Collecting Digital Data with the Assurance of Integrity.

Abstract

It is very common today that systems collect and store sensitive information. The database administrators of these types of systems have access to this sensitive information and can manipulate it. Therefore, data integrity is of core importance in these systems, and methods to detect fraudulent behavior need to be implemented. The objective of this article is to evaluate the features and performance impact of different methods for achieving and implementing data integrity in a database during data collection to improve assurance. Five methods for achieving data integrity were tested. The methods were tested in a controlled environment. This paper evaluates traditional Digital signature, Linked timestamping applied to a Merkle hash tree, and Auditing performance impact and feature impact wise. Two more methods were implemented and tested in a controlled environment, Merkle hash tree and Digital watermarking. In the evaluation, the researcher proved that traditional Digital signature is faster than Linked timestamping. In this study, it was concluded that when choosing a data integrity method to implement, it is of great importance to know which type of operation is more frequently used. The experiments show that the Digital signature method performed better than Linked timestamping and Auditing. Keyword: Data Collection, Integrity, Assurance, Security, Cyber space, cybercrimes,