Embracing the latest technological strides holds immense promise for individuals, organizations, and governments. However, divergent perspectives exist on these advancements, particularly regarding safeguarding critical information, securing stored data platforms, and ensuring data accessibility. A pivotal challenge in the contemporary landscape is the escalating threat of digital terror ism, causing disruptions for individuals and institutions. This form of cybercrime, orchestrated by diverse entities like criminal organizations, skilled individuals, and digital activists, now poses a significant risk to public and national security. Intrusion Detection Systems (IDS) have been developed to address this pressing issue. The study leverages the recently introduced UNSWNB dataset to evaluate the efficacy of the chosen approach. The SVM algorithm demonstrated a commendable accuracy of 83.29. The company demonstrated its ability to effectively counter cyber threats by showcasing its potential. Moreover, they utilized a convolutional neural network (CNN) to achieve this feature outperformed, and achieved an accuracy level of 99.52 with your cybersecurity project.