Understanding Ethereum via Graph Analysis

@article{Chen2018UnderstandingEV,
  title={Understanding Ethereum via Graph Analysis},
  author={Ting Chen and Yuxiao Zhu and Zihao Li and Jiachi Chen and Xiaoqi Li and Xiapu Luo and Xiaodong Lin and Xiaosong Zhang},
  journal={IEEE INFOCOM 2018 - IEEE Conference on Computer Communications},
  year={2018},
  pages={1484-1492}
}
Being the largest blockchain with the capability of running smart contracts, Ethereum has attracted wide attention and its market capitalization has reached 20 billion USD. [] Key Method We design a new approach to collect all transaction data, construct three graphs from the data to characterize major activities, and discover new observations and insights from these graphs. Moreover, we propose new approaches based on cross-graph analysis to address two security issues in Ethereum. The evaluation through…
Understanding Ethereum via Graph Analysis
TLDR
The first systematic study on Ethereum is conducted by leveraging graph analysis to characterize three major activities on Ethereum, namely money transfer, smart contract creation, and smart contract invocation, and address three security issues based on graphs.
DataEther: Data Exploration Framework For Ethereum
  • Ting Chen, Teng Hu, Shifang Deng
  • Computer Science
    2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)
  • 2019
TLDR
This paper proposes DataEther, a systematic and high-fidelity data exploration framework for Ethereum by exploiting its internal mechanisms and further empowers users to explore unknown phenomena and obtain in-depth understandings.
Ethereum Analysis via Node Clustering
TLDR
This paper applies machine learning in Ethereum analysis for the first time and cluster users and smart contract into groups by using transaction information in existing blocks and proposes a new way of user identity discrimination and malicious user detection.
Evolution of Ethereum: A Temporal Graph Perspective
TLDR
A data analytics platform is developed to collect external transactions associated with users as well as internal transactions initiated by smart contracts, and the Gini indexes of the transaction graphs and the user wealth in which Ethereum is found to be very unfair since the very beginning.
A Behavior-Aware Profiling of Smart Contracts
TLDR
A behavior-aware profiling of individual smart contract from a multi-party perspective is presented, which improves the visibility of the smart contract ecosystem and effectively complements previous work towards generating a comprehensive understanding of smart contracts.
Modeling and Understanding Ethereum Transaction Records via a Complex Network Approach
TLDR
This work first model the Ethereum transaction records as a complex network by incorporating time and amount features of the transactions, and then design several flexible temporal walk strategies for random-walk based graph representation of this large-scale network.
Understanding (Mis)Behavior on the EOSIO Blockchain
TLDR
A large-scale measurement study of the EOSIO blockchain and its associated DApps is performed and thousands of bot accounts are discovered and a number of real-world attacks are discovered, especially related to security and fraud.
Temporal Analysis of the Entire Ethereum Blockchain Network
TLDR
This paper studies the growth rate and model of four Ethereum blockchain networks, active lifespan and update rate of high-degree vertices, and forecast the survival of network communities in succeeding months leveraging on the relevant graph features and machine learning models.
Characterizing EOSIO Blockchain
TLDR
This paper gathers a large-scale dataset of EOSIO and characterize activities including money transfers, account creation and contract invocation, and develops techniques to automatically detect bots and fraudulent activity.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 54 REFERENCES
Understanding Ethereum via Graph Analysis
TLDR
The first systematic study on Ethereum is conducted by leveraging graph analysis to characterize three major activities on Ethereum, namely money transfer, smart contract creation, and smart contract invocation, and address three security issues based on graphs.
Making Smart Contracts Smarter
TLDR
This paper investigates the security of running smart contracts based on Ethereum in an open distributed network like those of cryptocurrencies, and proposes ways to enhance the operational semantics of Ethereum to make contracts less vulnerable.
Analyzing Ethereum's Contract Topology
TLDR
This paper examines how contracts in Ethereum are created, and how users and contracts interact with one another, and finds that contracts today are three times more likely to be created by other contracts than they are by users, and that over 60% of contracts have never been interacted with.
Under-optimized smart contracts devour your money
TLDR
This work conducts the first investigation on Solidity, the recommended compiler, and reveals that it fails to optimize gas- costly programming patterns, and proposes and develops GASPER, a new tool for automatically locating gas-costly patterns by analyzing smart contracts' bytecodes.
Towards Saving Money in Using Smart Contracts
  • Ting Chen, Zihao Li, Xiaosong Zhang
  • Computer Science
    2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER)
  • 2018
TLDR
GasReducer is designed and developed, the first tool to automatically detect all these anti-patterns from the bytecode of smart contracts and replace them with efficient code through bytecode-to-bytecode optimization.
Network Analysis of ERC20 Tokens Trading on Ethereum Blockchain
TLDR
This work is the first analysis of the network properties of the ERC20 protocol compliant crypto-coins’ trading data, demonstrating that the network displays strong power-law properties, coinciding with current network theory expectations.
Erays: Reverse Engineering Ethereum's Opaque Smart Contracts
TLDR
This work presents Erays, a reverse engineering tool for smart contracts that takes in smart contract from the Ethereum blockchain, and produces high-level pseudocode suitable for manual analysis, and leverages it to link contracts with no previously available source code to public source code, thus reducing the overall opacity in the ecosystem.
Securify: Practical Security Analysis of Smart Contracts
TLDR
An extensive evaluation of Securify over real-world Ethereum smart contracts is presented and it is demonstrated that it can effectively prove the correctness of smart contracts and discover critical violations.
MadMax: surviving out-of-gas conditions in Ethereum smart contracts
TLDR
MadMax is presented: a static program analysis technique to automatically detect gas-focused vulnerabilities with very high confidence and achieves high precision and scalability.
An Adaptive Gas Cost Mechanism for Ethereum to Defend Against Under-Priced DoS Attacks
TLDR
This paper proposes a novel gas cost mechanism, which dynamically adjusts the costs of EVM operations according to the number of executions, to thwart DoS attacks and designs a special smart contract that collaborates with the updated EVM for dynamic parameter adjustment.
...
1
2
3
4
5
...