/secure-interoperable-data-sharing

Primary LanguagePython

Enabling privacy-aware interoperable and quality IoT data sharing with context

image

Cite

If you use any code, please cite our article.

@article{CHHETRI2024,
title = {Enabling privacy-aware interoperable and quality IoT data sharing with context},
journal = {Future Generation Computer Systems},
year = {2024},
issn = {0167-739X},
doi = {https://doi.org/10.1016/j.future.2024.03.039},
url = {https://www.sciencedirect.com/science/article/pii/S0167739X24001109},
author = {Tek Raj Chhetri and Chinmaya Kumar Dehury and Blesson Varghese and Anna Fensel and Satish Narayana Srirama and Rance J. DeLong},
keywords = {Data sharing, Edge intelligence, Interoperability, Internet of Things (IoT), Knowledge graphs, General Data Protection Regulation (GDPR), Smart cities},
abstract = {Sharing Internet of Things (IoT) data across different sectors, such as in smart cities, becomes complex due to heterogeneity. This poses challenges related to a lack of interoperability, data quality issues and lack of context information, and a lack of data veracity (or accuracy). In addition, there are privacy concerns as IoT data may contain personally identifiable information. To address the above challenges, this paper presents a novel semantic technology-based framework that enables data sharing in a GDPR-compliant manner while ensuring that the data shared is interoperable, contains required context information, is of acceptable quality, and is accurate and trustworthy. The proposed framework also accounts for the edge/fog, an upcoming computing paradigm for the IoT to support real-time decisions. We evaluate the performance of the proposed framework with two different edge and fog-edge scenarios using resource-constrained IoT devices, such as the Raspberry Pi. In addition, we also evaluate shared data quality, interoperability and veracity. Our key finding is that the proposed framework can be employed on IoT devices with limited resources due to its low CPU and memory utilization for analytics operations and data transformation and migration operations. The low overhead of the framework supports real-time decision making. In addition, the 100% accuracy of our evaluation of the data quality and veracity based on 180 different observations demonstrates that the proposed framework can guarantee both data quality and veracity.}
}

DOI

https://doi.org/10.1016/j.future.2024.03.039

Instructions

  • First start the RabbitMQ cluster

    docker-compose up

    If started successfully, you should be able to see the following screen after successful login into RabbitMQ management UI at http://localhost:15672

    • User name: admin
    • Password: P@ssword Screenshot 2022-05-08 at 10 55 09

  • Create a queue (go to queues tab) with a name secure_interoperable_data_sharing (or based on what you've defined in config.yml)

  • Create exchange of type topic, routing key and assign (or bind) it to newly created queue. The name for both routing key and exchange is the same, which is secure_interoperable_data_sharing. IF you wish to change, you can do so in config.yml.

  • Run the code depending on how you want to run it, i.e., in edge or edge/fog mode, adjusting the settings in the config file.

KG Instance

image

Ganache Details (Test account)

Accounts

  • ganache_1 | (0) 0xe3Fc9C5d3055ceb429F0F161E863151D19d4B2bF (100 ETH)
  • ganache_1 | (1) 0xE29a5B5a6193d3D3fe826F9D0D76feDeb712B872 (100 ETH)
  • ganache_1 | (2) 0xE10A3f8143cdC05d141afA1B04E453fd81f6B625 (100 ETH)
  • ganache_1 | (3) 0xA94623F49092E1eAafE152d25C40fBdead4b7d69 (100 ETH)
  • ganache_1 | (4) 0x7873488f33cA043BcB3f7Ad50EcfCC96e72DF682 (100 ETH)
  • ganache_1 | (5) 0x3E52c734bD3c33572bDB03cb9626cdb4670E69bB (100 ETH)
  • ganache_1 | (6) 0x9FE595C5fa0b2Dcf54518c0deDe63c5B5Dc2c960 (100 ETH)
  • ganache_1 | (7) 0x31EcEF1D517cB84Aa34Cd538F929f1CF8A62bd6d (100 ETH)
  • ganache_1 | (8) 0x6B2317D0d758736ED57DB44B42D70ce39260f71E (100 ETH)
  • ganache_1 | (9) 0x8d8C2916D380b1327eE1b05F63e9D388D9231fA7 (100 ETH)
  • ganache_1 |

Private Keys

  • ganache_1 | ==================
  • ganache_1 | (0) 0xfadd56513d37277a3fe72518f0087fe26053df9f59dc95b97451f9a0a832fa57
  • ganache_1 | (1) 0x1123e0c9c6df300c0cbdf61cbdca918716ca5e68fd306193aa61b345176d53d8
  • ganache_1 | (2) 0xcc8cb23dda7bef8b5d27a2649a99f922d645e17797a78864dbde29f4cdc918fe
  • ganache_1 | (3) 0x859ea19cfe763c0098916582ef117042297b81ab44c9bef04c0c9d192fbafc4f
  • ganache_1 | (4) 0x13932b970acc1ae04e21a71ae4751106ceb51c5e7a92ee60c76f897b27a497e1
  • ganache_1 | (5) 0x4c5603594ad6a371e7418c2d24ee62d5b69e35caca20fe0636c7071b7ffe461f
  • ganache_1 | (6) 0xa11c4d0f09db8e196fe27da5d9814787e0b0a5cfc8862bd444c5d078fbdaaa5f
  • ganache_1 | (7) 0x506e07ead195c0dcd0c1508b0576f7ccbb1cc829d31a881154c1f202e797f4bb
  • ganache_1 | (8) 0x17ed4b1d19242eecc08627c32fe7cf9c24b214026a7ffb5ae9459742bbd935c8
  • ganache_1 | (9) 0x914608beec2dff591b74cb420a418c0289079a564ff8ab8a3a31de35a2be55d3

Softwares

Libraries Version
Python 3.8
RDFLib 6.1.1
PyYAML 6.0
pySHACL 0.19.0
Docker 20.x
Pika 1.2.1
Owlready2 0.3
Adafruit-DHT 1.4.0
py_solc_x 1.1.1
web3 5.31.1

License