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Volume-4 Issue-7, December 2017, ISSN: 2319-9598 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.

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Gaurav Choudhary, Manju

Paper Title:

Energy Components Based Image Fusion Technique for Both Gray Scale and Color Images

Abstract: In this paper, an image fusion scheme based on Hilbert vibration decomposition (HVD) is proposed. In this proposed technique, the images to be fused are first enhanced and then converted into 1-D signals which are decomposed using the HVD technique into different components called energy components. These energy components are fused by taking the average of corresponding energy components except the last component having least energy. Simulation results of the proposed technique are carried out in MATLAB and its performance is compared with other existing techniques using some commonly used performance metrics. It is seen that the proposed technique gives better visual appearance of the fused image than other existing techniques and the values of the several performance metrics are also better/comparable with other techniques. The simulation results obtained for color images show that the proposed algorithm works well for color images in HSI color space also.

Keywords: Image Fusion; Image Enhancement; Hilbert Vibration Decomposition.


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Rethishkumar S., R. Vijayakumar

Paper Title:

An Efficient Co-Resident Dos Attack Defense Mechanism for Cloud Computing using Two-Player Security Game Approach

Abstract: For cloud computing systems, Virtual Machines (VM) were conceived as the basic component. However, VMs give effective computing resources; they were prone to lots of security threats. Whereas few threats can be easily rectified, but few attacks like co-resident attacks were tedious process to identify. So, to reduce the co-resistance DOS attacks by creating it as tedious for attackers to initiate attacks, two-player game approach based defense mechanism is suggested in our work. The attacker behavior variations among the attacker and normal users under PSSF VM allocation policy, is examined initially in the proposed mechanism. EDBSCAN (Enhanced Density-based Spatial Clustering of Applications with Noise), is utilized to do the clustering analysis process. Based on the clustering algorithm, the Partial labeling is performed, to partially comprehend the users as legal or malicious. In order to classify the nodes, the semi-supervised learning using Deterministic Annealing Semi-supervised SVM (DAS3VM) optimized by branch and bounds method is performed. The two-player security game approach helps to raise the cost of introduction new VMs therefore reducing the probability of initiating co-resident DOS attack, once after the user accounts were classified. Therefore, the security threats can be avoided effectively with the help of the proposed defense mechanism. Experimental result confirms that the suggested co-resident DOS attack defense mechanism makes a desirable involvement to avoid the security threats.

Keywords: Co-Resident DOS Attack, PSSF, EDBSCAN, DAS3VM, Branch and Bound Method. 


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