Watermark Decoding Technique using Machine Learning for Intellectual Property Protection

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Mr. R. Senthil Ganesh


The Watermarking is an Intellectual Property (IP) Protection method. It can ensure Field-Programmable Gate Array (FPGA) IPs from encroachment. The IP security of equipment and programming structures is the most significant prerequisite for some FPGA licensed innovation merchants. Advanced watermarking has become a creative innovation for IP assurance as of late. This paper proposes the Publicly Verifiable Watermarking plan for licensed innovation insurance in FPGA structure. The Zero-Knowledge Verification Protocol and Data Matrix strategy are utilized in this watermarking location method. The time stepping is likewise utilized with the zero-information check convention and it can versatility oppose the delicate data spillage and implanting assaults, and is along these lines hearty to the cheating from the prover, verifier, or outsider. The encryption keys are additionally utilized with the information lattice technique and it can restrict the watermark, and make the watermark vigorous against assaults. In this proposed zero-information technique zero rate asset, timing and watermarking overhead can be accomplished. The proposed zero-information watermarking plan causes zero overhead. In this proposed information lattice technique signal-rich-workmanship code picture, can be portrayed. The proposed information network watermarking plan encodes the copyright confirmation data. The zero-information confirmation convention and information grid technique proposed in this paper is executed by MATLAB R2014a in which C programming language is utilized in it and ModelSim 10.5b in which VHDL coding is utilized in it, are running on a PC. The combination instrument Xilinx ISE 14.5 is likewise used to confirm and actualize the watermarking plan.


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Mr. R. Senthil Ganesh. (2019). Watermark Decoding Technique using Machine Learning for Intellectual Property Protection . International Journal of New Practices in Management and Engineering, 8(03), 01–09. https://doi.org/10.17762/ijnpme.v8i03.77