Many methods optimizing the on-chip cache utilization are dependent on the profile or identification of the access sequence characteristics, for instance, prefetcher or bypass etc. How to identify these characteristics is still an open problem. Through a detailed theoretical analysis of typical access patterns, it is shown that the frequency of stack distance has obvious features. Furthermore, according to the results of the Simics simulation, these features present persistent and stable to a certain extent, therefore, they are feasible to be identified and predicted. An online method based on the peak value of the collected stack histogram attaching to each core is provided. In addition, the storage and time overhead is small. The experimental results based on 15 benchmarks from SPEC CPU2000/2006 show that it identifies all correctly.