Skip to main content

Advertisement

Springer Nature Link
Log in

Distributed PEP–PDP Architecture for Cloud Databases

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Cloud computing allows accessing data from anywhere; Cloud databases play an important role in storing requests for access management. These requests require authorization management which has become a crucial area in access control. The request-response paradigm plays an important role in the PEP–PDP architecture. Many applications are available in literature based on the centralized PEP–PDP architecture. In this architecture, performance degrades with the increase in requests. Failure of PDP increases while handling requests from multiple PEPs. The proposed work extends the existing centralized PEP–PDP architecture to distributed architecture with PEP side caching to achieve scalability. In the proposed architecture, all PEPs employ side caching to improve efficiency. Various simulations and validation checks are performed to validate the architecture. Simulation results show proposed architecture is significantly efficient in handling large requests in contrast to existing single PEP-PDP and multiple PEP-single PEP architectures.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data Availability

All data generated or analysed during this study are included in this published article.

Code Availability

The code developed during the current study are available from the corresponding author on reasonable request.

References

  1. Modi, C., Patel, D., Borisaniya, B., Patel, A., & Rajarajan, M. (2013). A survey on security issues and solutions at different layers of Cloud computing. The Journal of Supercomputing, 63(2), 561–592.

    Article  Google Scholar 

  2. Hsu, C. H., Ma, J., & Obaidat, M. S. (2014). Dynamic intelligence towards merging cloud and communication services. Information Systems Frontiers, 16(1), 1–5.

    Article  Google Scholar 

  3. Flahive, A., Taniar, D., & Rahayu, W. (2013). Ontology as a Service (OaaS): A case for sub-ontology merging on the cloud. The Journal of Supercomputing, 65(1), 185–216.

    Article  Google Scholar 

  4. Petrov, C. (2021). 25+ Impressive big data statistics for 2021. https://techjury.net/blog/big-data- statistics/#gref

  5. Petters, J. E. F. F. (2020, September 28). Data privacy guide: definitions, explanations and legislation. https://Www.Varonis.Com/Blog/Data-Privacy/.

  6. Al-Gburi, A., Al-Hasnawi, A., & Lilien, L. (2018). Differentiating security from privacy in internet of things: a survey of selected threats and controls. In Computer and network security essentials, (pp. 153–172). Springer, Cham.

  7. Sharma, S., Singh, S., Singh, A., & Kaur, R. (2016). Virtualization in cloud computing. International Journal of Scientific Research in Science, Engineering and Technology, 2, 181–186.

    Google Scholar 

  8. Devi, V. A. & Nayyar, A. (2021). Evaluation of geotagging twitter data using sentiment analysis during COVID-19. In Proceedings of the second international conference on information management and machine intelligence, (pp. 601–608). Springer, Singapore.

  9. Daradoumis, T., Bassi, R., Xhafa, F., & Caballé, S. (2013). A review on massive e-learning (MOOC) design, delivery and assessment. In 2013 eighth international conference on P2P, parallel, grid, cloud and internet computing (pp. 208–213). IEEE.

  10. Mehmi, S., Verma, H. K., & Sangal, A. L. (2014). Smart grid cloud for Indian power sector. In International conference on recent advances and innovations in engineering (ICRAIE-2014) (pp. 1–6). IEEE.

  11. Bhatia, R. (2020). Interoperability solutions for blockchain. In 2020 International conference on smart technologies in computing, electrical and electronics (ICSTCEE) (pp. 381–385). IEEE.

  12. Singh, M. & Singh, S. (2014). Review of implicit security mechanisms for cloud computing. International Journal of Computer Applications, 106(17).

  13. Verma, A. & Kaushal, S. (2011). Cloud computing security issues and challenges: a survey. In International conference on advances in computing and communications (pp. 445–454). Springer, Berlin, Heidelberg.

  14. Shikare, D. & Shetty, S. D. (2014). Supercloud–need, issues and challenges. International Journal of Engineering Research, 3(5).

  15. Sharma, R., Kumar, S., & Trivedi, M. C. (2013). Mobile cloud computing: Bridging the gap between cloud and mobile devices. In 2013 5th international conference and computational intelligence and communication networks (pp. 553–555). IEEE.

  16. Mackenzie, R. J. (2021). 4 ways that the cloud is changing research. https://Www.Technologynetworks.Com/Informatics/Lists/4-Ways-That-the-Cloud-Is-Changing-Research-315952.

  17. Gurucul Solutions Pvt Ltd. (n.d.). 2020 insider threat survey report. https://Gurucul.Com/2020-Insider-Threat-Survey-Report. Retrieved June 5, 2021, from https://gurucul.com/2020-insider-threat-survey-report.

  18. Tabrizchi, H., & Rafsanjani, M. K. (2020). A survey on security challenges in cloud computing: Issues, threats, and solutions. The Journal of Supercomputing, 76(12), 9493–9532.

    Article  Google Scholar 

  19. Liu, L., De Vel, O., Han, Q. L., Zhang, J., & Xiang, Y. (2018). Detecting and preventing cyber insider threats: A survey. IEEE Communications Surveys & Tutorials, 20(2), 1397–1417.

