Abstract. The secure preservation of biomedical image data is a primary concern in today's technology enabled medical world. The new advancements in the technology are insisting us to outsource our digital data to a third party server and bring as and when needed. In this regard, efficient storage and transmission of this large medical data set becomes an important concern. In this paper we studied different compression techniques as a significant step of data preparation for implementing searchable encryption of medical data privacy preservation. We also shown texture based feature extraction for enabling privacy preserving query search. The simulation results obtained using different modalities of CT and MRI images with the performance comparison of wavelet and contourlet transform in peak signal to noise ratio for different compression ratios.
Currently, model based development of web services is being actively researched for its usefulness in developing a system. Various techniques like EPC, petrinet, process algebra, CPN and UML have been proposed for web service modeling. FSM is found appropriate to model Business requirements because a business process on execution moves forward from one state to other. We have shown uses of FSM (Finite State Machine) based models in development of web services ; also have developed a tool HUMSAT to model service specification in FSM and to generate executable codes in BPEL and WSDL. However, automated code generation depends on correct specification of models as an improperly specified model leads to errors and bugs in resultant code. Hence model checking plays an important role in eliminating the flaws at design phase itself. In this paper, we propose a technique for model verification that identifies structural flaws e.g. unreachability, deadlock and temporal inconsistencies. Further, HUMSAT is augmented with the model verification features.
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