Skip to main content
SpringerLink
Log in

Intelligent Monitoring Method for Backstage Data Security of Tourism Information Promotion Platform Based on Cloud Computing

  • Conference paper
  • First Online:
Multimedia Technology and Enhanced Learning (ICMTEL 2021)

  • 606 Accesses

Abstract

Due to the rapid update of information platform unsafe factors, the monitoring ability and response effect of the monitoring platform of tourism information promotion platform are not high. The monitoring center of the platform is the data acquisition module, and the data acquisition module uses RTL8019AS controller to collect the data transmitted by the nodes and the data of the security status of the nodes. The processing module uses MSP430 processor to monitor the security of the measured data, and connects with the transmission module directly, so as to monitor the error of the processed data and transmit the data. Finally, the experimental results show that the background data security intelligent monitoring method of tourism information promotion platform based on cloud computing has strong monitoring ability and good response.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wang, T., Guomai, S., Zhang, L., et al.: Earthquake response framework on based on campus on multi-source monitoring. J. Cleaner Prod. 238(20), 117965.1–117965.10 (2019)

    Google Scholar 

  2. Xie, K., Chen,Y., Wang, X., et al.: Accurate and fast recovery of network monitoring data with GPU-accelerated tensor completion. IEEE/ACM Trans. Netw. 28(4), 1–14 (2020)

    Google Scholar 

  3. Xiang, C., Li, B.: Research on ship intelligent manufacturing data monitoring and quality control system based on the industrial Internet of Things. Int. J. Adv. Manuf. Technol. 107(3), 983–992 (2020)

    Article  Google Scholar 

  4. Gomez, A., Magno, M., et al.: Precise, energy-efficient data acquisition architecture for radiomonitoring activity using sustainable wireless sensor nodes. IEEE J. Sens. 18(1), 459–469 (2018)

    Google Scholar 

  5. Petersen, H.I., Hillock, P., Milner, S., et al.: Monitoring gas distribution and origin in the Culzean field, UK central north logging, using data sea a from continuous isotope logging, tool and isotube and test samples. J. Petrol. Geol. 42(4), 435–449 (2019)

    Google Scholar 

  6. Khalfallah, C.B., Delatre, E., Ouerchefani, D., et al.: Monitoring vegetation in Southern Tunisia using SPOT-5 (Take5) data: a case of study of the Tozeur. J. Appl. Remote Sens. 12(4), 1–5 (2018)

    Google Scholar 

  7. Fu, W., Liu, S., Srivastava, G.: Optimization of big data scheduling in social networks. Entropy 21(9), 902 (2019)

    Article  MathSciNet  Google Scholar 

  8. Liu, S., Li, Z., Zhang, Y., et al.: Introduction of key problems in long-distance learning and training. Mobile Netw. Appl. 24(1), 1–4 (2019)

    Article  Google Scholar 

  9. Liu, S., Liu, D., Srivastava, G., et al.: Overview and methods of correlation filter algorithms in object tracking. Complex Intell. Syst. (2020). https://doi.org/10.1007/s40747-020-00161-4

  10. Liu, Y., Sun, R., Jin, S.: A survey on data-driven process monitoring and diagnostic methods for variation in multi-station systems reduction assembly. Assembly Autom. 39(4), 727–739 (2019)

    Google Scholar 

  11. Xin, D., Ji, J., Jing, F., et al.: Efficient fully homomorphic encryption scheme using ring-LWE. J. Phys. Conf. Ser. 1738(1), 012105 (2021)

    Google Scholar 

  12. Wei, T., Qiping, H., Tangzhi, W.: Research on location big data encryption method based on privacy protection. J. Anhui Electr. Eng. Prof. Tech. Coll. 24(1), 118–122 (2019)

    Google Scholar 

  13. Niu, J., Li, X., Gao, J., et al.: Blockchain-based anti-key-leakage key aggregation searchable encryption for IoT. IEEE Internet Things J. 7(2), 1502–1518 (2020)

