Hybrid optimization enabled secure privacy preserved data sharing based on blockchain

被引:0
作者
J. Uma Maheswari
S. K. Somasundaram
P. Sivakumar
机构
[1] Vellore Institute of Technology,School of Computer Science and Engineering
[2] Vellore Institute of Technology,Department of Information Security, School of Computer Science and Engineering
来源
Wireless Networks | 2024年 / 30卷
关键词
Internet of things (IoT); Blockchain; Hybrid leader optimization (HLBO); Average subtraction based optimization (ASBO); Quality of service (QoS);
D O I
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中图分类号
学科分类号
摘要
The sensing-as-a-service concept has been developed to address the challenges that future smart cities would have in managing an enormous number of sensors. Smart cities must find a solution to the enormous difficulty of effectively sharing user-confidential information without sacrificing quality, privacy, or interruption. The development of blockchain technology has the potential to overcome these problems, but the limitations of the current models include large storage, customizable blockchain, high communication overhead, and high processing costs. The proposed average hybrid leader optimization (AHLO)-PrivPresKey Gen model determined a blockchain-based secure information sharing scheme using a smart contract in a smart city. Blockchain-based smart contracts implement a highly complex midway illustration method to reduce the user's clarification burden. The proposed scheme makes utilize of different safety operators, like 3 Data Encryption Standard, segmenting interpolation, passwords, one time password token and etc. Furthermore, the data privacy phase is improved by utilizing various functionalities, such as dyadic product, Chebyshev polynomial, and keys, where the keys are optimally generated using AHLO. The designed AHLO is obtained by the consolidation of average and subtraction based optimizer and hybrid leader-based optimization. The designed model has delivered minimum memory of 30.5 MB, minimum computational time of 28.467 MB, maximum encryption quality of 0.808, maximum detection rate of 0.898, minimum responsiveness of 41.679 and minimum bandwidth of 95 that surpasses the conventional schemes.
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页码:1553 / 1574
页数:21
相关论文
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  • [1] Gubbi J(2013)Internet of Things (IoT): A vision, architectural elements, and future directions Future generation computer systems 29 1645-1660
  • [2] Buyya R(2021)Process automation in an IoT–fog–cloud ecosystem: A survey and taxonomy IoT 2 92-118
  • [3] Marusic S(2020)Internet of things (IoT) for next-generation smart systems: A review of current challenges, future trends and prospects for emerging 5G-IoT scenarios Ieee Access 8 23022-23040
  • [4] Palaniswamia M(2020)A survey on the internet of things (IoT) forensics: Challenges, approaches, and open issues IEEE Communications Surveys & Tutorials 22 1191-1221
  • [5] Chegini H(2017)Smart city and IoT Future Generation Computer Systems 76 159-162
  • [6] Naha RK(2014)Smart city policies: A spatial approach Cities 41 S3-S11
  • [7] Mahanti A(2017)Security and privacy in smart city applications: Challenges and solutions IEEE Communications Magazine 55 122-129
  • [8] Thulasiraman P(2013)The pursuit of citizens' privacy: A privacy-aware smart city is possible IEEE Communications Magazine 51 136-141
  • [9] Shafique K(2019)Security and privacy on blockchain ACM Computing Surveys (CSUR) 52 1-34
  • [10] Khawaja BA(2023)A blockchain-based signature exchange protocol for metaverse Future Generation Computer Systems 142 237-247