Abstract:
The increasing usage of databases in the storage of critical and sensitive information in many organizations has led to an increase in the rate at which databases are exploited in computer crimes. Databases are often manipulated to facilitate crimes and as such are usually of interest during many investigations as useful information relevant to the investigation can be found therein.
A branch of digital forensics that deals with the identification, preservation, analysis and presentation of digital evidence from databases is known as database forensics. Despite the large amount of information that can be retrieved from databases and the amount of research that has been done on various aspects of databases, database security and digital forensics in general, very little has been done on database forensics. Databases have also been excluded from traditional digital investigations until very recently. This can be attributed to the inherent complexities of databases and the lack of knowledge on how the information contained in the database can be retrieved, especially in cases where such information have been modified or existed in the past.
This thesis addresses one major part of the challenges in database forensics, which is the reconstruction of the information stored in the database at some earlier time. The dimensions involved in a database forensics analysis problem are identified and the thesis focuses on one of these dimensions. Concepts such as the relational algebra log and the inverse relational algebra are introduced as tools in the definition of a theoretical framework that can be used for database forensics.
The thesis provides an algorithm for database reconstruction and outlines the correctness proof of the algorithm. Various techniques for a complete regeneration of deleted or lost data during a database forensics analysis are also described. Due to the importance of having adequate logs in order to use the algorithm, specifications of an ideal log configuration for an effective reconstruction process are given, putting into consideration the various dimensions of the database forensics problem space. Throughout the thesis, practical situations that illustrate the application of the algorithms and techniques described are given.
The thesis provides a scientific approach that can be used for handling database forensics analysis practice and research, particularly in the aspect of reconstructing the data in a database. It also adds to the field of digital forensics by providing insights into the field of database forensics reconstruction.