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P2 Tracing where IoT data are collected and aggregated

追踪 IoT 数据的收集与聚合位置
LMCS vol.Volume 13, Issue 32017匹配度 2/10 · 该论文提出面向 IoT 的进程演算与静态分析,用于追踪数据来源与流动,虽属于静态分析/形式化方法范畴,但应用领域是 IoT 系统,不涉及机器学习系统、LLM/Agentic 程序、浮点程序分析或贝叶斯程序分析,与用户核心方向重叠很弱。引用 25 inbox
Chiara Bodei, Pierpaolo Degano, Gian-Luigi Ferrari, Letterio Galletta
dblp: 2026-09-10crossref: 2026-09-10arxiv: 2026-09-10

AI 速览

一句话:提出 IoT-LySa 进程演算及静态分析,追踪 IoT 数据来源、聚合与流动,以支持安全等非功能性质验证。

IoT 为信息社会提供基础设施,其中智能对象自动收集并交换来自传感器或聚合生成的数据。为设计并推理此类系统,论文从基础层面研究协调原语与分析机制,提出 IoT-LySa:一种带有静态分析的进程演算。该分析追踪 IoT 数据的来源、被如何操作以及如何在系统中流动,从而刻画数据收集与聚合的路径。其结果可供设计者检查智能对象的行为,特别是验证安全性等非功能性质。摘要未报告具体实现或实验评估,贡献主要在形式化模型与分析机制。

问题
IoT 中智能对象自动收集与交换数据,需要合适的协调原语和分析机制来设计并推理系统,尤其要追踪数据来源、操作与流动。
方法
从基础层面定义 IoT-LySa 进程演算,并为其配备静态分析,用于追踪 IoT 数据的来源、被如何操作以及如何在系统中流动。
评估
分析结果可由设计者检查智能对象行为并验证安全等非功能性质;摘要未报告具体实验或工具实现评估。
原文摘要(Abstract)

The Internet of Things (IoT) offers the infrastructure of the information society. It hosts smart objects that automatically collect and exchange data of various kinds, directly gathered from sensors or generated by aggregations. Suitable coordination primitives and analysis mechanisms are in order to design and reason about IoT systems, and to intercept the implied technological shifts. We address these issues from a foundational point of view. To study them, we define IoT-LySa, a process calculus endowed with a static analysis that tracks the provenance and the manipulation of IoT data, and how they flow in the system. The results of the analysis can be used by a designer to check the behaviour of smart objects, in particular to verify non-functional properties, among which security.

链接与引用

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BibTeX
@article{BodeiDFG16a,
  title = {Tracing where IoT data are collected and aggregated},
  author = {Chiara Bodei and Pierpaolo Degano and Gian-Luigi Ferrari and Letterio Galletta},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 13, Issue 3},
  year = {2017},
  doi = {10.23638/lmcs-13(3:5)2017}
}