Title: An Optimized Pattern Recognition Algorithm for Anomaly Detection in IoT Environment,
Abstract: With the advent of large-scale heterogeneous search engines comes the problem
of unified search control resulting in mismatches that could have otherwise
avoided. A mechanism is needed to determine exact patterns in web mining and
ubiquitous device searching. In this paper we demonstrate the use of an
optimized string searching algorithm to recognize exact patterns from a large
database. The underlying principle in designing the algorithm is that each
letter that maps to a fixed real values and some arithmetic operations which
are applied to compute corresponding pattern and substring values. We have
implemented this algorithm in C. We have tested the algorithm using a large
dataset. We created our own dataset using DNA sequences. The experimental
result shows the number of mismatch occurred in string search from a large
database. Furthermore, some of the inherent weaknesses in the use of this
algorithm are highlighted.