In view of the diversity of cryptographic service types and complex interdependencies between cryptographic tasks in cryptographic clouds， leading to frequent communication between heterogeneous cryptographic engines， which can cause large communication latencies， a mathematical model for optimal low-latency task mapping for cryptographic services for data dependency types in cryptographic clouds was constructed. The objective of the model is to minimize the maximum service completion time. And it is proved that the problem is an Non-deterministic Polynomial hard （NP-hard） problem. To this end， an efficient heuristic scheduling algorithm was designed. Firstly， a task-length threshold mechanism was established on the basis of historical scheduling data analysis for initial task allocation optimization. Secondly， a critical task identification method was used to locate potential latency bottleneck tasks， and the scheduling order of critical tasks was adjusted dynamically to reduce the impact on the overall completion time. Finally， a task transfer-execution time balancing strategy was adopted to further optimize the distribution of tasks between heterogeneous engines， so as to reduce the overall task latency. Experimental results show that on a small-scale dataset， the average gap between the cryptographic service completion time of the proposed algorithm and the optimal solution is only 8.67%， with a scheduling speed improvement of 8.62 times. On a large-scale dataset， the cryptographic service completion time is reduced by 84.67% and 82.15% compared to the random and long-task-first methods， respectively.