This study explores the utilization of artificial intelligence (AI) within the realm of data analytics and extraction methodologies, specifically focusing on its role in information security. As advancements in information technology accelerate, concerns over information security are escalating. Incidents such as cyber-attacks and data breaches have become increasingly commonplace, posing significant risks to individual privacy, corporate assets, and national security interests. This paper first summarizes the importance of data analysis and mining technology in the field of information security, and points out its application in network attack detection, user behavior analysis and sensitive information protection. This paper introduces the basic theory and process of data mining in detail, including key steps such as data collection, preprocessing, mining, result evaluation and knowledge representation. Data mining techniques, such as classification and prediction, cluster analysis, association rule mining and anomaly detection, have been applied to different scenarios, showing their unique advantages. In order to cope with the limitations of traditional methods in dealing with complex and covert network attacks, this paper introduces anomaly detection technology based on deep learning, especially the Transformer model using self-attention mechanism. This model can capture long-distance dependencies in data, and is suitable for processing information security data with time series characteristics, such as user login mode and transaction frequency. The experimental results show that the anomaly detection method based on Transformer model performs well on KDD Cup 99 data set, and compared with traditional methods such as support vector machine (SVM) and random forest (RF), it has significantly improved accuracy, recall and F1 score, and it is more efficient when dealing with large-scale data. The research in this paper not only improves the accuracy and efficiency of anomaly detection in the field of information security, but also provides strong support for formulating more scientific and reasonable security strategies.