Over the years, the proliferation of internet data and its widespread usage has contributed to increase in threats to security. Many new technologies are transforming the face of the world in the real environment of today. Nevertheless because of these emerging technologies, we are unable to secure our private information in a very effective manner and these days' cybercrimes are growing day by day. Several methods such as authentication, firewall, cryptography and steganography are used to safeguard this vast amount of data on the internet. Hence, this research aims at protecting the privacy of big data applications using the Advanced Encryption Standard (AES) technique and the Least Significant Bit (LSB) steganography technique. This proposed algorithm hides the generated cipher text using the AES algorithm inside a cover image to hide the presence of the cipher text using the LSB technique. Based on the PSNR, SNR, SSIM and MSE values obtained, it can be concluded that the proposed system is robust and reliable.
Nowadays, organizations collect volumes of data for future analysis. Motivated by this amount of data and requirements of Web 2.0, a plethora of non-relational databases (NoSQL) emerged in recent years. However, several security features in relational databases (e.g., access control) have been left in non-relational management systems to be developed by the application, which can raise security breaches. This paper proposes two distinctive security model, based on the use of metadata, to provide access control for NoSQL graph-oriented database management system and organization based system. The goal is to support the development of applications that use graph-oriented database in preserving the integrity of stored data and protect them from non-authorized access. A case study has been performed as proof of concept, where the model has been instantiated and implemented for Neo4j database. A network management data security technique for executives based on NoSQL is suggested for better assurance of Organization based security systems. These are the two distinctive security models presented in this study.
Dense Image Captioning task describes the objects within an image by identifying them and their surroundings and establishing a relationship between them. The architecture comprises a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) language model that generates the captions. This project requires a system making use of computer vision to both find regions and describe them in natural language. The images are passed through a Convolutional network to identify the region features. These features then form the input for the Recurrent neural network, which generates the captions for the regions encompassing the relationships between the objects.
In the medical field, telemedicine, smart health and e-health, are cutting-edge technologies. These technologies utilize digital medical information for end-user communication. Even though this digitalization reduces time, it is a open source for hackers. Hence, hackers can tamper the digital medical image during broadcast. In the medical field, most of the investigations are done through X-rays, MRI and CT scan images. Security must be provided to maintain secrecy of diseases for avoiding the panic in the patients and for improving the degree of security in the image broadcast through internet. The DNA cryptography provides powerful security to enhance the probability of preventing from the brute-force and statistical analysis attacks. In this paper, two level security is provided using DNA codons. In first level, image is encrypted into DNA sequences by selecting key. In second level, codons are generated with dynamic numbers for encryption of image and construct DNA alphabets. In this technique, the encrypted image is in hidden format so that it is very difficult for attacker with known image attacks. The experimental results of the proposed technique are investigated with histogram based method and statistical analysis attacks and confirmed the superior security level in the protection of the image transmission.
Mobile Ad hoc Network (MANET) is the significant technology among various wireless communication technologies where all the nodes are mobile and which can be connected to dynamically used wireless link in a random manner. They connect or disconnect from the active network any time and transfer packets in a single or a multicast mode. Nodes are connected by way of wireless links and form a random topology. This research paper focuses on, performance comparison of a new Intrusion Detection Systems (IDS), Secure-Enhanced Adaptive 3 Acknowledgement with hybrid cryptography's EA3ACK-MARS4 and EA3ACK-ECC specially designed for MANET. Furthermore, all the above mentioned protocols are compared based on several important performance metrics which are Packet Delivery Ratio (PDR), end-toend delay and average energy via one of the efficient networking routing protocol called Network Simulator 2 (Ns2). It is used to implement and test the suggested system under various size of topology with different constant sets of nodes as well as comparing the results with two different protocols.
