Workflow satisfiability problem is an elemental issue in the security planning of business process, and it is facing the performance challenge caused by high resource ratio (the number n of resources is significantly greater than the number k of steps). Under resource-independent constraints, its most efficient approach is incremental pattern backtracking (IPB) in the pattern space. To overcome the performance bottleneck of verifying whether a node is authentic, IPB computes the k-assignment (bipartite) graph of a pattern and its (left complete) matching in an incremental manner, which requires O(kn) and O(k²) time respectively. This study computes a full-assignment graph incrementally with only O(n) time by exploiting the atomic difference between a sub-pattern and its super one, and in particular its actual performance will increase rapidly with the size of a block in pattern. However, the size O(kn) of such a graph will result in the same incremental matching time. Further, this study introduces the concept of complete k core matching and shows that its existence is equivalent to a left complete matching and its incremental computation only costs O(k²) time. Therefore, this study proposes an algorithm of minimum incremental pattern backtracking (MIPB) that is superior to IPB in time complexity. Experiments are conducted on an extended public instance set with constraints of two global value-cardinality types and of the mutual exclusion, and with an authorization ratio of about 1/4. The results show that: when k varies at n/k=10 (n/k=100, respectively), MIPB achieves averagely more than 2 (5, respectively) times and at least 1.5 (2.9, respectively) times advantage of performance compared to IPB; when k=18 (k=36, respectively), and n/k belongs to 2~4096 (2~2048, respectively), MIPB achieves averagely more than 2.6 (3.6, respectively) times advantage. While compared to the champion solver OR-Tools CP-SAT in the 2018~2021 Minizinc Challenges, MIPB achieves at least more than 3 times advantage.