BlockDeepNet: A Blockchain-Based Secure Deep Learning for IoT Network

被引：64

作者：

Rathore, Shailendra ^{[1
]}

Pan, Yi ^{[2
]}

Park, Jong Hyuk ^{[1
]}

机构：

[1] Seoul Natl Univ Sci & Technol, Dept Comp Sci & Engn, Seoul 01811, South Korea

[2] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30302 USA

来源：

SUSTAINABILITY | 2019年 / 11卷 / 14期

关键词：

IoT; deep learning; blockchain; security and privacy; collaborative deep learning; FRAMEWORK;

D O I：

10.3390/su11143974

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The recent development in IoT and 5G translates into a significant growth of Big data in 5G-envisioned industrial automation. To support big data analysis, Deep Learning (DL) has been considered the most promising approach in recent years. Note, however, that designing an effective DL paradigm for IoT has certain challenges such as single point of failure, privacy leak of IoT devices, lack of valuable data for DL, and data poisoning attacks. To this end, we present BlockDeepNet, a Blockchain-based secure DL that combines DL and blockchain to support secure collaborative DL in IoT. In BlockDeepNet, collaborative DL is performed at the device level to overcome privacy leak and obtain enough data for DL, whereas blockchain is employed to ensure the confidentiality and integrity of collaborative DL in IoT. The experimental evaluation shows that BlockDeepNet can achieve higher accuracy for DL with acceptable latency and computational overhead of blockchain operation.

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