Rethinking Data Security in Aggregated Databases: Beyond Encryption

In today's digital landscape, the proliferation of cloud-based applications and databases has become commonplace. To fortify data security in this dynamic environment, organizations employ various safeguards, including encryption. Column Level Encryption and Transparent Data Encryption are also commonly adopted strategies for securing database data. Encryption, when appropriately implemented, may serve as a formidable barrier against unauthorized access, safeguarding sensitive information from prying eyes. Nevertheless, this paper seeks to underscore a critical point for IT professionals: encryption does not inherently shield against the inference of valuable business insights through data in aggregate. For instance, it is possible to discern the growth rate of a user base by analyzing the number of records within specific tables acquired at specific intervals. In the paper, we introduce straightforward, quantifiable techniques designed to obfuscate genuine data, camouflage aggregate information so the only way to analyze the data is to decrypt first. Furthermore, we explore the limitations and potential drawbacks of these camouflage strategies. By shedding light on these considerations, this paper aims to enrich the discourse surrounding data security in cloudbased environments, offering valuable insights into safeguarding sensitive information while preserving the confidentiality of aggregated data.