系统梳理智能家电安全漏洞，提出多层防护方案。
A Systematic Review of Security Vulnerabilities in Smart Home Devices and Mitigation Techniques
- 从网络、设备、云端与AI系统三层面分类安全风险
- 后量子加密与AI异常检测可显著提升防护效果
- 适合关注智能家居安全的开发者与研究者
智能家庭融合物联网设备面临日益严峻的网络安全威胁。本研究系统分析了智能家庭生态系统中的安全风险，将其分为网络层、设备层以及基于云和AI系统的漏洞。研究发现，后量子加密结合AI驱动的异常检测在增强安全性方面表现优异；然而其计算资源需求较大，带来实施挑战。区块链认证与零信任架构虽能提升安全韧性，但需对现有基础设施进行改造。具体安全策略通过方差分析（ANOVA）、卡方检验和蒙特卡洛模拟验证了有效性，但在可扩展性方面仍显不足。研究强调需改进密码技术，强化AI驱动的威胁检测，并发展兼顾性能、效率与实时性的自适应安全模型，以满足智能家庭环境的实际需求。
原文摘要 · Abstract (English)
Smart homes that integrate Internet of Things (IoT) devices face increasing cybersecurity risks, posing significant challenges to these environments. The study explores security threats in smart homes ecosystems, categorizing them into vulnerabilities at the network layer, device level, and those from cloud-based and AI-driven systems. Research findings indicate that post-quantum encryption, coupled with AI-driven anomaly detection, is highly effective in enhancing security; however, computational resource demands present significant challenges. Blockchain authentication together with zero-trust structures builds security resilience, although they need changes to existing infrastructure. The specific security strategies show their effectiveness through ANOVA, Chi-square tests, and Monte Carlo simulations yet lack sufficient scalability according to the results. The research demonstrates the requirement for improvement in cryptographic techniques, alongside AI-enhanced threat detection and adaptive security models which must achieve a balance between performance and efficiency and real-time applicability within smart home ecosystems.
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