DescriptionThe Log4Audit framework, I developed in my dissertation creates a centralized processing engine that captures necessary events from an application log, analyzes them and provides real time monitoring. Based on design research methodology, I find the motivation in the scarcity of studies that utilize large volumes of information contained in system and application logs. The purpose of my work is to provide detailed view of Log4Audit framework I developed and illustrate its capabilities in anomaly detection and management’s assertions guidance. My dissertation follows the design research methodology. The framework is the first attempt to alleviate the problems of alienated applications employed by an organization to perform different business functions. I provide the theoretical basis to an optimal structure of the Log4Audit framework and application logs that fit a wide range of objectives of a business process. Although there is a wide range of capabilities of the framework, I focus on its theoretical foundation, implemented tool stack and the illustration of Log4Audit capabilities to provide additional data for audit evidence and assistance in management decision making process. In my observational case studies I determine the robustness of Log4Audit framework. These anomaly detection and management’s assertions case studies illustrate the powerful capabilities of the Log4Audit framework.