August & September  2019, 12(4&5): 1219-1232. doi: 10.3934/dcdss.2019084

Reversible hidden data access algorithm in cloud computing environment

School of Modern Posts & Institute of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

* Corresponding author: Jinsong Xu

Received  June 2017 Revised  November 2017 Published  November 2018

At present, the data filtering quality of reversible hidden data access algorithm based on column store database is not guaranteed, and the location accuracy and data access security of reversible hidden data are low. In this paper, the whitening vector is obtained by processing the sample length of the observed data signal. By using the nonlinear robust function, the data projection is realized, the judged threshold of projection data is constructed, an matrix with adaptive filter characteristic is set up, and the high quality of filtering results are output; the parameters between three anchor nodes and the location of reversible hidden data are measured, and the artificial bee colony optimization neural network is used for modeling and forecasting the ranging error, and determine the weights according to the results, so that on the basis of the three edge location algorithm, the positioning accuracy of the data is to further improve; through the establishment of authorized institutions, producing key, off-line encryption, online encryption, ciphertext conversion, decrypt ion and other aspects, the security of access data is completed. The experiment shows that the algorithm can effectively improve the quality of data filtering and positioning accuracy and the security of data access is also better than that of the current algorithm.

Citation: Jinsong Xu. Reversible hidden data access algorithm in cloud computing environment. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1219-1232. doi: 10.3934/dcdss.2019084
References:
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W. Gao and W. Wang, A tight neighborhood union condition on fractional $(g,f,n',m)$-critical deleted graphs, Colloquium Mathematicum, 149 (2017), 291-298.  doi: 10.4064/cm6959-8-2016.  Google Scholar

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P. Gope and T. Hwang, A realistic lightweight anonymous authentication protocol for securing real-time application data access in wireless sensor networks, IEEE Transactions on Industrial Electronics, 63 (2016), 7124-7132.   Google Scholar

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F. Guo and T. Cheng, Systems and methods for detecting suspicious attempts to access data based on organizational relationships, 2015. Google Scholar

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D. HuangD. HanJ. WangJ. YinX. ChenX. ZhangJ. Zhou and M. Ye, Achieving load balance for parallel data access on distributed file systems, IEEE Transactions on Computers, 67 (2018), 388-402.  doi: 10.1109/TC.2017.2749229.  Google Scholar

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M. KumarN. P. GantasalaT. RoychowdhuryP. K. ThakurP. BanakarR. N. ShuklaM. G. Jones and U. Rao, De novo transcriptome sequencing and analysis of the cereal cyst nematode, heterodera avenae, Plant Molecular Biology, 1 (2015), 69-80.   Google Scholar

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Y. KwonB. Park and D. H. Kang, Scaling of data retention statistics in phase-change random access memory, IEEE Electron Device Letters, 36 (2015), 454-456.   Google Scholar

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O. LancasterT. BeckD. AtlanM. SwertzD. ThangaveluC. VealR. Dalgleish and A. J. Brookes, Cafe variome: General-purpose software for making genotype-phenotype data discoverable in restricted or open access contexts, Human Mutation, 36 (2015), 957-964.   Google Scholar

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F. LiB. Liu and J. Hong, An efficient signcryption for data access control in cloud computing, Computing, 99 (2017), 465-479.  doi: 10.1007/s00607-017-0548-7.  Google Scholar

[19]

T. L. Spires-JonesP. Poirazi and M. S. Grubb, Opening up: open access publishing, data sharing, and how they can influence your neuroscience career, European Journal of Neuroscience, 43 (2016), 1413-1419.   Google Scholar

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L. Y. WangL. ChenX. R. HaoQ. Wang and M. Ni, Life-aware buffer management algorithm for flash-based databases, Jilin Daxue Xuebao, 47 (2017), 632-638.   Google Scholar

[21]

Z. WangD. HuangY. ZhuB. Li and C. J. Chung, Efficient attribute-based comparable data access control, IEEE Transactions on Computers, 64 (2015), 3430-3443.  doi: 10.1109/TC.2015.2401033.  Google Scholar

[22]

D. T. Wiriaatmadja and K. W. Choi, Hybrid random access and data transmission protocol for machine-to-machine communications in cellular networks, IEEE Transactions on Wireless Communications, 14 (2015), 33-46.   Google Scholar

[23]

F. Y. Wu, Remote sensing image processing based on multi-scale geometric transformation algorithm, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 309-321.   Google Scholar

[24]

J. Xu, Data distributed momdatory secure access method in cloud computing environment, Bulletin of Science & Technology, 8 (2017), 189-192.   Google Scholar

[25]

T. Yin, The exploration and research of software development architecture based on asp.net mvc pattern, Journal of China Academy of Electronics & Information Technology, 599-602. Google Scholar

[26]

J. Zhang, Simulation of database access information security management under big data platform, Computer Simulation, 7. Google Scholar

show all references

References:
[1]

R. AfshariB. S. Gildeh and M. Sarmad, Fuzzy multiple deferred state attribute sampling plan in the presence of inspection errors, Journal of Intelligent & Fuzzy Systems, 33 (2017), 503-514.   Google Scholar

[2]

A. BahlS. MassonZ. MalikA. J. BirtleS. SundarR. J. JonesN. D. JamesM. D. MasonS. Kumar and D. Bottomley, Final quality of life and safety data for patients with metastatic castration-resistant prostate cancer treated with cabazitaxel in the uk early access programme (eap) (nct01254279), Bju International, 116 (2015), 880-887.   Google Scholar

[3]

A. Basar and M. Abbasi, On ordered bi-ideals in ordered-semigroups, Journal of Discrete Mathematical Sciences and Cryptography, 20 (2017), 645-652.  doi: 10.1080/09720529.2015.1130474.  Google Scholar

