Zusammenfassung
Advancement in Information and technology results in use informational system on a large scale. This informational system consisting of the relational databases stored over the network and shared by different owners in a collaborative environment for decision-making and knowledge extraction purpose. Sharing these database results in the security threats such as data tampering and ownership rights. Medical data are also stored and shared by the different health organization over the cloud network. This medical data are also targeted by the attacker to manipulate or misuse the original data for their benefits. Thus, this data which are stored and shared over the cloud network needs to be taken care by implementing some powerful security mechanism. Watermarking technique are used as powerful security mechanism for ownership protection and data tampering from the malicious attackers. However, using the watermarking technique results in the modification of the original data that degrade the data quality and results in data distortation. Thus, reversible watermarking techniques are used for data protection along with data recovery. There are various reversible watermarking techniques available such as Reversible Watermarking Technique (RRW), Difference Expansion Watermarking Technique (DEW), Genetic Algorithm based on Difference Expansion (GADEW), Prediction Error Expansion Watermarking technique (PEW), and Quantization Index Modulation (QIM). The proposed system is the combination of the RRW technique and QIM technique along with distortion control for selecting the appropriate features for watermarking and data recovery. The proposed method will be more secured and robust against the attack with less data distortion and higher data recovery, implemented for relational datasets of medical healthcare system.
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