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In edge computing environments, app vendors can cache their data to be sharedwith their users in many geographically distributed edge servers. However, thecached data is particularly vulnerable to several intentional attacks orunintentional events. Given the limited resources of edge servers andprohibitive storage costs incurred by app vendors, designing an efficientapproach to inspect and maintain the data over tremendous edge servers is acritical issue. To tackle the problem, we design a novel data inspectionapproach, named ${\text{O}^2\text{DI}}$, that provides the following services:i) using ${\text{O}^2\text{DI}}$, app vendors can inspect the data cached inedge servers without having the original data, which reduces the incurred I/Oand storage overhead significantly; ii) computational operations conducted byboth edge servers and app vendors are highly efficient because of a novelonline/offline technique; iii) many data files cached in different edge serverscan be verified quickly and at once by using a novel batch verification method;iv) corrupted data in edge servers can be localized and repaired efficiently.We analyze the security and performance of ${\text{O}^2\text{DI}}$. We see thatit is secure in the random oracle model, much faster, and more cost-effectivecompared to state-of-the-art approaches.

Federated Online/Offline Remote Data Inspection for Distributed Edge Computing