Hwanjo Heo (ETRI), Seungwon Woo (ETRI/KAIST), Taeung Yoon (KAIST), Min Suk Kang (KAIST), Seungwon Shin (KAIST)

We present a practical partitioning attack, which we call Gethlighting, that isolates an Ethereum full node from the rest of the network for hours without having to occupy (or eclipse) all of the target’s peer connections. In Gethlighting, an adversary controls only about a half (e.g., 25 out of total 50) of all peer connections of a target node, achieving powerful partitioning with a small attack budget of operating several inexpensive virtual machines. At the core of Gethlighting, its low-rate denial-of-service (DoS) strategy effectively stops the growth of local blockchain for hours while leaving other Ethereum node operations undisturbed. We analyze how subtle and insignificant delays incurred by a low-rate DoS can lead to a powerful blockchain partitioning attack. The practical impact of Gethlighting is discussed — i.e., the attack is scalable and low-cost (only about $5,714 for targeting all Ethereum full nodes concurrently for 24 hours), and extremely simple to launch. We demonstrate the feasibility of Gethlighting with full nodes in the Ethereum mainnet and testnet in both controlled and real-world experiments. We identify a number of fundamental system characteristics in Ethereum that enable Gethlighting attacks and propose countermeasures that require some protocol and client implementation enhancements. Ethereum Foundation has acknowledged this vulnerability in September 2022 and one of our countermeasures has been accepted as a hotfix for Geth 1.11.0.

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OptRand: Optimistically Responsive Reconfigurable Distributed Randomness

Adithya Bhat (Purdue University), Nibesh Shrestha (Rochester Institute of Technology), Aniket Kate (Purdue University), Kartik Nayak (Duke University)

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Sometimes, You Aren’t What You Do: Mimicry Attacks against...

Akul Goyal (University of Illinois at Urbana-Champaign), Xueyuan Han (Wake Forest University), Gang Wang (University of Illinois at Urbana-Champaign), Adam Bates (University of Illinois at Urbana-Champaign)

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HeteroScore: Evaluating and Mitigating Cloud Security Threats Brought by...

Chongzhou Fang (University of California, Davis), Najmeh Nazari (University of California, Davis), Behnam Omidi (George Mason University), Han Wang (Temple University), Aditya Puri (Foothill High School, Pleasanton, CA), Manish Arora (LearnDesk, Inc.), Setareh Rafatirad (University of California, Davis), Houman Homayoun (University of California, Davis), Khaled N. Khasawneh (George Mason University)

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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