🤖 AI Summary
This study addresses the security and privacy risks arising from legal conflicts and technical vulnerabilities in cross-border data flows involving large language models and IoT systems, where traditional static encryption and data localization strategies struggle to balance regulatory compliance with utility. To overcome this challenge, the work proposes a jurisdiction-aware, privacy-first architecture that dynamically integrates jurisdictional regulations into localized encryption, adaptive differential privacy, and cryptographic compliance proofs, enabling proactive alignment between security and compliance. Evaluated on a multi-jurisdiction simulation platform, the proposed framework reduces unauthorized data exposure to below 5%, achieves zero compliance violations, maintains model utility above 90%, and incurs manageable computational overhead.
📝 Abstract
The reliance of Large Language Models and Internet of Things systems on massive, globally distributed data flows creates systemic security and privacy challenges. When data traverses borders, it becomes subject to conflicting legal regimes, such as the EU's General Data Protection Regulation and China's Personal Information Protection Law, compounded by technical vulnerabilities like model memorization. Current static encryption and data localization methods are fragmented and reactive, failing to provide adequate, policy-aligned safeguards. This research proposes a Jurisdiction-Aware, Privacy-by-Design architecture that dynamically integrates localized encryption, adaptive differential privacy, and real-time compliance assertion via cryptographic proofs. Empirical validation in a multi-jurisdictional simulation demonstrates this architecture reduced unauthorized data exposure to below five percent and achieved zero compliance violations. These security gains were realized while maintaining model utility retention above ninety percent and limiting computational overhead. This establishes that proactive, integrated controls are feasible for secure and globally compliant AI deployment.