IoT Based Blockchain Methods for Data Association Technique for Secure Intelligent Contract
Keywords:
Blockchain, Smart Contract, Internet ofThings, Data Association, Data ConfirmationAbstract
IoT data association based on blockchain smart contracts solves the problems of difficulty in confirming ownership of personal data, quantitative tracking of data assets and inability to efficiently complete value transfer in IoT systems. Transfer the right of control and control from the equipment manufacturer to the user to confirm the ownership of personal data; store the equipment status and data hash value in the blockchain through technologies such as full life cycle management and digital signatures to ensure the reliability of the data; use intelligent The contract construction goes to a third-party data trading platform to ensure the security of data sharing, and to easily complete data realization and data value transfer. The quantitative analysis results of attack possibility and attack success probability show that blockchain smart contract technology can provide defense against data Tampering, eliminating trust problems in data transactions. With the help of blockchain innovative contract technology, physical Internet data can be capitalized initially, and the data value transfer and sharing of Internet of Things devices can be promoted.
Downloads
References
J. Ellul and G. J. Pace, "AlkylVM: A Virtual Machine for Smart Contract Blockchain Connected Internet of Things," 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), 2018, pp. 1-4, doi: 10.1109/NTMS.2018.8328732.
H. Cheng, Q. Hu, X. Zhang, Z. Yu, Y. Yang and N. Xiong, "Trusted Resource Allocation Based on Smart Contracts for Blockchain-enabled Internet of Things," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3114438.
N. Zhang, N. Zhao and Y. Qu, "Research on the Integration System of Ubiquitous Power Internet of Things Based on Blockchain Technology," 2020 International Conference on Robots & Intelligent System (ICRIS), 2020, pp. 356-359, doi: 10.1109/ICRIS52159.2020.00094.
M. Ur Rahman, F. Baiardi and L. Ricci, "Blockchain Smart Contract for Scalable Data Sharing in IoT: A Case Study of Smart Agriculture," 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), 2020, pp. 1-7, doi: 10.1109/GCAIoT51063.2020.9345874.
D. Di Francesco Maesa, F. Tietze and J. Theye, "Putting Trust back in IP Licensing: DLT Smart Licenses for the Internet of Things," 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2021, pp. 1-3, doi: 10.1109/ICBC51069.2021.9461145.
A. Vangala, A. K. Sutrala, A. K. Das and M. Jo, "Smart Contract-Based Blockchain-Envisioned Authentication Scheme for Smart Farming," in IEEE Internet of Things Journal, vol. 8, no. 13, pp. 10792-10806, 1 July1, 2021, doi: 10.1109/JIOT.2021.3050676.
V. Singla, I. K. Malav, J. Kaur and S. Kalra, "Develop Leave Application using Blockchain Smart Contract," 2019 11th International Conference on Communication Systems & Networks (COMSNETS), 2019, pp. 547-549, doi: 10.1109/COMSNETS.2019.8711422.
L. Xu and Y. Li, "Internet of Things Access Control System Based on Smart Contract," 2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID), 2021, pp. 659-662, doi: 10.1109/AIID51893.2021.9456510.
G. Sawant and V. Bharadi, "Permission Blockchain based Smart Contract Utilizing Biometric Authentication as a Service: A Future Trend," 2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW), 2020, pp. 1-4, doi: 10.1109/ICCDW45521.2020.9318715.
K. Peng, M. Li, H. Huang, C. Wang, S. Wan and K. -K. R. Choo, "Security Challenges and Opportunities for Smart Contracts in Internet of Things: A Survey," in IEEE Internet of Things Journal, vol. 8, no. 15, pp. 12004-12020, 1 Aug.1, 2021, doi: 10.1109/JIOT.2021.3074544.
Q. Ren, K. L. Man, M. Li and B. Gao, "Using Blockchain to Enhance and Optimize IoT-based Intelligent Traffic System," 2019 International Conference on Platform Technology and Service (PlatCon), 2019, pp. 1-4, doi: 10.1109/PlatCon.2019.8669412.
J. Hinckeldeyn and K. Jochen, "(Short Paper) Developing a Smart Storage Container for a Blockchain-Based Supply Chain Application," 2018 Crypto Valley Conference on Blockchain Technology (CVCBT), 2018, pp. 97-100, doi: 10.1109/CVCBT.2018.00017.
