QoS oriented MapReduce Optimization for Hadoop Based BigData Application

International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc

State-of-the-art application of artificial neural network in digital watermarking and the way forward

Several high-ranking watermarking schemes using neural networks have been proposed in order to make the watermark stronger to resist attacks.The ability of Artificial Neural Network, ANN to learn, do mapping, classify, and adapt has increased the interest of researcher in application of different types ANN in watermarking.In this paper, ANN based approached have been categorized based on their application to different components of watermarking such as; capacity estimate, watermark embedding, recovery of watermark and error rate detection. We propose a new component of water marking, Secure Region, SR in which, ANN can be used to identify such region within the estimated capacity. Hence an attack-proof watermarking system can be achieved

A Comprehensive Insight into Game Theory in relevance to Cyber Security

The progressively ubiquitous connectivity in the present information systems pose newer challenges tosecurity. The conventional security mechanisms have come a long way in securing the well-definedobjectives of confidentiality, integrity, authenticity and availability. Nevertheless, with the growth in thesystem complexities and attack sophistication, providing security via traditional means can beunaffordable. A novel theoretical perspective and an innovative approach are thus required forunderstanding security from decision-making and strategic viewpoint. One of the analytical tools whichmay assist the researchers in designing security protocols for computer networks is game theory. Thegame-theoretic concept finds extensive applications in security at different levels, including thecyberspace and is generally categorized under security games. It can be utilized as a robust mathematicaltool for modelling and analyzing contemporary security issues. Game theory offers a natural frameworkfor capturing the defensive as well as adversarial interactions between the defenders and the attackers.Furthermore, defenders can attain a deep understanding of the potential attack threats and the strategiesof attackers by equilibrium evaluation of the security games. In this paper, the concept of game theoryhas been presented, followed by game-theoretic applications in cybersecurity including cryptography.Different types of games, particularly those focused on securing the cyberspace, have been analysed andvaried game-theoretic methodologies including mechanism design theories have been outlined foroffering a modern foundation of the science of cybersecurity

Development of an imputation technique - INI for software metric database with incomplete data

Software metrics are numerical data that provides a quantitative basis for the development and validation of models, and effective measurement of the software development process. Gathering software engineering data can be expensive. Such precious and costly data cannot afford to be missing. However missing data is a common problem and software engineering database is not an exception. Though there are many algorithms to solve problem of incomplete data, unfortunately few have been developed in the field of Software Engineering. Missing data causes significant problem. With inaccurate data or missing data, it is very difficult to know how much a project will cost or worth. Missing data leads to loss of information, causes biasness in data analysis and hence results to inaccurate decision-making for project management and implementation. In this paper, an imputation technique for imputing missing data based on global-local Modified Singular Value Decomposition (MSVD) algorithm, INI was proposed. This technique was used for estimating missing data in a software engineering database (PROMISE). Its performance was evaluated and compared with two existing imputation techniques, Expectation Maximization (EM) and Mean Imputation (MI). Varying percentages of missings, (1%, 10%, 15%, and 20% 25%) were introduced in the original dataset in order to have an incomplete dataset for imputation. Simulations were carried for comparative purposes. Imputation Error (IE) was use as an evaluation criterion. Imputation Error (IE) was use as an evaluation criterion. Study results showed that, the only method that consistently outperformed other methods (EM and MI), guarantee a higher accuracy of imputed data, prompt and less bias at all level of missings is the global-local MSVD, INI. It maintained consistency at all level of missings compared to EM and MI. It was found that EM is not suitable for data with missing proportion greater than 20%. While MI lost in all count to EM and INI