Encryption of Video over WiFi - Coursework Example

Video Encryption (College) Video Encryption 0 Introduction In cryptography, the encryption process is the process ofdata transformation with the aid of an algorithm or mathematical functions limiting the access of information to only those with private keys. For a very long time the security of our information has been ensured through data encryption techniques. Since each and every day this security gets compromised, there has been major strides towards the betterment of data security. This encompasses both audio, written as well as visual information that is vital and needs restricted access. Based on this subject, the growing quantity of video data modified in various forms has made it difficult to come up with standard algorithms that would see to it that all encryptions are impermeable. Ever since 1977 Data Encryption Standard (DES) has been one of the most commonly used encryption standards. However, twenty one years after the stipulated year the method was reported to have grown susceptible to attacks. Due to increase in new encryption standard, various ciphers had to be developed with the development still underway. The security measures include AES, DES, MARKS, RSA, Serpent, teo fish, blow fish, IDEA and GHOST. Furthermore other systems like the Chaotic System and the frequency domain algorithms have since been developed (Talewad, 2013 pp.1). This study purposes to reveal the necessary procedure that can be used for video encryption. The involved algorithm makes it possible to sequentially encrypt and decrypt video. This is applicable in MATLAB as we are about to encounter in the study. In the modern day, cryptography is mainly characterized by complex mathematical algorithms due to advanced technology from malicious people. 2.0 Background The reverse of encryption is decryption, a process which will only enable the recipient with the required key to view the information (Hashim & Neamaa, 2014, pp.141). On social networks as YouTube, Facebook and Twitter, at times videos get post with blurred effects some of which cannot be decrypted to reveal the actual people involved. This is therefore an implication that video encryption is not only to enable specific people get information but can also be used to send factual information about realities to the open. During signal transmission, encryption locks out the third party. Kester (2013) in his discussion on image encryption reveal the necessity of security in the current era we live in. The encryption level of a video primly depends on the method used to secure the digital content. Neural network has started to play a major role in information security. Most of the algorithms used are mainly generic since key exchange has become a prerequisite prior to exchange of the data. Therefore the ability of such encryption solely depends on the length of the key. In today’s world, encryption process has employed random substitutions and impurity addition (doping) resulting to more confusion and misguide the cryptanalyst to obtain tend. This technique employs use of artificial neural networks to obtain the original video. The abolishing of the key exchange and the usage of artificial neural network to provide high security are some of the major strengths observed in the present work. 3.0 Video Encryption 3.1 Requirements Socek et al (2005) talks about application specific-video encryption and its importance in the multimedia society. Socek et al further presents the necessary requirements for video encryption as discussed below: a) Perceptual quality control: Perception quality can intentionally be degraded by an encryption algorithm, however, the video will still be kept visually perceivable. b) Codec standard compliance: A premanufactured standard-conforming encoder as well as decoder is the components in a typical video system. On top of this is a video encryption method. c) Format compliance: There could be necessity for an encryption algorithm to preserve the compression format of the video. This will enable the ordinary decoders to still decode the encrypted video in full performance. d) Constant bitrate: Encryption transformation should preserve the size of a bit stream. In that case the resultant output from an encryption-equipped encoder and that from an ordinary encoder have similar sizes if not same. e) Minimal processing speed: Encryption and decryption algorithms should be fast in real-time video application so that minimal processing speed is realized. 3.2 Encryption Algorithms Of late there has been several proposals on video encryption algorithms. Some of the proposed algorithms seem effective while others do lack efficiency factor. Let us now examine a few algorithms based on (Kulkami et al, 2013, pp.3-4): a) Simple Permutation: This method encrypts every byte in the video stream using algorithms such as AES and DES. In this algorithm, the video bit stream is cindered to be a standard text data. It involves single byte encryption hence high security level. b) Pure Scrambling: Permutation operation enables video bytes in each frame to get shuffled. This is a useful algorithm it applications in which video is decoded by hardware. Unfortunately, it happens to be susceptible to plain text attacks and should therefore be cautiously handled. c) Crisscross Permutation: This algorithm generates 64 byte permutation list that that is quantized into 8x8 block. Application of random permutation list follows afterwards to the split blocks. Result encoding then occurs. Just like pure scrambling, this algorithm cannot withstand known-plaintext attack. It has lowered video compression rate. d) Choose and Encrypt: An implementation of a methodology as the one presented by this algorithm causes great decrease in complexity and encryption/decryption. Should a better trade off get maintained between complexity and security then this algorithm stands a chance of being successful. 