W. Dandi and H. Jian, "Blockchain-based node data detection scheme for the Internet of Things system," 2021 International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA), 2021, pp. 206-209, doi: 10.1109/CAIBDA53561.2021.00050.
C. K. Da Silva Rodrigues and V. Rocha, "Towards Blockchain for Suitable Efficiency and Data Integrity of IoT Ecosystem Transactions," in IEEE Latin America Transactions, vol. 19, no. 7, pp. 1199-1206, July 2021, doi: 10.1109/TLA.2021.9461849.
P. P. Ray, D. Dash, K. Salah and N. Kumar, "Blockchain for IoT-Based Healthcare: Background, Consensus, Platforms, and Use Cases," in IEEE Systems Journal, vol. 15, no. 1, pp. 85-94, March 2021, doi: 10.1109/JSYST.2020.2963840.
J. Zhou, G. Feng and Y. Wang, "Optimal Deployment Mechanism of Blockchain in Resource-Constrained IoT Systems," in IEEE Internet of Things Journal, vol. 9, no. 11, pp. 8168-8177, 1 June1, 2022, doi: 10.1109/JIOT.2021.3106355.
N. Saquib, F. Bakir, C. Krintz and R. Wolski, "A Resource-Efficient Smart Contract for Privacy Preserving Smart Home Systems," 2021 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI), 2021, pp. 532-539, doi: 10.1109/SWC50871.2021.00079.
R. Xu, S. Y. Nikouei, Y. Chen, E. Blasch and A. Aved, "BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety," 2019 IEEE International Conference on Blockchain (Blockchain), 2019, pp. 564-571, doi: 10.1109/Blockchain.2019.00082.
E. S. Kang, S. J. Pee, J. G. Song and J. W. Jang, "A Blockchain-Based Energy Trading Platform for Smart Homes in a Microgrid," 2018 3rd International Conference on Computer and Communication Systems (ICCCS), 2018, pp. 472-476, doi: 10.1109/CCOMS.2018.8463317.
G. Si, Y. Sun, W. Chen and L. Chen, "Node Switching Method in Power Distribution Internet of Things based on Blockchain," 2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2020, pp. 291-295, doi: 10.1109/ICCEIC51584.2020.00062.
G. Si, Y. Sun, W. Chen and L. Chen, "Node Switching Method in Power Distribution Internet of Things based on Blockchain," 2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2020, pp. 291-295, doi: 10.1109/ICCEIC51584.2020.00062.
W. Xiao et al., "Blockchain for Secure-GaS: Blockchain-Powered Secure Natural Gas IoT System With AI-Enabled Gas Prediction and Transaction in Smart City," in IEEE Internet of Things Journal, vol. 8, no. 8, pp. 6305-6312, 15 April15, 2021, doi: 10.1109/JIOT.2020.3028773.
Y. Jiang, Y. Zhong and X. Ge, "Smart Contract-Based Data Commodity Transactions for Industrial Internet of Things," in IEEE Access, vol. 7, pp. 180856-180866, 2019, doi: 10.1109/ACCESS.2019.2959771.
Bansal R., Gupta A., Singh R. and Nassa V. K., (2021). Role and Impact of Digital Technologies in E-Learning amidst COVID-19 Pandemic. 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT), pp. 194-202.doi: 10.1109/CCICT53244.2021.00046.
Dushyant, K., Muskan, G., Gupta, A. and Pramanik, S. (2022). Utilizing Machine Learning and Deep Learning in Cyber security: An Innovative Approach”, in Cyber security and Digital Forensics, M. M. Ghonge, S. Pramanik, R. Mangrulkar,D. N. Le, Eds, Wiley, https://doi.org/10.1002/9781119795667.ch12
Gupta A., et. al, (2020). An Analysis of Digital Image Compression Technique in Image Processing. International Journal of Advanced Science and Technology, 28(20), 1261 - 1265. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/3837
Kaushik, K., Garg, M., Annu, Gupta, A. and Pramanik, S. (2021). Application of Machine Learning and Deep Learning in Cyber security: An Innovative Approach, in Cybersecurity and Digital Forensics: Challenges and Future Trends, M. Ghonge, S. Pramanik, R. Mangrulkar and D. N. Le, Eds, Wiley, 2021.
