Biblio

Securing data, management of the authorised access of the user and maintaining the privacy of the data are some of the problems relating with the stored data in the database. The security of the data stored is considered as the major concern which is to be managed in a very serious manner as the users are sensitive about their shared data. The user's data can be protected by the process of cryptography which is considered as the conventional method. Advanced Encryption Standard (AES), Data Encryption Standard(DES), Two Fish, Rivest Shamir Adleman Algorithm (RSA), Attribute Based Encryption (ABE), Blowfish algorithms are considered as some of the cryptographic algorithms. These algorithms are classified into symmetric and asymmetric algorithms. Same key is used for the encryption and decoding technique in symmetric key cryptographic algorithm whereas two keys are used for the asymmetric ones. In this paper, the implementation of one of the asymmetric algorithm RSA with the educational dataset is done. To secure the distributed database, the extended version of the RSA algorithm is implemented as the proposed work.

There are two types of network architectures are presents those are wired network and wireless network. MANETs is one of the examples of wireless network. Each and every network has their own features which make them different from other types of network. Some of the features of MANETs are; infrastructure less network, mobility, dynamic network topology which make it different and more popular from wired network but these features also generate different problems for achieving security due to the absence of centralized authority inside network as well as sending of data due to its mobility features. Achieving security in wired network is little-bit easy compare to MANETs because in wired network user need to just protect main centralized authority for achieving security whereas in MANETs there is no centralized authority available so protecting server in MANETs is difficult compare to wired network. Data sending and receiving process is also easy in wired network but mobility features makes this data sending and receiving process difficult in MANETs. Protecting server or central repository without making use of secrete sharing in wired network will create so many challenges and problem in terms of security. The proposed system makes use of Secrete sharing method to protect server from malicious nodes and `A New particle Swarm Optimization Method for MANETs' (NPSOM) for performing data sending and receiving operation in optimization way. NPSOM technique get equated with the steady particle swarm optimizer (PSO) technique. PSO was essentially designed by Kennedy, Eberhart in 1995. These methods are based upon 4 dissimilar types of parameters. These techniques were encouraged by common performance of animals, some of them are bird assembling and fish tuition, ant colony. The proposed system converts this PSO in the form of MANETs where Particle is nothing but the nodes in the network, Swarm means collection of multiple nodes and Optimization means finding the best and nearer root to reach to destination. Each and every element study about their own previous best solution which they are having with them for the given optimization problem, likewise they see for the groups previous best solution which they got for the same problem and finally they correct its solution depending on these values. This same process gets repeated for finding of the best and optimal solutions value. NPSOM technique, used in proposed system there every element changes its location according to the solution which they got previously and which is poorest as well as their collection's earlier poorest solution for finding best, optimal value. In this proposed system we are concentrating on, sidestepping element's and collections poorest solution which they got before.

Swarm Intelligence (SI) algorithms, such as Fish School Search (FSS), are well known as useful tools that can be used to achieve a good solution in a reasonable amount of time for complex optimization problems. And when problems increase in size and complexity, some increase in population size or number of iterations might be needed in order to achieve a good solution. In extreme cases, the execution time can be huge and other approaches, such as parallel implementations, might help to reduce it. This paper investigates the relation and trade off involving these three aspects in SI algorithms, namely population size, number of iterations, and problem complexity. The results with a parallel implementations of FSS show that increasing the population size is beneficial for finding good solutions. However, we observed an asymptotic behavior of the results, i.e. increasing the population over a certain threshold only leads to slight improvements.