东北大学刘园副教授学术报告 11月8日下午

发布时间:2021-11-07浏览次数:177


报告题目:Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains

时间:2021118(星期一) 15:00 ~ 17:00

地点:腾讯会议ID639287611

主讲:刘园

主办:计算机与网络空间安全学院, 福建省网络安全与密码技术重点实验室

参加对象:计网学院网安系感兴趣的老师和学生

 

报告摘要:The progress of deep learning (DL), especially the recent development of automatic design of networks, has brought unprecedented performance gains at heavy computational cost. On the other hand, blockchain systems routinely perform a huge amount of computation that does not achieve practical purposes in order to build Proof-of-Work (PoW) consensus from decentralized participants. In this study, we propose a new consensus mechanism, Proof of Learning (PoLe), which directs the computation spent for consensus toward optimization of neural networks (NN). In our mechanism, the training/testing data are released to the entire blockchain network (BCN) and the consensus nodes train NN models on the data, which serves as the proof of learning. When the consensus on the BCN considers a NN model to be valid, a new block is appended to the blockchain. We experimentally compare the PoLe protocol with Proof of Work (PoW) and show that PoLe can achieve a more stable block generation rate, which leads to more efficient transaction processing. We also introduce a novel cheating prevention mechanism, Secure Mapping Layer (SML), which can be straightforwardly implemented as a linear NN layer. Empirical evaluation shows that SML can detect cheating nodes at small cost to the predictive performance.

 

专家简介:刘园,东北大学副教授,引进人才,CCF区块链专委会通信委员,中国通信学会区块链专委会委员。201411月于新加坡南洋理工大学计算机工程学院获博士学位,201007月于哈尔滨工业大学实验学院获学士学位。主要研究领域包括区块链核心算法、区块链物联网、区块链大数据、区块链机器学习、医疗健康区块链应用等。主持和参与国家自然基金3项,省级以上重点项目4项,发表学术重要论文40余篇。主讲《区块链技术》、《博弈论》等课程。