This paper discusses the application of logistic regression to detect attacks on financial monitoring. Financial organizations are facing increasing security threats, which requires effective methods to detect fraudulent activities. Logistic regression, with its binary classification capability and interpretability of results, is a powerful tool for transaction analysis. The paper also emphasizes the features of this method, including its applicability to large amounts of data and opportunities for model development. Thus, the use of logistic regression is a promising solution for securing financial transactions and identifying potential threats.
keywords: Logistic regression, financial monitoring, attack detection, fraudulent transactions, binary classification, interpretability.
