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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM64305

User Data-Centric Authentication for Network Data Retrieval

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64305

Volume:

10 |

5 |

May 2026

Pages:

1-10

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SP

SK. Pujitha

Computer Science and Engineering

Guru Nanak Institute of Technology

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VV

Vemula Vigneshwari

Computer Science and Engineering

Guru Nanak Institute of Technology

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JVK

Javaji Vijay Kumar

Computer Science and Engineering

Guru Nanak Institute of Technology

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VMK

Vanga Madhu Krishna

Computer Science and Engineering

Guru Nanak Institute of Technology

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Mentors

GL

Gugulothu Lakpathi

Computer Science and Engineering

Guru Nanak Institute of Technology

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Abstract

Big data has created a strong demand for secure and efficient data retrieval in modern network environments. Information-Centric Networking (ICN) enables data to be cached within the network, allowing users to retrieve data from nearby cache locations instead of centralized servers. Although this improves performance and reduces delay, it also introduces security threats such as malicious-request attacks and data-poisoning attacks. Existing systems mainly provide authentication only between users and publishers and suffer from increased authentication delay due to dependency on centralized certificate servers. To overcome these issues, this project proposes a secure Data-Centric Authentication framework called DCAuth using the Suspension-Chain Model (SCM). The proposed system integrates certificate collection with packet forwarding to establish secure authentication among users, routers, publishers, and network entities without relying heavily on centralized servers. The framework reduces authentication delay, prevents fake-data propagation, and improves secure big-data retrieval in ICN environments. Experimental analysis shows that DC Auth enhances network security, reliability, and overall performance compared to existing approaches.

KEYWORDS

Information-Centric Networking (ICN) Data-Centric Authentication Big Data Retrieval SuspensionChain Model (SCM) DCAuth Data Poisoning Attack Network Security.

Cite This Article

SK. Pujitha, Vemula Vigneshwari, Javaji Vijay Kumar, Vanga Madhu Krishna, Gugulothu Lakpathi, "User Data-Centric Authentication for Network Data Retrieval," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-10, May 2026.

Full Article/Conclusion

Our project “User Data-Centric Authentication for Network Data Retrieval” provides a secure and efficient authentication framework for Information-Centric Networking (ICN) environments. The proposed DC Auth mechanism uses the Suspension Chain Model (SCM) to establish secure communication among users, routers, publishers, and network entities. The system effectively reduces authentication delay and prevents malicious-request and data-poisoning attacks during big-data retrieval. By integrating certificate management, packet forwarding, and secure caching, the framework improves network security, reliability, and scalability. The proposed solution supports efficient in-network data retrieval while minimizing dependency on centralized servers. However, further improvements can be made in areas such as advanced attack detection, large-scale deployment, and performance optimization. Overall, DC Auth provides a strong foundation for future secure and scalable ICN-based communication systems. 

References

[1] N. Khan, I. Yaqoob, I. Hashem, Z. Inayat, W. Ali, M. Alam, M. Shiraz, andA. Gani, “Big Data: Survey, Technologies, Opportunities, and Challenges,”The Scientific World Journal , Vol. 2014, 2014. [2] H. Yin, Y. Jiang, C. Lin, Y. Luo, and Y. Liu, “Big data: Transforming thedesign philosophy of future Internet,” IEEE Network, vol. 28, no. 4, pp.14-19, July 2014. [3] S. Yu, and S. Guo (Eds.), “Big Data Concepts, Theories, and Applications,” Springer 2016, ISBN 978-3-319-27761-5. [4] J. Saltzer, D. Reed, and D. Clark, “End-to-end arguments in systemdesign,” ACM Transactions on Computer Systems, 2 (4), pp. 277-2881984. [5] S. Yu, M. Liu, W. Dou, X. Liu, and S. Zhou, “Networking for Big Data:A Survey,” IEEE Communications Surveys and Tutorials, Vol. 19, Issue 1,pp. 531-549, 2017. [6] B. Ahlgren, C. Dannewitz, C. Imbrenda, D. Kutscher, and B. Ohlman,“A survey of information-centric networking,” IEEE CommunicationsMagazine, 50(7), pp.26-36, 2012. [7] T. Koponen, M. Chawla, B.-G. Chun, A. Ermolinskiy, K. H. Kim, S.Shenker, and I. Stoica, “A data-oriented (and beyond) network architecture,” ACM SIGCOMM 2007, Aug. 2007. [8] P. Jokela, A. Zahemszky, C. E. Rothenberg, S. Arianfar, and P. Nikander,“LIPSIN: Line Speed Publish/Subscribe Inter-Networking,” Proceedingsof the ACM SIGCOMM 2009, pp. 195-206, Aug. 2009. [9] A. Ghodsi, S. Shenker, T. Koponen, A. Singla, B. Raghavan, and J.Wilcox, “Information-centric networking: seeing the forest for the trees,”Proceedings of the 10th ACM Workshop on Hot Topics in Networks, 2011. [10] S. K. Fayazbakhsh, Y. Lin, A. Tootoonchian, A. Ghodsi, T. Koponen, B.Maggs, K. Ng, V. Sekar, and S. Shenker, “Less pain, most of the gain:incrementally deployable icn,” Proceedings of the ACM SIGCOMM 2013conference, pages 147-158, 2013.

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Publication Date

5/30/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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