Privacy-Preserving and Energy-Centered QoS for IoT Using XOR-RSA and BM-SSA

Priya, P. Prem; Katiravan, Jeevaa

doi:10.1007/s11277-021-08966-3

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…They mainly implemented this scheme using the Raspberry Pi and Desktop PC and the efficiency of this scheme is analyzed in terms of different attacks. Manzoor et al 23 developed a proxy re‐encryption scheme to make the sensible data visible to only the authorized individuals of the smart contract. This scheme is efficient for sensor data storage, trade, and management.…”

Section: Related Workmentioning

confidence: 99%

“…We have previously presented an energy‐efficient secure IoT‐based data transmission framework using blockchain technology and secure hash algorithm 512 (SHA512) 23 . The IoT data is encrypted using an eXclusive OR‐Rivest, Shamir, Adleman (XOR‐RSA) algorithm, and the data is securely stored in the blockchain‐centric cloud.…”

Section: Related Workmentioning

confidence: 99%

“…The IoT memory consumption is measured at different levels such as the user level, sensor level, server level, or gateway level. We have computed the computational complexity by comparing different techniques such as SDN‐enabled blockchain architecture with a distributed trust mechanism, 11 blockchain‐based Internet of Edge model, 21 SCAB‐IoTA, 22 XOR‐RSA, 23 ADMM, 30 and momentum gradient descent energy‐efficient offloading decision (MGDEEOD) algorithm 31 with the proposed model in terms of space complexity and results are presented in Table 5. The space complexity mainly measures the memory taken by the different models to run based on the input size.…”

Section: Experimental Analysismentioning

confidence: 99%

“…The time complexity of the proposed model is obtained by computing the total time taken to complete the services of 500 IoT nodes and the time is computed in milliseconds. The time complexity is computed for different techniques such as SDN‐enabled blockchain architecture with a distributed trust mechanism, 11 blockchain‐based Internet of Edge model, 21 SCAB‐IoTA, 22 XOR‐RSA, 23 ADMM, 30 and MGDEEOD algorithm 31 and the results are presented in Table 6.…”

Section: Experimental Analysismentioning

confidence: 99%

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Energy‐efficient and privacy‐preserving approach forInternet of Thingsnodes using a novel hybrid fuzzy water cycle and evaporation strategy and matrix‐based Rivest–Shamir–Adleman encryption algorithm

Dhavamani

Priya

2022

Concurrency and Computation

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The Internet of Things (IoT) connects physical components all around the world via the internet and provides people with easy access. Even though IoT offers speedy operations, saves money, and provides automation and control, it suffers from different complexities such as data breaches, security issues, and load balancing. To overcome these complexities in the IoT environment, we propose a novel strategy to deal with energy consumption issues and offer a privacy-preserving data transfer strategy. The proposed hybrid fuzzy water cycle and evaporation algorithm increases the lifetime of IoT networks by reducing the amount of energy required by massive IoT nodes and balancing traffic loads. To protect against malicious entries in cloud servers, the digital data block that is transported to be stored in the cloud is encrypted using the matrix-based RSA encryption technique. The significance of the proposed methodology is proven by simulated results that compare it to state-of-the-art methodologies in terms of security, system cost, resource utilization, and energy consumption. The resource utilization of this proposed methodology is 100% and the security level is 96%.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%