Visible to the public Biblio

Filters: Author is Praveenkumar, Padmapriya  [Clear All Filters]
2021-08-31
B.D.J., Anudeep, Sai N., Mohan, Bhanuj T., Sai, Devi, R. Santhiya, Kumar, Vaishnavi, Thenmozhi, K., Rengarajan, Amirtharajan, Praveenkumar, Padmapriya.  2020.  Reversible Hiding with Quick Response Code - A Responsible Security. 2020 International Conference on Computer Communication and Informatics (ICCCI). :1—5.
In this paper, Reversible data hiding using difference statistics technique incorporating QR codes was proposed. Here, Quick Response (QR) codes were employed as an additional feature and were hidden in the corners of the original image to direct to the hyperlink after authentication and then embedding the secret data bits was carried out. At the receiver side, when the QR codes were scanned by the user, the link to the webpage was accessed, and then the original image and the secret data bits were recovered by using the proposed reversible data hiding scheme. In the proposed scheme, the pixels of the cover image were scanned in row-major order fashion, and the differences between the adjacent pixels were computed, keeping the first pixel unaltered to maintain the size of the host and the difference image same. Now, the histogram was shifted towards the right or left to reduce the redundancy and then to embed the secret data bits were done. Due to the similarity exists between the pixel values, the difference between the host and the secret image reconstructs the marked image. The proposed scheme was carried out using MATLAB 2013. PSNR (Peak Signal to Noise Ratio) and payload have been computed for various test images to validate the proposed scheme and found to be better than the available literature.
2020-06-26
Betha, Durga Janardhana Anudeep, Bhanuj, Tatineni Sai, Umamaheshwari, B, Iyer, R. Abirami, Devi, R. Santhiya, Amirtharajan, Rengarajan, Praveenkumar, Padmapriya.  2019.  Chaotic based Image Encryption - A Neutral Perspective. 2019 International Conference on Computer Communication and Informatics (ICCCI). :1—5.

Today, there are several applications which allow us to share images over the internet. All these images must be stored in a secure manner and should be accessible only to the intended recipients. Hence it is of utmost importance to develop efficient and fast algorithms for encryption of images. This paper uses chaotic generators to generate random sequences which can be used as keys for image encryption. These sequences are seemingly random and have statistical properties. This makes them resistant to analysis and correlation attacks. However, these sequences have fixed cycle lengths. This restricts the number of sequences that can be used as keys. This paper utilises neural networks as a source of perturbation in a chaotic generator and uses its output to encrypt an image. The robustness of the encryption algorithm can be verified using NPCR, UACI, correlation coefficient analysis and information entropy analysis.

2020-01-07
Aparna, H., Bhoomija, Faustina, Devi, R. Santhiya, Thenmozhi, K., Amirtharajan, Rengarajan, Praveenkumar, Padmapriya.  2019.  Image Encryption Based on Quantum-Assisted DNA Coded System. 2019 International Conference on Computer Communication and Informatics (ICCCI). :1-4.

Information security is winding up noticeably more vital in information stockpiling and transmission. Images are generally utilised for various purposes. As a result, the protection of image from the unauthorised client is critical. Established encryption techniques are not ready to give a secure framework. To defeat this, image encryption is finished through DNA encoding which is additionally included with confused 1D and 2D logistic maps. The key communication is done through the quantum channel using the BB84 protocol. To recover the encrypted image DNA decoding is performed. Since DNA encryption is invertible, decoding can be effectively done through DNA subtraction. It decreases the complexity and furthermore gives more strength when contrasted with traditional encryption plans. The enhanced strength of the framework is measured utilising measurements like NPCR, UACI, Correlation and Entropy.