Issue #37
Paper of the Week:
Paper Title: SquirRL: Automating Attack Discovery on Blockchain Incentive Mechanisms with Deep Reinforcement Learning.
TLDR:
Today, attacks on blockchain incentive mechanisms are typically discovered through a lengthy process of modeling and theoretical analysis. In addition, the difficulty of obtaining general theoretical results in this area is well-known.
This work proposes a framework for discovering attacks on blockchain incentive mechanisms using deep reinforcement learning. It is intended as a general-purpose methodology for blockchain developers to test incentive mechanisms for vulnerabilities and it does not provide theoretical guarantees.
The proposed work is applied to various blockchain protocols and is able to recover known theoretical selfish mining results in the Bitcoin protocol, while also extending state-of-the-art results to domains that were previously intractable (e.g., the multi-agent setting, larger state spaces, other protocols).
The results suggest that in the Bitcoin protocol, as the number of agents increases, selfish mining and its variants become progressively less profitable. This is consistent with the fact that selfish mining has been unobserved in the wild (to the best of our knowledge), although it is unclear whether this observation or other externalities are the reason.
Additionally, the experiments provide results about multi- agent settings that have previously been challenging to analyze theoretically.
Finally, this paper shows that the proposed work is generally applicable to attacks on incentive mechanisms beyond selfish mining.
Authors: Charlie Hou*†, Mingxun Zhou‡, Yan Ji†§, Phil Daian†§, Florian Tramer✜, Giulia Fanti*†, and Ari Juels†§,
Affiliations: * Carnegie Mellon University, † IC3, ‡ Peking University, § Cornell Tech, and ✜ Stanford University.
Security:
1. Paper Title: Improvements of the Balance Discovery Attack on Lightning Network Payment Channels.
Summary: Potential Balance Discovery Attack (BDA) algorithm improvements and the role of LN client software in BDA.
Authors: Gijs van Dam*, Rabiah Abdul Kadir*, Puteri N.E. Nohuddin*, and Halimah Badioze Zaman*,
Affiliations: * The National University of Malaysia.
Privacy:
No papers.
Scalability:
1. Paper Title: Randpay: The Technology for Blockchain Micropayments and Transactions Which Require Recipient’s Consent.
Summary: A sustainable technology for micropayments.
Authors: Oleksii Konashevych* and Oleg Khovayko†,
Affiliations: * Erasmus Mundus and † Emercoin.
Proofs:
No papers.
Consensus:
1. Paper Title: When Blockchain Meets AI: Optimal Mining Strategy Achieved By Machine Learning.
Summary: This work employs RL to dynamically learn a mining strategy with performance approaching that of the optimal mining strategy by observing and interacting with the network.
Authors: Taotao Wang*, Soung Chang Liew†, and Shengli Zhang*,
Affiliations: * Shenzhen University and † The Chinese University of Hong Kong.
Tokenomics:
1. Paper Title: Blockchain Governance for Technologists.
Summary: A brief tutorial-style introduction to institutional economics, which is one of the important frameworks for thinking about the economic aspects of blockchain systems.
Authors: Martin Weiss, Ilia Murtazashvili*, Jennifer Murtazashvili*, Marcela Gomez*, and Amy Babay,
Affiliations: * University of Pittsburgh.
2. Paper Title: More (or Less) Economic Limits of the Blockchain.
Summary: This paper extends the blockchain sustainability framework of Budish (2018) to consider proof of stake (in addition to proof of work) consensus mechanisms and permissioned (where the number of nodes are fixed) networks.
Authors: Neil Gandal* and Joshua S. Gans†,
Affiliations: * Tel Aviv University and † University of Toronto.
Upcoming Conferences:
Feb 10-14 - Financial Cryptography and Data Security 2020(Malaysia)
Feb 19-21 - Stanford Blockchain Conference 2020 (Palo Alto)
March 07-08 - Cryptoeconomic Systems Conference 2020 by MIT Press (Boston)
April 13-16 - The 2nd IEEE International Conference on Decentralized Applications and Infrastructures (IEEE DAPPS 2020) (Oxford)
Past Conferences’ Videos:
Jobs:
“Significant research in the blockchain space is constantly being achieved by academic researchers. Unfortunately, a lot of this research is overlooked due to the massive numbers of papers being generated and the way they are being promoted and published. We’ve put together a categorized list of academic papers that can guide our subscribers and keep them up to date.”
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