As the virtual landscape continues to enlarge, the proliferation of cyber threats poses extraordinary demanding situations to the security of records structures. This assessment paper examines the symbiotic courting among facts technology and cyber security, with a primary awareness at the application of anomaly detection techniques. The paper provides a top level view of the contemporary country of cyber security, highlighting the numerous array of threats faced in the digital age. It then delves into the role of records science in fortifying cyber security defenses, exploring ideas such as device getting to know, artificial intelligence, and statistical analysis. The center of the assessment centers on anomaly detection methodologies, dissecting the strengths and barriers of strategies like unsupervised device learning, deep learning, and ensemble techniques. Real-world case research illustrate the sensible software of those techniques in diverse cyber security situations. The overview concludes by using addressing existing challenges within the integration of statistics technological know-how into cyber security and speculating on future guidelines for studies and development. In essence, this evaluation underscores the pivotal function of information technology, especially in anomaly detection, as a linchpin for protecting the digital frontier towards evolving and complex cyber threats.

cyber security, data science, threat detection, artificial intelligence, anomaly detection, false positives, interpretability