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Information security has always been important in all aspects of life as technology controls various operations. Cryptography provides a layer of security in cases where the medium of transmission is susceptible to interception, by translating a message into a form that cannot be read by an unauthorized third party. All non-quantum transmission media known today are capable of being intercepted in one way or another. This paper seeks to implement a novel partial pipelined, robust architecture of Blowfish algorithm in hardware. Blowfish algorithm has no known cryptanalysis. The best proven attack against Blowfish till date is an exhaustive brute-force attack. This makes Blowfish an attractive cryptographic algorithm since it is not susceptible to any reasonable attack. The hardware implementation of Blowfish would be a powerful tool for any mobile device, or any technology requiring strong encryption. The proposed design uses the core_slow library for worst-case scenario analysis and attains an incredible encryption speed of 2670 MBits/sec and decryption speed of 2642 MBits/sec. The area is 5986 LUT's and the power is a mere 77 mW.

Due to the huge advancement in technology, digitizing the multimedia content like text, images and videos has become easier. Everyday huge amounts of multimedia content are shared through the social networks using internet. Sometimes this multimedia content can be hacked by the hackers. This will lead to the misuse of the data. On the other hand, the medical content needs high security and privacy. Motivated by this, joint secured medical image compression–encryption mechanisms are proposed in this paper using multiscale transforms and symmetric key encryption techniques. The multiscale transforms involved in this paper are wavelet transform, bandelet transform and curvelet transform. The encryption techniques involved in this paper are international data encryption algorithm (IDEA), Rivest Cipher (RC5) and Blowfish. The encoding technique used in this paper is embedded block coding with truncation (EBCOT). Experimental results are done for the proposed works and evaluated by using various parameters like Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Image Quality Index (IQI) and Structural Similarity Index (SSIM), Average Difference (AD), Normalized Cross-correlation (NK), Structural Content (SC), Maximum difference (MD), Laplacian Mean Squared Error (LMSE) and Normalized Absolute Error (NAE). It is justified that the proposed approaches in this paper yield good results.