Finding patterns in genome of viruses in Bioinformatics is an essential and challenging task. It helps in understanding the gene activities in the context of Bioinformatics. For researchers, finding DNA motifs remains a challenging task despite concerted efforts. This study presents randomized motif search algorithm for locating motifs, its operational principles, and validation of results. The study of this type gives researchers insight into advancing the work. The research focuses on validating the identified patterns in the genomic sequence through efficient algorithmic methods. The study identifies conserved sequences called motifs, which are crucial for the virus pathogenicity. It also helps in understanding the replication capabilities of viruses. It identifies the motifs with accuracy and speed. The results indicate several motifs are present and conserved among the Zika Virus. Motif finding and validation could be a target antiviral approach. This discovery highlights genome reinforcements and a future framework for treatments. Identifying recurring patterns in biological sequences is vital in decoding gene functions and regularities. Different efficient mathematical methods are identified for motif validations. The motif-finding algorithms focus on speed and accuracy. We propose validation techniques to assess the reliability of identified motifs. This research provides valuable insights for bioinformatics researchers, guiding them for efficient motif-finding and validation strategies.