arXiv:2610.27152v1 Announce Type: new Abstract: Neural networks (NNs) are increasingly deployed on edge devices such as mobile and IoT platforms, offering low latency and improved privacy compared to cloud-based deployment.
Model Exposure on One Device Endangers Others: Rethinking Edge Neural Network Security across Devices
About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.27152
Source attribution: headline and facts are from arXiv cs.CR (arxiv.org). Summary method: excerpt of the source description. See our source attribution policy.
Related coverage
Parameters efficient language model with latent cross-attention for IoT intrusion detection
arXiv:2610.30222v1 Announce Type: new Abstract: Language models have shown strong potential for intrusion detection, but their high memory and computational demands make…
Moldova investigates possible foreign involvement in major government cyberattack
Prime Minister Vasile Tofan said the incident may be part of a broader campaign targeting both citizens' personal data and government digital infrastructure, according…
Researchers uncover Volt Typhoon’s covert, ephemeral network
Volt Typhoon, a China-government backed hacking group that has infiltrated America’s critical infrastructure networks for years, has consistently built and dismantled…
AU: Northern Territory Health backtracks on claim only five patients impacted by RDH privacy breach
Grace Atta reports: The Northern Territory health department has backtracked on its claim that only five patients were affected by a privacy breach that led to pregnant…
Pricing Cross-Bank Context in Federated Anti-Money Laundering
arXiv:2610.35996v1 Announce Type: new Abstract: Most graph-based Anti-Money Laundering (AML) methods assume access to a pooled transaction graph containing all accounts…
Privately Clipping Heavy-Tailed Data
arXiv:2610.36281v1 Announce Type: new Abstract: Summing vectors is a basic task in differentially private data analysis. Standard private sum algorithms clip vectors to…