With　the　emergence　of　the　industrial　internet　of　things,　distributed　data　storage　systems　have　become　widely　used　to　store　the　monitoring　data　of　power　generation　systems.　Malicious　hackers　often　try　to　destroy　or　steal　these　confidential　data　by　illegally　invading　the　systems.　In　addition　to　hackers＇　illegal　intrusions,　the　availability　of　the　data　stored　is　also　affected　by　the　internal　failures　of　the　system.　In　this　research,　two　reliability　models　are　formulated　to　study　the　reliability　of　a　phased-mission　distributed　data　storage　system　considering　internal　failures　and　illegal　intrusion.　The　first　model　considers　internal　failures　and　data　destruction,　whereas　the　second　model　further　considers　data　theft.　Furthermore,　the　allocation　of　the　data　partitions　is　optimized　so　that　system　reliability　can　be　maximized.　Numerical　experiments　demonstrate　the　effectiveness　of　the　proposed　models　and　algorithms.