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20182021
most citedTowards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition

14 citations · 34 across the 9 of their papers we have counts for

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cs.CR2021

Lifting The Grey Curtain: A First Look at the Ecosystem of CULPRITWARE

Zhuo Chen, Lei Wu, Jing Cheng +6

Mobile apps are extensively involved in cyber-crimes. Some apps are malware which compromise users' devices, while some others may lead to privacy leakage. Apart from them, there a…

cs.CR20215 cited

A Measurement Study on the (In)security of End-of-Life (EoL) Embedded Devices

Dingding Wang, Muhui Jiang, Rui Chang +5

Embedded devices are becoming popular. Meanwhile, researchers are actively working on improving the security of embedded devices. However, previous work ignores the insecurity caus…

cs.CR2021

Revisiting Challenges for Selective Data Protection of Real Applications

Lin Ma, Jinyan Xu, Jiadong Sun +5

Selective data protection is a promising technique to defend against the data leakage attack. In this paper, we revisit technical challenges that were neglected when applying this…

cs.CR2021

Automatically Locating ARM Instructions Deviation between Real Devices and CPU Emulators

Muhui Jiang, Tianyi Xu, Yajin Zhou +5

Emulator is widely used to build dynamic analysis frameworks due to its fine-grained tracing capability, full system monitoring functionality, and scalability of running on differe…

cs.CR2021

DeFiRanger: Detecting Price Manipulation Attacks on DeFi Applications

Siwei Wu, Dabao Wang, Jianting He +5

The rapid growth of Decentralized Finance (DeFi) boosts the Ethereum ecosystem. At the same time, attacks towards DeFi applications (apps) are increasing. However, to the best of o…

cs.CR20213 cited

e-PoS: Making Proof-of-Stake Decentralized and Fair

Muhammad Saad, Zhan Qin, Kui Ren +2

Blockchain applications that rely on the Proof-of-Work (PoW) have increasingly become energy inefficient with a staggering carbon footprint. In contrast, energy-efficient alternati…