3.3 The Encryption process. Below is a diagrammatic representation of the encryption process. The presented encryption process takes effect before the actual video encoding. This is an implication that there is possibility in performing encryption prior to encoding. Figure 1.0 4.0 Artificial Neural Networks Gershenson (2010) states that and an artificial networks are the types of network that sees the nodes as ‘artificial neurons’. This networks are generally simplified models of the biological systems of nerves. They are highly interconnected massively parallel distributed processing elements called neurons in an architecture aspect. Each neurons is linked to the other through a direct communication links each having an associated weight. Usually neural networks are adjusted or trained so that a specific target input leads to specific output as shown Figure 2.0 Courtesy of IOSR Journal of Electronics and Communication Engineering 4.1 Encryption System Design The system design for encryption can be broadly divided into two, that is; i. Modules-encryption. ii. Modules-decryption. In the encryption module, the video is usually encrypted and at the receiving end the user in the remote system decrypts it by feeding in the received data to the decryption module using artificial neural networks. An example of the procedure of showing an Encryption module is shown below. Usually the image to be encrypted is read pixel by pixel and then the transformation is done on them using permutation, impurity addition and substitution. There are two levels of encryption that assist the user to obtain high level of image encryption. The steps are shown below. Step1 This step involves one having to get the pixel value of the video file that is to be encrypted. For instance [01000011] that is; 0*2^7+1*2^6+0*2^5+0*2^4+0*2^3+0*2^2+1*2^1+1*2^0= [67] Step2 After identifying the number of pixels in this step one is supposed to divide the pixel byte value into upper and lower nibble, for instance [0100 and 0011]. Upper nibble are basically the first four digits of the binary code while the lower nibbles are the last four digits of the binary code. Step3 In this step the binary nibbles are exchanged and then they concatenate to form a byte, for instance [00110100]. Step4 In step four the user is supposed to calculate the impurity by EX-O-ring the original MS nibble and nibble, [0111].that is to mean; 0 0=x 1 0=0 0 1=1 0 1=1 0 0=x =0111 0 1=1 1 0=x 1 0=x Step5 After calculation of the impurity the bits are shifted by 5 bits to the right. Now we will be having a total of 9bit number. [011100000] Step6 EX-OR the results you found in step 3 and step 5[011010100] =212. Step7 Add impurity to the obtained result in step 6. In this case the Impurity Value chosen is 117, [212+117]. Step8 After all is done till step 7 in this step you are requested to continue step1 to step7 for all the pixels of the video File till they are all done then proceed to step 9. Addition of two columns Step9 When you are done repeating for all the other remaining pixels an additional two columns are added and the value of 117 is added to the first new column and 627 is added to the second new column. This is so that you can be able to normalize the matrix. Second level encryption: Step10 For the second level of encryption, you are required to add another level of impurity to the resultant matrix obtained in step9 such that impurity varies with respect to the position of the pixel. 4.2 Analysis and Results For the purpose of evaluating the discussed mechanism, the encryption and decryption workings have been displayed below. The displays are the results of the encryption process obtained from the MATLAB program experiment. We can begin by showing the resultant graphs in the encryption experiment. The end results for this experiment can be graphically displayed as follows: Graph (a) Graph (b) Graph (c) Graph (d) Let us now draw focus on the actual encryption process itself. The images displayed bellow entail information obtained from the MATLAB software upon code execution. The end result has been summarized by the graphs as we are about to observe. Figure 5.0 is more of a cypher text. Figure 3.0 Figure 4.0 Figure 5.0 Figure 6.0 Figure 7.0 Figure 8.0 Figure 9.0 Figure 10.0 Figure 11.0 Figure 12.0 Figure 13.0 Figure 14.0 We can now finalize our experiment my looking at the functionality results of our cryptographic algorithm. The first image (Image 1.0) is an encrypted image while the last image (Image 3.0) displays the results after decryption has occurred. Basically, the images before encryption appease the same as that after decryption hence satisfying the intended aim of the entire process. Image 1.0 Image 2.0 Image 3.0 5.0 Conclusion This project is heavily based on the Artificial Neural Networks technique as presented by Gujral & Pradhan (2005). The technique has enabled us to employ simple combinational logic machine as well as sequential machine. In order to improve these results, one has to improve the code or come up with a better algorithm. This study has explored a video encryption algorithm as well as mentioned other proposed algorithms commonly used in the video industry. With advanced cryptosystem it is able to comfortable pass information without the fear of its leakage. Another common area where we observe video encryption is during reporting of news in televisions. Such encryption is only meant to prevent sensitive viewers from frustration. Therefore we could say that video encryption does not only involve hiding the entire video from unintended audience but also preventing some body parts especially the face from being seen. Encryption can be done both via local storage devices or the internet. This implies that there are various kinds of algorithms that used for various modes of video encryption. Reference List Kulkami, A., Kulkarni, S., Haridas, K., More, A. 2013. Proposed Video Encryption Algorithm v/s Other Existing Algorithms: A Comparative Study. International Journal of Computer Applications. (0975-8887). Vol. 65-No. 1. Hashim, H.R. & Neamaa, I.A. 2014. Image Encryption and Decryption in a Modification of ElGamal Cryptosystem in MATLAB. International Journal of Sciences: Basic and Applied Research (IJSBARS). ISSN 2307-4531. Vol. 14-No.2, pp. 141-147. Kester, Q.A. 2013. Image encryption based on the RGB PIXEL Transposition and Shuffling. I.J. Computer Network and Information society. DOI: 10.5815/ijcnis.2013.07.05, pp.43-50. Retrieved from http://www.mecs-press.org Socek, D. Magliveras, S. Culibrk, D., Margues, O., Kalva, H. & Furht, B. 2005. Digital Video Encryptions Algorithms Based on Correlated-Preserving Permutations. Florida Atlantic University, Boka Ratan FL 33431. PP.1-24 Talewad, B. R.2013 .Video Encryption and Decryption with Authentication using Artificial Neural Networks: Volume 6, Issue 6. Karnataka, India Gershenson, C. Artificial Neural Networks for Beginners. Retrieved from Gershenson@sussex.ac.uk Gujral, V., & Pradhan, S.K. 2005. Cryptography Using Artificial Neural Networks. Department of Electronics and Communication Engineering National Institute of Technology Rourkela – 769008 Orissa, pp. 1-60 Read More