Data trustworthiness in IoT

Autor: Choong Seon Hong, Abid Khan, Faisal Bashir, Sabah Suhail, M. Ali Lodhi, Faheem Zafar
Rok vydání: 2018
Předmět:
Zdroj: ICOIN
DOI: 10.1109/icoin.2018.8343151
Popis: Internet of Things (IoT) is deployed in numerous pervasive application areas, for instance, environment monitoring, energy management, health-care system and industrial automation. Data are streamed from multiple sources and is traversed through intermediate nodes until it arrives at sink node which performs decision-making for critical infrastructures. Malicious or compromised nodes may forge data or inject false data. Therefore, assuring high data trustworthiness is crucial for precise decision-making. Data provenance play an important role in evaluating the trustworthiness of data. However, provenance management for resource-constrained devices introduces several challenging requirements, such as network overhead, energy consumption, and efficient storage. In this paper, we formulate the problem of binding IoT with a provenance-aware system to enable it to track the data flow across the networked entities and data transformations applied to data by nodes. We propose a lightweight scheme to transmit provenance for IoT sensor data. The proposed technique relies on the hash chain scheme to encode provenance as the packet traversed from each participating node while the provenance verification is done at the sink node. Furthermore, we evaluate our technique with respect to energy consumption by the constrained nodes.
Databáze: OpenAIRE