Encryption is the widely used technique to offer security for video communication and considerable numbers of video encryption algorithms have been proposed. The paper explores the literature for already proposed video encryption algorithms with the focus on the working principle of already proposed video encryption schemes. This study is aimed to give readers a quick overview about various video encryption algorithms proposed so far. General TermsEncryption, video security, video encryption metric, compression, decompression.

In this paper, we have proposed parameterized security technique based on remote reference passing (RRP). RRP intrinsically works on the principle of transmitting the information or data in the form of reference at receiver side. RRP is most suitable technique to address security needs of video services while accessed/played through constrained devices because of its low power design and negligible delay during decryption process, one of stringent requirement of video transmission. Proposed technique has potential to offer varying level of perceptual encryption which makes it suitable to support different multimedia service with different security needs. This technique offer confidentiality and authentication for secure communication and further, same is also suitable for entertainment video services to facilitate pay TV, video on demand or pay per view. This technique encrypts the raw video in RGB 24 bit color space which makes its integration possible with different video codec.

In this paper, Secure Network Interface Card (SNIC) Architecture is proposed, to provide secure video communication without extra overhead on host processor of receiver. PROM based security model is developed & its integration with Network Interface is described. The approach adopted here to design SNIC, is based on remote reference passing. In this approach PROM is integrated to NIC to serve as security buffer where data values are to be placed at memory locations using some mathematical mapping which establishes relation between location reference and data. Sender generates respective location reference(at receiver's security buffer) corresponding to the each data byte of video stream. For reference creation, respective reverse mathematical mapping is used. In this, security is achieved at MAC layer at receivers end. General TermsSecurity

Facial expressions, usually has an adverse effect on the performance of a face recognition system. In this investigation, expression invariant face recognition algorithm is presented that converts input face image with an arbitrary expression into its corresponding neutral facial image. In the present study, deep learning algorithm is used to train classifiers for reference keypoints, where key-points are located and deep neural network is trained to make the system able to locate the landmarks in test image. Create an intermediate triangular mesh from the test and reference image and then warp it using affine transform and take the average of the normalized faces. To extract the features presented in the result image shift invariant feature extraction technique is used. Finally, results are compared and the recognition accuracy is determined for different expressions. The present work is tested on three different databases: JAFFE, Cohn-Kanade (CK) and Yale database. Experimental results show that the expression invariant face recognition method is very robust to variety of expressions and recognition accuracy is found to be 97.8 %, 96.8% and 95.7% for CK, JAFFE and Yale databases respectively.

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