Forensic investigation framework for the document store NoSQL DBMS: MongoDB as a case study

The NoSQL DBMS provides an efficient means of storing and accessing big data because its servers are more easily horizontally scalable and replicable than relational DBMSs. Its data model lacks a fixed schema, so that users can easily dynamically change the data model of applications. These characteristics of the NoSQL DBMS mean that it is increasingly used in real-time analysis, web services such as SNS, mobile apps and the storage of machine generated data such as logs and IoT (Internet of Things) data. Although the increased usage of the NoSQL DBMS increases the possibility of it becoming a target of crime, there are few papers about forensic investigation of NoSQL DBMS. In this paper, we propose a forensic investigation framework for the document store NoSQL DBMS. It is difficult to cover all of the NoSQL DBMS, as 'NoSQL' includes several distinct architectures; our forensic investigation framework, however, is focused on the document store NoSQL DBMS. In order to conduct an evaluative case study, we need to apply it to MongoDB, which is, a widely used document store NoSQL DBMS. For this case study, a crime scenario is created in an experimental environment, and then we propose in detail a forensic procedure and technical methods for MongoDB. We suggested many substantial technical investigation methods for MongoDB, including identifying real servers storing evidences in a distributed environment and transaction reconstruction method, using log analysis and recovering deleted data from the MongoDB data file structure.