cs.AI updates on arXiv.org 09月19日
IoT音频分类安全架构设计
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本文提出一种针对物联网音频分类设备的安全架构,包含安全协议、信任域划分、远程认证和端到端加密等技术,旨在保护敏感数据。

arXiv:2509.14657v1 Announce Type: cross Abstract: The rapid proliferation of IoT nodes equipped with microphones and capable of performing on-device audio classification exposes highly sensitive data while operating under tight resource constraints. To protect against this, we present a defence-in-depth architecture comprising a security protocol that treats the edge device, cellular network and cloud backend as three separate trust domains, linked by TPM-based remote attestation and mutually authenticated TLS 1.3. A STRIDE-driven threat model and attack-tree analysis guide the design. At startup, each boot stage is measured into TPM PCRs. The node can only decrypt its LUKS-sealed partitions after the cloud has verified a TPM quote and released a one-time unlock key. This ensures that rogue or tampered devices remain inert. Data in transit is protected by TLS 1.3 and hybridised with Kyber and Dilithium to provide post-quantum resilience. Meanwhile, end-to-end encryption and integrity hashes safeguard extracted audio features. Signed, rollback-protected AI models and tamper-responsive sensors harden firmware and hardware. Data at rest follows a 3-2-1 strategy comprising a solid-state drive sealed with LUKS, an offline cold archive encrypted with a hybrid post-quantum cipher and an encrypted cloud replica. Finally, we set out a plan for evaluating the physical and logical security of the proposed protocol.

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相关标签

物联网安全 音频分类 安全架构 端到端加密 量子安全
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