With　the　advancement　of　cloud　computing　and　internet　of　things,　data　are　usually　stored　on　distributed　computers　and　these　data　may　risk　being　lost　or　stolen.　In　this　article,　we　consider　a　common　case　where　the　entirety　of　the　data　is　partitioned　into　several　parts　and　each　data　part　can　be　allocated　to　one　or　more　computers.　In　the　case　where　a　computer　fails,　all　the　data　parts　on　it　are　lost.　Before　the　failure　of　any　computer,　the　data　parts　may　also　be　stolen　by　hackers.　The　basic　model　of　computer　failure　and　computer　intrusion　resulting　in　the　theft　of　all　the　data　parts　on　the　computer　is　considered　first.　Then,　the　case　is　extended　to　a　general　model　where　computer　failure,　as　well　as　data　part　corruption　and　theft　caused　by　hacking　are　embedded.　It　is　essential　to　study　the　reliability　of　distributed　storage　systems　considering　both　data　loss　and　data　theft,　which　can　be　a　basis　for　decision　making　on　system　structure　optimization.　In　this　article,　a　multi-valued　decision　diagram-based　approach　is　developed　to　quantitatively　evaluate　system　reliability　for　both　models　considering　the　time-dependence　property　of　sequential　events.　The　proposed　method　is　applicable　to　systems　where　the　random　time　to　failure,　theft,　or　corruption　follows　arbitrary　distributions　including　the　commonly　used　exponential　distributions.　Illustrative　examples　are　provided　to　validate　the　proposed　method.