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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Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning

Harsh Chaudhari (Indian Institute of Science, Bangalore), Rahul Rachuri (Aarhus University, Denmark), Ajith Suresh (Indian Institute of Science, Bangalore)

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You Are What You Do: Hunting Stealthy Malware via...

Qi Wang (University of Illinois Urbana-Champaign), Wajih Ul Hassan (University of Illinois Urbana-Champaign), Ding Li (NEC Laboratories America, Inc.), Kangkook Jee (University of Texas at Dallas), Xiao Yu (NEC Laboratories America, Inc.), Kexuan Zou (University Of Illinois Urbana-Champaign), Junghwan Rhee (NEC Laboratories America, Inc.), Zhengzhang Chen (NEC Laboratories America, Inc.), Wei Cheng (NEC Laboratories America,…

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HFL: Hybrid Fuzzing on the Linux Kernel

Kyungtae Kim (Purdue University), Dae R. Jeong (KAIST), Chung Hwan Kim (NEC Labs America), Yeongjin Jang (Oregon State University), Insik Shin (KAIST), Byoungyoung Lee (Seoul National University)

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FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic

Thijs van Ede (University of Twente), Riccardo Bortolameotti (Bitdefender), Andrea Continella (UC Santa Barbara), Jingjing Ren (Northeastern University), Daniel J. Dubois (Northeastern University), Martina Lindorfer (TU Wien), David Choffnes (Northeastern University), Maarten van Steen (University of Twente), Andreas Peter (University of Twente)

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