CCA: A Methodical Vendee Vendor Carbon Copy Algorithm for Data Trading

International Journal of Computer Science and Engineering

© 2019 by SSRG - IJCSE Journal

Volume 6 Issue 3

Year of Publication : 2019

Authors : M. Ayisha Siddhiqua, T. Arivulagarasi, M. Kanmani, V. Lakshmi, B.Ezhilarasi

10.14445/23488387/IJCSE-V6I3P105

How to Cite?

M. Ayisha Siddhiqua, T. Arivulagarasi, M. Kanmani, V. Lakshmi, B.Ezhilarasi, "CCA: A Methodical Vendee Vendor Carbon Copy Algorithm for Data Trading," SSRG International Journal of Computer Science and Engineering , vol. 6,  no. 3, pp. 19-22, 2019. Crossref, https://doi.org/10.14445/23488387/IJCSE-V6I3P105

Abstract:

Owing to the meteoric growth of Internet and cyberspace technology, digital data (images, audios, videos and datasets) can be seized easily. On one hand, this helps people to share digital merchandise with others. Contrarily illegal copies are produced and distributed with little efforts. To deter piratism and protect the proprietorship of digital products, digital carbon copy technology is introduced. A carbon copy is an imperceptible copy of the digital data maintained before selling, which can be detected later for vendee/vendor identification, ownership proof, traitor tracing and so forth. Vendee vendor carbon copy algorithm is designed to hinder clients from unjustly distributing copies of digital content. In this paper, an anonymous and interactive Carbon Copy Algorithm (CCA) is proffered, which is designed to be impartial and efficient. To solve the unbinding problem and the vendees’ right problem, operations of carbon copy generation and digital content selling are performed by a Trusted Third Party in the proposed scheme. Vendees and vendors have equal rights and responsibilities, and computational and corresponding overhead is lessened. We show that the proposed protocol is highly accurate, secure and efficient.

Keywords:

Proprietorship protection, unbinding problem, vendees’ right problem, traitor tracing

References:

[1] S. Brin, J. Davis, and H. Garcia-Molina. Copy detection mechanisms for digital documents. In SIGMOD, volume 24, pages 398–409. ACM, 1995.
[2] M. Felici, T. Koulouris, and S. Pearson. Accountability for data governance in cloud ecosystems. In CloudCom, volume 2, pages 327– 332. IEEE, 2013.
[3] T. Truderung, A. Vogt, et al. Accountability: definition and relationship to verifiability. In CCS, pages 526–535. ACM, 2010.
[4] L. Zhang, T. Jung, C. Liu, X. Ding, X.-Y. Li, and Y. Liu. Pop: Privacy preserving outsourced photo sharing and searching for mobile devices. In IEEE ICDCS. IEEE, 2015.
[5] A. Z. Broder. On the resemblance and containment of documents. In Compression and Complexity of Sequences, pages 21–29. IEEE, 1997.
[6] X. Cao, Y. Chen, and K. R. Liu. An iterative auction mechanism for data trading. In ICASSP, pages 5850–5854. IEEE, 2017.
[7] Y. Xiao. Flow-net methodology for accountability in wireless networks. Network, IEEE, 23(5):30–37, 2009.
[8] L. Zhang, X.-Y. Li, K. Liu, T. Jung, and Y. Liu. Message in a sealed bottle: Privacy preserving friending in mobile social networks. TMC, 14(9):1888–1902, 2015.
[9] S. Delgado-Segura, C. P´erez-Sol`a, G. Navarro-Arribas, and J. Herrera- Joancomart´ı. A fair protocol for data trading based on bitcoin transactions. Future Generation Computer Systems, 2017.
[10] X.-Y. Li, C. Zhang, T. Jung, J. Qian, and L. Chen. Graph-based privacy preserving data publication. In INFOCOM, pages 1–9. IEEE, 2016.