Privacy-Preserving Support Vector Machine Training Over Blockchain-Based Encrypted IoT Data in Smart Cities

Machine learning (ML) techniques have been widely used in many smart city sectors, where a huge amount of data is gathered from various (IoT) devices. As a typical ML model, support vector machine (SVM) enables efficient data classification and thereby finds its applications in real-world scenarios,...

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Vydané v:	IEEE internet of things journal Ročník 6; číslo 5; s. 7702 - 7712
Hlavní autori:	Shen, Meng, Tang, Xiangyun, Zhu, Liehuang, Du, Xiaojiang, Guizani, Mohsen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.10.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Anomalies Blockchain Computational modeling Cryptography Data models Data privacy Data retrieval Distributed ledger encrypted Internet of Things (IoT) data Encryption homomorphic cryptosystem (HC) Internet of Things Iterative methods Machine learning machine learning (ML) Multiplication Polynomials Privacy privacy protection Smart cities Support vector machines Training Trusted third parties
ISSN:	2327-4662, 2327-4662
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