Pandey, B.K. et al. (2022). Effective and Secure Transmission of Health Information Using Advanced Morphological Component Analysis and Image Hiding. In: Gupta, M., Ghatak, S., Gupta, A., Mukherjee, A.L. (eds) Artificial Intelligence on Medical Data. Lecture Notes in Computational Vision and Biomechanics, vol 37. Springer, Singapore.https://doi.org/10.1007/978-981-19-0151-5_19
Pathania, V. et al. (2022). A Database Application of Monitoring COVID-19 in India. In: Gupta, M., Ghatak, S., Gupta, A., Mukherjee, A.L. (eds) Artificial Intelligence on Medical Data. Lecture Notes in Computational Vision and Biomechanics, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-19-0151-5_23
Veeraiah V., Rajaboina N. B., Rao G. N., Ahamad S., Gupta A. and Suri C. S., (2022).Securing Online Web Application for IoT Management. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 1499-1504.doi: 10.1109/ICACITE53722.2022.9823733.
V. Jain, S. M. Beram, V. Talukdar, T. Patil, D. Dhabliya and A. Gupta, "Accuracy Enhancement in Machine Learning During Blockchain Based Transaction Classification," 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), Solan, Himachal Pradesh, India, 2022, pp. 536-540, doi: 10.1109/PDGC56933.2022.10053213.
V. Talukdar, D. Dhabliya, B. Kumar, S. B. Talukdar, S. Ahamad and A. Gupta, "Suspicious Activity Detection and Classification in IoT Environment Using Machine Learning Approach," 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), Solan, Himachal Pradesh, India, 2022, pp. 531-535, doi: 10.1109/PDGC56933.2022.10053312.
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya and A. Gupta, "A Scalable Platform to Collect, Store, Visualize and Analyze Big Data in Real- Time," 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM), Uttar Pradesh, India, 2023, pp. 1-6, doi: 10.1109/ICIPTM57143.2023.10118183.
M. Dhingra, D. Dhabliya, M. K. Dubey, A. Gupta and D. H. Reddy, "A Review on Comparison of Machine Learning Algorithms for Text Classification," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 1818-1823, doi: 10.1109/IC3I56241.2022.10072502.
D. Mandal, A. Shukla, A. Ghosh, A. Gupta and D. Dhabliya, "Molecular Dynamics Simulation for Serial and Parallel Computation Using Leaf Frog Algorithm," 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), Solan, Himachal Pradesh, India, 2022, pp. 552-557, doi: 10.1109/PDGC56933.2022.10053161.
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya and A. Gupta, "A Review on Application of Deep Learning in Natural Language Processing," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 1834-1840, doi: 10.1109/IC3I56241.2022.10073309.
V. V. Chellam, S. Praveenkumar, S. B. Talukdar, V. Talukdar, S. K. Jain and A. Gupta, "Development of a Blockchain-based Platform to Simplify the Sharing of Patient Data," 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM), Uttar Pradesh, India, 2023, pp. 1-6, doi: 10.1109/ICIPTM57143.2023.10118194.
Veeraiah V., Ahamad G. P, S., Talukdar S. B., Gupta A. and Talukdar V., (2022) Enhancement of Meta Verse Capabilities by IoT Integration. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 1493-1498.doi: 10.1109/ICACITE53722.2022.9823766.
Gupta A., Singh R., Nassa V. K., Bansal R., Sharma P. and Koti K., (2021) Investigating Application and Challenges of Big Data Analytics with Clustering. 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), pp. 1-6.doi: 10.1109/ICAECA52838.2021.9675483.
Natalia Volkova, Machine Learning Approaches for Stock Market Prediction , Machine Learning Applications Conference Proceedings, Vol 2 2022.
M, A. ., M, D. ., M, A. ., M, V. ., I, S. T. ., & P, K. . (2023). COVID -19 Predictions using Transfer Learning based Deep Learning Model with Medical Internet of Things . International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 43–50. https://doi.org/10.17762/ijritcc.v11i3.6200
Sherje, N. P., Agrawal, S. A., Umbarkar, A. M., Dharme, A. M., & Dhabliya, D. (2021). Experimental evaluation of mechatronics based cushioning performance in hydraulic cylinder. Materials Today: Proceedings, doi:10.1016/j.matpr.2020.12.1021
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