    Article  Google Scholar 

  20. Ramachandran, M., & Chang, V. (2016). Towards performance evaluation of cloud service providers for cloud data security. International Journal of Information Management, 36(4), 618–625.

    Article  Google Scholar 

  21. Barrowclough, J. P., & Asif, R. (2018). Securing cloud hypervisors: A survey of the threats, vulnerabilities, and countermeasures. Security and Communication Networks, 2018, 1–20.

    Article  Google Scholar 

  22. Sandhu, R. S., & Samarati, P. (1994). Access control: Principle and practice. IEEE Communications Magazine, 32(9), 40–48.

    Article  Google Scholar 

  23. Kizza, J., & Kizza, F. M. (2008). Access control, authentication, and authorization (pp. 180–208). IGI Global.

    Google Scholar 

  24. Sail, S. & Bouden, H. (2018). A multi-factor authentication scheme to strength data-storage access. In International conference on big data, cloud and applications (pp. 67–77). Springer, Cham.

  25. Anakath, A. S., Rajakumar, S., & Ambika, S. (2019). Privacy preserving multi factor authentication using trust management. Cluster Computing, 22(5), 10817–10823.

    Article  Google Scholar 

  26. Chen, H. C. J., Violetta, M. A., & Yang, C. Y. (2013). Contract RBAC in cloud computing. The Journal of Supercomputing, 66(2), 1111–1131.

    Article  Google Scholar 

  27. Xu, J., Yu, Y., Meng, Q., Wu, Q., & Zhou, F. (2020). Role-based access control model for cloud storage using identity-based cryptosystem. Mobile Networks and Applications, 1–18.

  28. Morisset, C., Willemse, T. A., & Zannone, N. (2019). A framework for the extended evaluation of ABAC policies. Cybersecurity, 2(1), 1–21.

    Article  Google Scholar 

  29. Rana, S., & Mishra, D. (2020). Efficient and secure attribute based access control architecture for smart healthcare. Journal of Medical Systems, 44(5), 1–11.

    Article  Google Scholar 

  30. Ahmadi, S., Nassiri, M., & Rezvani, M. (2020). XACBench: A XACML policy benchmark. Soft Computing, 24(21), 16081–16096.

    Article  Google Scholar 

  31. Rezvani, M., Rajaratnam, D., Ignjatovic, A., Pagnucco, M., & Jha, S. (2019). Analyzing XACML policies using answer set programming. International Journal of Information Security, 18(4), 465–479.

    Article  Google Scholar 

  32. de Carvalho, R. M., Del Prete, C., Martin, Y. S., Araujo Rivero, R. M., Önen, M., Schiavo, F. P., Rumín, Á. C., Mouratidis, H., Yelmo, J. C., & Koukovini, M. N. (2020). Protecting citizens’ personal data and privacy: joint effort from GDPR EU cluster research projects. SN Computer Science, 1(4), 1–16.

    Article  Google Scholar 

  33. Bertin, E., Hussein, D., Sengul, C., & Frey, V. (2019). Access control in the Internet of Things: A survey of existing approaches and open research questions. Annals of Telecommunications, 74(7), 375–388.

    Article  Google Scholar 

  34. Bruno, E., Gallier, R., & Gabillon, A. (2019). Enforcing access controls in IoT networks. In International conference on future data and security engineering (pp. 429–445). Springer, Cham.

  35. Yaseen, Q., Jararweh, Y., Panda, B., & Althebyan, Q. (2017). An insider threat aware access control for cloud relational databases. Cluster Computing, 20(3), 2669–2685.

    Article  Google Scholar 

  36. Yaseen, Q. & Panda, B. (2010). Predicting and preventing insider threat in relational database systems. In IFIP international workshop on information security theory and practices (pp. 368–383). Springer, Berlin, Heidelberg.

  37. Yaseen, Q., & Panda, B. (2012). Insider threat mitigation: Preventing unauthorized knowledge acquisition. International Journal of Information Security, 11(4), 269–280.

    Article  Google Scholar 

  38. Lazouski, A., Martinelli, F., Mori, P., & Saracino, A. (2017). Stateful data usage control for android mobile devices. International Journal of Information Security, 16(4), 345–369.

    Article  Google Scholar 

  39. Da Silva, C. E., Diniz, T., Cacho, N., & de Lemos, R. (2018). Self-adaptive authorization in OpenStack cloud platform. Journal of Internet Services and Applications, 9(1), 1–17.

    Article  Google Scholar 

  40. Elgedawy, I., Khurshid, S., Masood, R., & Shibli, M. A. (2018). CRESCENT+: A self-protecting framework for reliable composite web service delivery. Iran Journal of Computer Science, 1(2), 65–87.

    Article  Google Scholar 

  41. Nyrkov, A., Romanova, Y., Ianiushkin, K., & Li, I. (2018). Data processing model in hierarchical multi-agent system based on decentralized attribute-based encryption. In Energy management of municipal transportation facilities and transport (pp. 429–438). Springer, Cham.

