Applications performing scientific computations or processing streaming media benefit from parallel I/O significantly, as they operate on large data sets that require large I/O. MPI-I/O is a commonly used library interface in parallel applications to perform I/O efficiently. Optimizations like collective-I/O embedded in MPI-I/O allow multiple processes executing in parallel to perform I/O by merging requests of other processes and sharing them later. In such a scenario, preserving confidentiality of disk-resident data from unauthorized accesses by processes without significantly impacting performance of the application is a challenging task. In this paper, we evaluate the impact of ensuring data-confidentiality in MPI-I/O on the performance of parallel applications and provide an enhanced interface, called MPISec I/O, which brings an average overhead of only 5.77% over MPI-I/O in the best case, and about 7.82% in the average case.