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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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1.

Authors:

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.

References: 

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  19. Naidu, V. P. S., and Bindu Elias. "A Novel Image Fusion Technique using DCT based Laplacian Pyramid." International Journal of Inventive Engineering and Sciences (IJIES), pp. 2319-9598, 2013.
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  21. Dong, Weihua, Xian'en Li, Xiangguo Lin, et al. “A Bidimensional Empirical Mode Decomposition Method for Fusion of Multispectral and Panchromatic Remote Sensing Images.” Remote Sensing, vol. 6, no. 9, pp. 8446-8467, 2014.
  22. Ehsan, Shoaib, Syed Muhammad Umer Abdullah, et al. “Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition.”Sensors, vol. 15, no. 5, pp. 10923-10947, 2015.
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  25. Sharma, H., and K. K. Sharma. "Baseline wander removal of ECG signals using Hilbert vibration decomposition." Electronics Letters, vol.51, no. 6, pp. 447-449, 2015.
  26. Chen, Soong-Der, and Abd Rahman Ramli. "Minimum mean brightness error bi-histogram equalization in contrast enhancement."  IEEE Trans. on Consumer Electronics, vol. 49, no. 4,pp. 1310-1319, 2003.
  27. Naik, Sarif Kumar, and C. A. Murthy. "Hue-preserving color image enhancement without gamut problem." IEEE Trans. on Image Processing, vol. 12, no. 12, pp. 1591-1598, 2003.
  28. Haghighat, Mohammad Bagher Akbari, Ali Aghagolzadeh, and Hadi Seyedarabi. "A non-reference image fusion metric based on mutual information of image features." Computers & Electrical Engineering 37, vol. 5, pp. 744-756, 2011.
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2.

Authors:

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. 

References: 

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  5. Zhang, Y., Juels, A., Oprea, A., Reiter, M.K.: HomeAlone: Co-Residency Detection in the Cloud via Side-Channel Analysis. In: Proceedings of 2011 IEEE Symposium on Security and Privacy, Berkeley (2011)
  6. Keller, E., Szefer, J., Rexford, J., Lee, R.B.: Eliminating the hypervisor attack surface for a more secure cloud. In: Proceedings of ACM Conference on Computer and Communications, Security (CCS’11) (2011)
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  8. Bier, V. M., & Azaiez, M. N. (Eds.). (2008). Game theoretic risk analysis of security threats(Vol. 128). Springer Science & Business Media.
  9. Han, Y., Chan, J., Alpcan, T., & Leckie, C. (2014, June). Virtual machine allocation policies against co-resident attacks in cloud computing. In 2014 IEEE International Conference on Communications (ICC)(pp. 786-792). IEEE.
  10. Han, Y., Alpcan, T., Chan, J., Leckie, C., & Rubinstein, B. I. (2016). A game theoretical approach to defend against co-resident attacks in cloud computing: Preventing co-residence using semi-supervised learning. IEEE Transactions on Information Forensics and Security, 11(3), 556-570.
  11. Yinqian Zhang, Ari Juels, Alina Oprea (2011) “Home Alone: Co-Residency Detection in the Cloud via Side-Channel Analysis” 2011 IEEE Symposium on Security and Privacy.
  12. Adam Bates, Benjamin Mood, Joe Pletcher, Hannah Pruse, Masoud Valafar (2010) “Detecting Co-Residency with Active Traffic Analysis Techniques”.
  13. Han Y, Tansu Alpcan, Jeffrey Chan, Christopher Leckie, (2011) “Security Games for Virtual Machine Allocation in Cloud Computing”.
  14. Yu, S.: Distributed Denial of Service Attack and Defense. Springer, 2014.
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  17. Ismail, M.N., Aborujilah, A., Musa, S., Shahzad, A.: Detecting ooding based dos attack in cloud computing environment using covariance matrix approach. In: Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, p. 36. ACM, 2013.
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