2019 GDRR: Blockchain Data Analytics - Machine Learning in/for Blockchain: Future and Challenges - Hong Wan, October 7, 2019
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The document discusses the integration of machine learning with blockchain technology, highlighting its applications in transaction categorization, price prediction, and resource allocation. It addresses the challenges and design questions for blockchain systems, such as data access and validation. The potential futures include improving blockchain design using machine learning and facilitating secure data sharing.
2019 GDRR: Blockchain Data Analytics - Machine Learning in/for Blockchain: Future and Challenges - Hong Wan, October 7, 2019
- 1. Machine Learning in/for Blockchain: Future and Challenges *Fang Chen, ***Hong Wan, *Hui Cai, and **Guang Cheng, *School of Industrial Engineering, Purdue University **Department of Statistics, Purdue University ***Edward P. Fitts Department of Industrial and Systems Engineering Oct 2019
- 2. In this talk: • Incorporating machine learning into blockchain algorithms or frameworks • Analyzing attributes or applications of blockchain using machine learning methods • Blockchain-based learning systems • Blockchain beyond cryptocurrency • Design and characterize the blockchain systems
- 4. Learning as a Prediction and Analysis Tool https://www.google.com/url?sa=i&source=images&cd=&ved=2ahUKEwj G4oqbp4nlAhUCQq0KHS3- CiYQjRx6BAgBEAQ&url=https%3A%2F%2Fblue-sea-697d.quartiers047.workers.dev%3A443%2Fhttps%2Fcointelegraph.com%2Fnews%2 Fbtc-price-rebounds-from-7-700-crypto-traders-hope-for-relief- rally&psig=AOvVaw2Nx-Z1btIKD3iRAf5Rrmxp&ust=1570508630461698 https://blog.emsisoft.com/wp-content/uploads/2019/09/ransomware-bitcoin.png
- 5. Transaction Categorization • Supervised learning to detect cybercriminal activities • Categorizing all transactions into: Exchange, Service, Gambling, and Mining Pool. • Topology-based methods to detect abnormal behaviors
- 6. Cryptocurrency Price Prediction • Topology based methods: chainlet • Bayesian regression for “latent source model" • Cryptocurrency price prediction and digital portfolio management using Recurrent Neural Network (RNN) and Long-Short Term Memory • Reinforcement-learning based portfolio optimization
- 7. Computational Resource Allocation • Deep-learning based auction algorithm for edge computing resources allocation to support mobile mining activities. • Mobile device miners will submit their bid valuation profiles to one Edge Computing Service Provider (ECSP) for buying additional computing power. • ECSP want to maximize its revenue.
- 8. Blockchain for Machine Learning • Decentralized privacy-preserving and secure machine learning system without a trusted central server. • IOT sensors with reinforcement learning abilities share data through a blockchain network. • Is public chain the right choice? Video Simulation
- 9. Futures and Challenges Machine learning to help design better blockchain systems; and blockchain to facilitate data sharing and verification
- 10. Blockchain Design Questions • Who can access data: Private vs. Public • Who can validate data/add block: Permissioned vs Permissionless • Consensus to be used: Trade-off among security and efficiency. https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=2ahUKEwinjN2s7_DkAhXlmeAKHXxhAIUQjRx6BAgBEAQ&url=ht tps%3A%2F%2F101blockchains.com%2Fconsensus-algorithms-blockchain%2F&psig=AOvVaw23pKh4qS8W_xgyajJ3aFl9&ust=1569669093339830
- 11. Challenges for Each Type • Permissionless-public chain: scalability and privacy • Permissioned-public chain: centralization and privacy • Permissionless-private chain: scalability and consensus • Permissioned-private chain: centralization and consensus https://medium.com/ltonetwork/the-rise-of-private-permissionless-blockchains- part-1-4c39bea2e2be
- 12. Bad News First • “Private blockchains are completely uninteresting… -- the only reason to operate one is to ride on the blockchain hype…” Bruce Schneier https://www.schneier.com/blog/archives/2019/02/blockchain_and_.html http://shorturl.at/ahsRU, shorturl.at/gETV2 Tonight we will talk about cryptocurrencies… .everything you don’t understand money combined by everything you don’t understand about computers…. Cryptocurrencies: Last Week Tonight with John Oliver (HBO)
- 14. Blockchain for Bitcoin and Business • Assets and records vs. Coins • Identity vs anonymity: different trust level • Data privacy vs open ledger • Efficiency vs security https://ibm.co/2xYSoGy
- 15. How Machine Learning can Help? • Deciding the system dynamics and behaviors Game theory modeling Input modeling of various simulation models utility function of smart agents Stress test
- 16. How Blockchain can Help • Connecting multiple blockchains. • Data fusion • Multi-level network: Centralization in some levels and decentralized in other levels.
- 17. Journal of Blockchain Research • System design and analysis • Distributed data storage • Security and privacy • Trust and certifications • Mathematics of blockchain • Data science of blockchain
- 18. Journal of Blockchain Research • Economics, finance and social science of blockchain • Manufacturing and blockchain • Cognitive and behavioral science of blockchain • Supply chain and service operations with blockchain • Case studies of blockchain • Reviews and Discussions of blockchain technology’s challenges, criticism and futures.
- 19. Discussions
- 21. Blockchain vs Shared Database • Private chain is a shared database with one or multiple parties with administrative power. • Private chain still make use of cryptography and data structures (like Merkle trees) to ensure non- valid transactions aren’t added to the blockchain and data are immutable • Higher levels of error checking and transaction validity than regular shared databases.
- 22. Blockchain As a System of Record • Digital identity: all four kinds. • Tokenization: private or public, permissioned • Inter-organizational data management: permissioned, private • Usage: government, financial institutes, auditing... https://www.coindesk.com/information/applications-use-cases-blockchains https://i.ytimg.com/vi/1bVczDqh7_A/maxresdefault.jpg
- 23. Blockchain as A Platform • Smart contracting • automated governance • Market without middleman • automating regulatory compliance https://static.coindesk.com/wp-content/uploads/2017/03/Screen-Shot-2017-03-28-at-5.43.08-PM.png https://storefoundry.s3.amazonaws.com/store_items/images/000/013/039/large/7.jpg?1561546577
- 24. Ripple Coin
- 25. Hybrid Chain • Connecting multiple blockchains. • Data fusion • Multi-level network: Centralization in some levels and decentralized in other levels.