A new method for dynamic reliability analysis of slope stability is proposed with considering the energy-time distribution. In this method

the dynamic critical slip surfaces and their factors of safety (FOS) are described as time series. The slope reliability evaluation criteria including dynamic fuzzy failure probability

dynamic reliability index and dynamic FOS

are obtained utilizing the statistical windows of duration that are extracted according to the characteristics of energy distribution of slope dynamic response. To validate the proposed method

a soil slope stability standard testing problem issued by Australian Association for Computer Aided Design (ACADS) is analyzed under the conditions of the Lushan Ms =7.0 earthquake. The differences of analysis results

which are controlled by the selection of statistical windows of duration

are studied in detail. The case study shows that: （1）The new method can yield good results by emphasizing the most significant time period.（2）The fuzzy discrimination for slope failure state significantly improves the reliability evaluation

which avoids the problem of insufficient discrimination of the traditional methods. （3）The guaranteed-probability-based dynamic FOS of slope has great potential of application and inherent the advantages for reliability analysis. Formally it is compatible with the definition of static stability FOS; quantitatively it is the conservative estimate of instantaneous FOS; and practically it compares well with the pseudo-static method in existing design specifications.（4）In this case

the locations of dynamic critical slip surfaces tend to approach the static critical slip surface. It is illustrated that a reinforcement design under a static or pseudo-static method framework still has a positive meaning in dynamic seismic conditions.（5）The new method provides a way to quantitatively determine the optimal redundancy of seismic design specifications. In summary

the new method provides new ideas

techniques and a reference example for slope seismic analysis.