Elijah Bouma-Sims (Carnegie Mellon University), Lily Klucinec (Carnegie Mellon University), Mandy Lanyon (Carnegie Mellon University), Julie Downs (Carnegie Mellon University), Lorrie Faith Cranor (Carnegie Mellon University)

Fraudsters often use the promise of free goods as a lure for victims who are convinced to complete online tasks but ultimately receive nothing. Despite much work characterizing these "giveaway scams," no human subjects research has investigated how users interact with them or what factors impact victimization. We conducted a scenario-based experiment with a sample of American teenagers (n = 85) and adult crowd workers (n = 205) in order to investigate how users reason about and interact with giveaway scams advertised in YouTube videos and to determine whether teens are more susceptible than adults. We found that most participants recognized the fraudulent nature of the videos, with only 9.2% believing the scam videos offered legitimate deals. Teenagers did not fall victim to the scams more frequently than adults but reported more experience searching for terms that could lead to victimization. This study is among the first to compare the interactions of adult and teenage users with internet fraud and sheds light on an understudied area of social engineering.

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Retrofitting XoM for Stripped Binaries without Embedded Data Relocation

Chenke Luo (Wuhan University), Jiang Ming (Tulane University), Mengfei Xie (Wuhan University), Guojun Peng (Wuhan University), Jianming Fu (Wuhan University)

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LLMPirate: LLMs for Black-box Hardware IP Piracy

Vasudev Gohil (Texas A&M University), Matthew DeLorenzo (Texas A&M University), Veera Vishwa Achuta Sai Venkat Nallam (Texas A&M University), Joey See (Texas A&M University), Jeyavijayan Rajendran (Texas A&M University)

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Kronos: A Secure and Generic Sharding Blockchain Consensus with...

Yizhong Liu (Beihang University), Andi Liu (Beihang University), Yuan Lu (Institute of Software Chinese Academy of Sciences), Zhuocheng Pan (Beihang University), Yinuo Li (Xi’an Jiaotong University), Jianwei Liu (Beihang University), Song Bian (Beihang University), Mauro Conti (University of Padua)

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KernelSnitch: Side Channel-Attacks on Kernel Data Structures

Lukas Maar (Graz University of Technology), Jonas Juffinger (Graz University of Technology), Thomas Steinbauer (Graz University of Technology), Daniel Gruss (Graz University of Technology), Stefan Mangard (Graz University of Technology)

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