Abstract Now a day an information security is a major issue in an IT Sector. An information security becomes complex and more important problem. Much of an organization does their expenditure on securing their data. Achieving security of the local server is not a big issue, but the problem comes When sensitive information transmitted over a wireless network. Encryption/ decryption can be an important... Now a day an information security is a major issue in an IT Sector. An information security becomes complex and more important problem. Much of an organization does their expenditure on securing their data. Achieving security of the local server is not a big issue, but the problem comes When sensitive information transmitted over a wireless network. Encryption/ decryption can be an important tool to help in improving information security. This paper focus on a concept of data hiding process through the use of fabbonacci series that get helps in randomize pixel selection. Randomize approach for pixel selection helps to achieve a good match between original carrier and resultant carrier. we developed techniques for securing data to avoid hacking as well as providing the user with some additional features such as key for integrity and validation of user. In this technique one can secure any type of files by hiding it in carrier media using Fibonacci series. The proposed algorithm is loss-less, key-dependent. Read More Read Less

Abstract A great deal of advances in innovation has offered fame to Cloud computing. It has turned into the most every now and again use answer for undertakings that need to focus on their data transactions and bit less worry on their infrastructures. Yet at the same time a few enterprises are not utilizing cloud facilities. The studies delights that security threats are... A great deal of advances in innovation has offered fame to Cloud computing. It has turned into the most every now and again use answer for undertakings that need to focus on their data transactions and bit less worry on their infrastructures. Yet at the same time a few enterprises are not utilizing cloud facilities. The studies delights that security threats are the motivation behind why cloud computing isn’t utilized as a specified goal. Cloud ventures questions security threats of the cloud. There are various kinds of security challenges for Cloud infrastructure. Such threats are identified as confidentiality, integrity, availability, accountability and privacy. In this work, we focus on the information integrity as characteristic of security. Since, in the wake of putting away information to cloud, client doesn’t have even an inkling where the information is put away. The client’s information should be put away in verified way. Hence, the proposed method PKI based RDIC concept to ensure the correctness of stored in cloud with the help of third party verifier. Read More Read Less

Abstract Clustering as an unsupervised method is used as a solution technique in various fields to divide and restructure data to become more significant and to transform them into useful information. Currently, clustering is being a difficult problem and complex phenomena since an appropriate number of clusters is unknown, the large number of potential solutions, and the dataset being unsupervised. The problems can be... Clustering as an unsupervised method is used as a solution technique in various fields to divide and restructure data to become more significant and to transform them into useful information. Currently, clustering is being a difficult problem and complex phenomena since an appropriate number of clusters is unknown, the large number of potential solutions, and the dataset being unsupervised. The problems can be addressed by Multi-objective Particle Swarm Optimization (MOPSO). In Knowledge Discovery settings, complex optimization problems are globally explored with Particle Swarm Optimization (PSO). Lack of appropriate leader selection method becomes a serious issue associated with PSO techniques. In an attempt to address this problem, we proposed a clustering-based method that utilizes the crowding distance (CD) technique to balance the optimality of the objectives in Pareto optimal solution search. We evaluated our method against five clustering approaches that have succeeded in optimization, these are: The K-means Clustering, the IMCPSO, the Spectral clustering, the Birch, and the average-link algorithms. The results of the evaluation show that our approach exemplifies the state-of-the-art methods with significance difference in all most all the tested datasets. Read More Read Less