy for Big Data, Cloud Computing and Applications

As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and;

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Privacy

In this book, the authors present current research in the study of the management, legal issues and security aspects relating to privacy;

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Federated Learning

This book shows how federated machine learning allows multiple data owners to collaboratively train and use a shared prediction model while;

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Federated Learning

This book shows how federated machine learning allows multiple data owners to collaboratively train and use a shared prediction model while;

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Web Information Systems and Applications

submissions. The papers are grouped in topical sections on machine learning and data mining, cloud computing and big data, information retrieval;

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Privacy and Security Issues in Big Data

This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements;

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Machine Learning and Big Data Analytics Paradigms

many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for;

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Web Information Systems and Applications

learning, graph query, edge computing and data mining, data privacy and security, and blockchain.;

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Web Information Systems and Applications

103 submissions. The papers cover topics such as machine learning and data mining; cloud computing and big data; information retrieval;

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