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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SymTCP: Eluding Stateful Deep Packet Inspection with Automated Discrepancy...

Zhongjie Wang (University of California, Riverside), Shitong Zhu (University of California, Riverside), Yue Cao (University of California, Riverside), Zhiyun Qian (University of California, Riverside), Chengyu Song (University of California, Riverside), Srikanth V. Krishnamurthy (University of California, Riverside), Kevin S. Chan (U.S. Army Research Lab), Tracy D. Braun (U.S. Army Research Lab)

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HYPER-CUBE: High-Dimensional Hypervisor Fuzzing

Sergej Schumilo (Ruhr-Universität Bochum), Cornelius Aschermann (Ruhr-Universität Bochum), Ali Abbasi (Ruhr-Universität Bochum), Simon Wörner (Ruhr-Universität Bochum), Thorsten Holz (Ruhr-Universität Bochum)

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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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Adversarial Classification Under Differential Privacy

Jairo Giraldo (University of Utah), Alvaro Cardenas (UC Santa Cruz), Murat Kantarcioglu (UT Dallas), Jonathan Katz (George Mason University)

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