Information security in cloud computing refers to the protection of data items such as text, images, audios and video files. In the modern era, data size is increasing rapidly from gigabytes to terabytes or even petabytes, due to development of a significant amount of real-time data. The majority of data is stored in cloud computing environments and is sent or received over the internet. Due to the fact that cloud computing offers internet-based services, there are various attackers and illegal users over the internet who are consistently trying to gain access to user’s private data without the appropriate permission. Hackers frequently replace any fake data with actual data. As a result, data security has recently generated a lot of attention. To provide access rights of files, the cloud computing is only option for authorized user. To overcome from security threats, a security model is proposed for cloud computing to enhance the security of cloud data through the fingerprint authentication for access control and genetic algorithm is also used for encryption/decryption of cloud data. To search desired data from cloud, fuzzy encrypted keyword search technique is used. The encrypted keyword is stored in cloud storage using SHA256 hashing techniques. The proposed model minimizes the computation time and maximizes the security threats over the cloud. The computed results are presented in the form of figures and tables.

Cloud Computing has been the most popular approach of computing due to faster access to folders and files at a low cost. Hence, many organizations are shifting the old long database folders and files over the cloud which may be text, audio, video or in the other formats. Due to large size of the database with multiple storages of folders and files over the cloud, there may be chances of duplicate access of the database folders and files which may cause the loss of time of execution or accessing the database files. In the present work, a technique is developed to remove duplicate files in the form of .txt, .doc, .jpg, .pdf as well as duplicate folders after applying a well-known ElGamal algorithm later on converted as fuzzy ElGamal technique, for faster retrieval of files in a very secure manner. For this purpose, Unified Modelling Language (UML) model is developed which has been implemented through Python programming language. The computed results towards the model’s efficiency have been depicted through tables and graphs, on a large database in the form of folders and files of Indian railway reservation system. The present work is significant for the large organizations and also useful for the users working over the cloud for faster accessing of the folders and files.

During the past years, it is observed from the literature that, identification of the brain tumor identification in human being is gaining popularity. Diagnosing any disease without manual interaction with great accuracy makes computer science research more demanding, therefore, the present work is related to identify the tumor clots in the affected patients. For this purpose, a well-known Safdarganj Hospital, New Delhi, India is consulted and 2165 Magnetic Resonance Images (MRI) of a single patient are collected through scanning, and interpolation technique of numerical method used to identify the accurate position of the brain tumor. A system model is developed and implemented by the use of Python programming language and MATLAB for the identification of affected areas in the form of a contour of a patient. The desired accuracy and specificity are evaluated using the computed results and also presented in the form of graphs.

Naval military units are convoluted frameworks required to work in specific time periods in seaward assignments where support operations are radically restricted. A decline at the time of mission is an analytical fact that can radically impact the mission achievement. The choice of changing a unit to a mission subsequently requires complex judgments including data about the well being status of hardware and the natural conditions. The present system expects to help the choice about changing a unit to a mission considering that ambiguity and unpredictability of information by methods of fuzzy concepts and imitates the selection procedure of a human trained by means of a rule-based inference system. A numerical application is introduced to demonstrate the viability of the approach.

Regression testing is used to check that changes in the some functionality of the software to not affect its old behaviours. Test case prioritization is essential for reducing the cost of regression testing. In this paper a test cases prioritization model based on fuzzy logic is presented. State machine diagram is used to capture the behaviour of the system. Risk information is associated with the states. After change in the functionality of the system new state machine diagram is designed. This new state machine diagram is converted into Weighted Extended Finite State Machine (WEFSM). Weights are assigned to nodes and edges based on change and risk exposure. Risk exposure and change information of each test case is used as input to fuzzy model. Test cases are categorized in retestable, reusable and obsolete.