    Article  Google Scholar 

  14. Zhong, W., Li, Z.: Research on network education system based on learning machine. J. Commun. 39(1), 135–140 (2018)

    Google Scholar 

  15. Yang, W.: Simulation of remote sharing method of database information under architecture of the internet of things. Comput. Simul. 35(04), 457–461 (2018)

    Google Scholar 

  16. Sun, Y., et al.: A comparative study on the security mechanism of open & sharing government date information in China, America and Britain. Libr. Inf. Serv. 62(21), 5–14 (2018)

    Google Scholar 

  17. Jones, L., Credo, J., Parnell, R., et al.: Dissolved uranium and arsenic in unregulated groundwater sources – western Navajo Nation. J. Contemp. Water Res. Educ. 169(1), 27–43 (2020)

    Article  Google Scholar 

  18. Hao, D., Tu, S., Zhang, C.: Experimental study on the effect of moisture content on bituminous coal porosity based on 3D reconstruction of computerized tomography. Nat. Resour. Res. 29(3), 1657–1673 (2020)

    Article  Google Scholar 

  19. Caron, J., Asselin, H., Beaudoin, J.M.: Attitudes and behaviors of mining sector employers towards the Indigenous workforce. Resour. Policy 61(10), 108–117 (2019)

    Article  Google Scholar 

  20. Wang, T., Zhang, H., Gamage, R.P., et al.: The evaluation criteria for rock brittleness based on double-body analysis under uniaxial compression. Geomech. Geophys. Geo-Energy Geo-Resources 6(3), 1–19 (2020)

    Google Scholar 

  21. Hellqvist, M.: Teaching sustainability in geoscience field education at falun mine world heritage site in Sweden. Geoheritage 11(4), 1785–1798 (2019)

    Article  Google Scholar 

  22. Teng, Y., Yang, L., Song, X., et al.: An augmented Lagrangian proximal alternating method for sparse discrete optimization problems. Numer. Algorithms 83(3), 833–866 (2020)

    Article  MathSciNet  Google Scholar 

  23. Li, Y., Yang, W., He, P., et al.: Design and management of a distributed hybrid energy system through smart contract and blockchain. Appl. Energy 248(15), 390–405 (2019)

    Article  Google Scholar 

  24. Spencer, A.A.M.S., Luciano, S., Mario, M.: Analysis and design of high-efficiency hybrid high step-up DC-DC converter for distributed PV generation systems. IEEE Trans. Ind. Electron. 66(5), 3860–3868 (2018)

    Google Scholar 

  25. Zhang, L.P., Liu, W., Qi, B.: Innovation design and optimization management of a new drive system for plug-in hybrid electric vehicles. Energy 186(1), 115823.1–115823.19 (2019)

    Google Scholar 

  26. Zkik, K., Hajji, S.E., Orhanou, G.: Sesign and implementation of a new security plane for hybrid distributed SDNs. J. Commun. 14(1), 26–32 (2019)

    Article  Google Scholar 

  27. Han, X., Dong, Y., Yue, L., et al.: State transition simulated annealing algorithm for discrete-continuous optimization problems. IEEE Access 7(12), 44391–44403 (2019)

    Google Scholar 

  28. Kamalakis, T., Dogkas, L., Simou, F.: Optimization of a discrete multi-tone visible light communication system using a mixed-integer genetic algorithm. Optics Commun. 485(1), 126741 (2020)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Information and Engineering, Sichuan Tourism University, Chengdu, 610000, China

    Yiqiong Ding

  2. Quanzhou Arts and Crafts Vocational College, Quanzhou, 362500, China

    Guozhi Lin

Authors
  1. Yiqiong Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guozhi Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Hunan Normal University, Changsha, China

    Weina Fu

  2. University of Jinan, Jinan, China

    Yuan Xu

  3. University of Leicester, Leicester, UK

    Shui-Hua Wang

  4. University of Leicester, Leicester, UK

    Yudong Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ding, Y., Lin, G. (2021). Intelligent Monitoring Method for Backstage Data Security of Tourism Information Promotion Platform Based on Cloud Computing. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-030-82562-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-82562-1_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82561-4

  • Online ISBN: 978-3-030-82562-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation