Daniel Perez (Imperial College London), Benjamin Livshits (Imperial College London, UCL Centre for Blockchain Technologies, and Brave Software)

Metering is an approach developed to assign cost to smart contract execution in blockchain systems such as Ethereum. This paper presents a detailed investigation of the metering approach based on emph{gas} taken by the Ethereum blockchain. We discover a number of discrepancies in the metering model such as significant inconsistencies in the pricing of the instructions. We further demonstrate that there is very little correlation between the gas and resources such as CPU and memory. We find that the main reason for this is that the gas price is dominated by the amount of emph{storage} that is used.

Based on the observations above, we present a new type of DoS attack we call~emph{Resource Exhaustion Attack}, which uses these imperfections to generate low-throughput contracts. Using this method, we show that we are able to generate contracts with a throughput on average 50 times slower than typical contracts. These contracts can be used to prevent nodes with lower hardware capacity from participating in the network, thereby artificially reducing the level of centralization the network can deliver.

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William Blair (Boston University), Andrea Mambretti (Northeastern University), Sajjad Arshad (Northeastern University), Michael Weissbacher (Northeastern University), William Robertson (Northeastern University), Engin Kirda (Northeastern University), Manuel Egele (Boston University)

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Shivam Bhasin (Nanyang Technological University), Anupam Chattopadhyay (Nanyang Technological University), Annelie Heuser (Univ Rennes, Inria, CNRS, IRISA), Dirmanto Jap (Nanyang Technological University), Stjepan Picek (Delft University of Technology), Ritu Ranjan Shrivastwa (Secure-IC)

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Qinhan Tan (Zhejiang University), Zhihua Zeng (Zhejiang University), Kai Bu (Zhejiang University), Kui Ren (Zhejiang University)

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DeepBinDiff: Learning Program-Wide Code Representations for Binary Diffing

Yue Duan (Cornell University), Xuezixiang Li (UC Riverside), Jinghan Wang (UC Riverside), Heng Yin (UC Riverside)

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