[4]

J. Bensmail and B. Stevens, Edge-partitioning graphs into regular and locally irregular components, Discrete Mathematics, 17 (2016), 43-58.   Google Scholar

[5]

A. Brezavscek, S. P. and Z. A., Factors influencing the behavioural intention to use statistical software: The perspective of the slovenian students of social sciences, Eurasia Journal of Mathematics Science and Technology Education, 13 (2017), 953-986. Google Scholar

[6]

K. CaineS. KohnC. LawrenceR. HananiaE. M. Meslin and W. M. Tierney, Designing a patient-centered user interface for access decisions about ehr data: Implications from patient interviews., Journal of General Internal Medicine, 30 (2015), 7-16.   Google Scholar

[7]

K. Caine and W. M. Tierney, Point and counterpoint: Patient control of access to data in their electronic health records, Journal of General Internal Medicine, 30 (2015), 38-41.   Google Scholar

[8]

T. H. ChenW. ShangZ. M. JiangA. E. HassanM. Nasser and P. Flora, Finding and evaluating the performance impact of redundant data access for applications that are developed using object-relational mapping frameworks, IEEE Transactions on Software Engineering, 42 (2016), 1148-1161.   Google Scholar

[9]

P. K. CommeanJ. M. RathmellK. W. ClarkD. R. Maffitt and F. W. Prior, A query tool for investigator access to the data and images of the national lung screening trial, Journal of Digital Imaging, 28 (2015), 439-447.   Google Scholar

[10]

J. DouZ. ZhangJ. DangL. WuY. Wei and C. Sun, Properties and achievable data rate of a cyclic prefix based imperfect reconstruction filter bank multiple access system, Iet Communications, 10 (2016), 2427-2434.   Google Scholar

[11]

W. Gao and W. Wang, A tight neighborhood union condition on fractional $(g,f,n',m)$-critical deleted graphs, Colloquium Mathematicum, 149 (2017), 291-298.  doi: 10.4064/cm6959-8-2016.  Google Scholar

[12]

P. Gope and T. Hwang, A realistic lightweight anonymous authentication protocol for securing real-time application data access in wireless sensor networks, IEEE Transactions on Industrial Electronics, 63 (2016), 7124-7132.   Google Scholar

[13]

F. Guo and T. Cheng, Systems and methods for detecting suspicious attempts to access data based on organizational relationships, 2015. Google Scholar

[14]

D. HuangD. HanJ. WangJ. YinX. ChenX. ZhangJ. Zhou and M. Ye, Achieving load balance for parallel data access on distributed file systems, IEEE Transactions on Computers, 67 (2018), 388-402.  doi: 10.1109/TC.2017.2749229.  Google Scholar

[15]

M. KumarN. P. GantasalaT. RoychowdhuryP. K. ThakurP. BanakarR. N. ShuklaM. G. Jones and U. Rao, De novo transcriptome sequencing and analysis of the cereal cyst nematode, heterodera avenae, Plant Molecular Biology, 1 (2015), 69-80.   Google Scholar

[16]

Y. KwonB. Park and D. H. Kang, Scaling of data retention statistics in phase-change random access memory, IEEE Electron Device Letters, 36 (2015), 454-456.   Google Scholar

[17]

O. LancasterT. BeckD. AtlanM. SwertzD. ThangaveluC. VealR. Dalgleish and A. J. Brookes, Cafe variome: General-purpose software for making genotype-phenotype data discoverable in restricted or open access contexts, Human Mutation, 36 (2015), 957-964.   Google Scholar

[18]

F. LiB. Liu and J. Hong, An efficient signcryption for data access control in cloud computing, Computing, 99 (2017), 465-479.  doi: 10.1007/s00607-017-0548-7.  Google Scholar

[19]

T. L. Spires-JonesP. Poirazi and M. S. Grubb, Opening up: open access publishing, data sharing, and how they can influence your neuroscience career, European Journal of Neuroscience, 43 (2016), 1413-1419.   Google Scholar

[20]

L. Y. WangL. ChenX. R. HaoQ. Wang and M. Ni, Life-aware buffer management algorithm for flash-based databases, Jilin Daxue Xuebao, 47 (2017), 632-638.   Google Scholar

[21]

Z. WangD. HuangY. ZhuB. Li and C. J. Chung, Efficient attribute-based comparable data access control, IEEE Transactions on Computers, 64 (2015), 3430-3443.  doi: 10.1109/TC.2015.2401033.  Google Scholar

[22]

D. T. Wiriaatmadja and K. W. Choi, Hybrid random access and data transmission protocol for machine-to-machine communications in cellular networks, IEEE Transactions on Wireless Communications, 14 (2015), 33-46.   Google Scholar

[23]

F. Y. Wu, Remote sensing image processing based on multi-scale geometric transformation algorithm, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 309-321.   Google Scholar

[24]

J. Xu, Data distributed momdatory secure access method in cloud computing environment, Bulletin of Science & Technology, 8 (2017), 189-192.   Google Scholar

[25]

T. Yin, The exploration and research of software development architecture based on asp.net mvc pattern, Journal of China Academy of Electronics & Information Technology, 599-602. Google Scholar

[26]

J. Zhang, Simulation of database access information security management under big data platform, Computer Simulation, 7. Google Scholar

Figure 1.  principle of reversible hidden data location
Figure 2.  working principle of three edge location method
Figure 3.  reversible hidden data's access control entities in the cloud computing environment
Figure 4.  Distribution model of reversible hidden data node in cloud computing environment
Figure 5.  Comparison of the filtering effects by different algorithms
Figure 6.  Comparison of location effect of reversible hidden data by different algorithms
Figure 7.  Comparison of access security for reversible hidden data by different algorithms
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