  42. Son, H. X., Nguyen, M. H., & Vo, H. K. (2019). Toward an privacy protection based on access control model in hybrid cloud for healthcare systems. In International joint conference: 12th international conference on computational intelligence in security for information systems (CISIS 2019) and 10th international conference on European transnational education (ICEUTE 2019) (pp. 77–86). Springer, Cham.

  43. Cao, Y., Huang, Z., Yu, Y., Ke, C., & Wang, Z. (2020). A topology and risk-aware access control framework for cyber-physical space. Frontiers of Computer Science, 14(4), 1–16.

    Article  Google Scholar 

  44. Ryan, D., De Leon, M. P., Grant, N., Butler, B., Vogel, S., Mirz, M., & Lyons, P. (2019). Deriving policies from connection codes to ensure ongoing voltage stability. Energy Informatics, 2(1), 1–14.

    Google Scholar 

  45. Elmisery, A. M., Rho, S., & Aborizka, M. (2019). A new computing environment for collective privacy protection from constrained healthcare devices to IoT cloud services. Cluster Computing, 22(1), 1611–1638.

    Article  Google Scholar 

  46. Oglaza, A., Laborde, R., Zaraté, P., Benzekri, A., & Barrère, F. (2017). A new approach for managing Android permissions: Learning users’ preferences. EURASIP Journal on Information Security, 2017(1), 1–16.

    Article  Google Scholar 

  47. Krempel, E., Birnstill, P., & Beyerer, J. (2017). A Privacy-Aware Fall Detection System for Hospitals and Nursing Facilities. European Journal for Security Research, 2(2), 83–95.

    Article  Google Scholar 

  48. Amin, S. O., Siddiqui, M. S., & Hong, C. S. (2008). A novel IPv6 traceback architecture using COPS protocol. Annals of Telecommunications-Annales des Télécommunications, 63(3), 207–221.

    Article  Google Scholar 

  49. Liu, Y., Zhang, J., & Zhan, J. (2021). Privacy protection for fog computing and the internet of things data based on blockchain. Cluster Computing, 24(2), 1331–1345.

    Article  Google Scholar 

  50. Vassis, D., Belsis, P., Skourlas, C., & Pantziou, G. (2010). Providing advanced remote medical treatment services through pervasive environments. Personal and Ubiquitous Computing, 14(6), 563–573.

    Article  Google Scholar 

  51. Basile, C., Cappadonia, A., & Lioy, A. (2011). Network-level access control policy analysis and transformation. IEEE/ACM Transactions On Networking, 20(4), 985–998.

    Article  Google Scholar 

  52. Gogoulos, F. I., Antonakopoulou, A., Lioudakis, G. V., Mousas, A. S., Kaklamani, D. I., & Venieris, I. S. (2014). On the design of a privacy aware authorization engine for collaborative environments. Electronic Markets, 24(2), 101–112.

    Article  Google Scholar 

  53. Cuevas, A., Febrero, M., & Fraiman, R. (2004). An anova test for functional data. Computational Statistics & Data Analysis, 47(1), 111–122.

    Article  MATH  Google Scholar 

  54. Kim, T. K. (2017). Understanding one-way ANOVA using conceptual figures. Korean Journal of Anesthesiology, 70(1), 22–26.

    Article  Google Scholar 

  55. Górecki, T., & Smaga, Ł. (2015). A comparison of tests for the one-way ANOVA problem for functional data. Computational Statistics, 30(4), 987–1010.

    Article  MATH  Google Scholar 

  56. Deng, F., Lu, J., Wang, S. Y., Pan, J., & Zhang, L. Y. (2019). A distributed PDP model based on spectral clustering for improving evaluation performance. World Wide Web, 22(4), 1555–1576.

    Article  Google Scholar 

  57. Salesforce.com. (n.d.). 12 Benefits of Cloud Computing. https://Www.Salesforce.Com/Products/Platform/Best-Practices/Benefits-of-Cloud-Computing/. Retrieved June 5, 2021, from https://www.salesforce.com/products/platform/best-practices/benefits-of-cloud-computing/

  58. Indu, I., Anand, P. R., & Bhaskar, V. (2018). Identity and access management in cloud environment: Mechanisms and challenges. Engineering Science and Technology, an International Journal, 21(4), 574–588.

    Article  Google Scholar 

Download references

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Computer Science and Engineering & Information Technology, Jaypee University of Information Technology, Waknaghat Solan, Himachal Pradesh, India

    Gaurav Deep, Jagpreeet Sidhu & Rajni Mohana

Authors
  1. Gaurav Deep
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jagpreeet Sidhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rajni Mohana
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jagpreeet Sidhu.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deep, G., Sidhu, J. & Mohana, R. Distributed PEP–PDP Architecture for Cloud Databases. Wireless Pers Commun 128, 1733–1761 (2023). https://doi.org/10.1007/s11277-022-10017-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-022-10017-4

Keywords

Search

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy