An efficient privacy preserving and public auditing data integrity verification protocol for cloud-based online learning environments
L. Jegatha Deborah, Shanmugam Milton Ganesh, P. Vijayakumar · 2023
Ever since the onset of COVID-19, governments and educational organizations have understood the significance of e-learning education systems for continuing education during lockdown periods. This paradigm shift has come with noticeable needs for security procedures for efficient integrity verification for the e-learning contents uploaded to the cloud storage servers. In spite of many works in the past, the need for computationally efficient protocol is still a concern. The research in this chapter is one of the pioneering attempts in data integrity verification for e-learning scenarios and it strives to address the issues of e-learning data integrity verification in three contexts. First is the invention of a novel integrity verification mechanism utilizing the security strength of elliptic curve cryptography. The second context is that of careful design of the protocol with lesser numbers of computationally expensive operations to suit diverse devices. The third context focuses on enabling support for public auditing mechanisms for the proposed protocol. This research work has been implemented using the pbc library 0.5.12 and the results suggest that the proposed protocol is better than previous works in terms of computational and communication overheads.