Hetvi Shastri (University of Massachusetts Amherst), Akanksha Atrey (Nokia Bell Labs), Andre Beck (Nokia Bell Labs), Nirupama Ravi (Nokia Bell Labs)

The recent emergence of decentralized wireless networks empowers individual entities to own, operate, and offer subscriptionless connectivity services in exchange for monetary compensation. While traditional connectivity providers have built trust over decades through widespread adoption, established practices, and regulation, entities in a decentralized wireless network, lacking this foundation, may be incentivized to exploit the service for their own advantage. For example, a dishonest hotspot operator can intentionally violate the agreed upon connection terms in an attempt to increase their profits. In this paper, we examine and develop a taxonomy of adversarial behavior patterns in decentralized wireless networks. Our case study finds that provider-driven attacks can potentially more than triple provider earnings. We conclude the paper with a discussion on the critical need to develop novel techniques to detect and mitigate adversarial behavior in decentralized wireless networks.

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SIGuard: Guarding Secure Inference with Post Data Privacy

Xinqian Wang (RMIT University), Xiaoning Liu (RMIT University), Shangqi Lai (CSIRO Data61), Xun Yi (RMIT University), Xingliang Yuan (University of Melbourne)

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Diffence: Fencing Membership Privacy With Diffusion Models

Yuefeng Peng (University of Massachusetts Amherst), Ali Naseh (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst)

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Iris: Dynamic Privacy Preserving Search in Authenticated Chord Peer-to-Peer...

Angeliki Aktypi (University of Oxford), Kasper Rasmussen (University of Oxford)

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