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

机译:BlockDeepNet:基于Slinchain的IoT网络安全深度学习

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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.
机译:IOT和5G最近的发展转化为5G-Envisioned工业自动化中大数据的显着增长。为了支持大数据分析,深度学习(DL)近年来被认为是最有希望的方法。但请注意,为IOT设计有效的DL范例具有某些挑战,例如单点故障,隐私泄漏的IOT设备,缺乏DL的有价值的数据以及数据中毒攻击。为此,我们呈现BlockDeepNet,基于区块链的安全DL,该基于SCRED DL,该安全DL组合了DL和Slarthchain,以支持IOT中的安全协作DL。在BlockDeepNet中,在设备级执行协作DL以克服隐私泄漏并获得足够的DL数据,而区块链用于确保IOT中协作DL的机密性和完整性。实验评估表明,BlockDeepNet可以实现更高的DL的准确性,具有块线操作的可接受等待时间和计算开销。

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