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Sayed, G. I., M. Soliman, and A. E. Hassanien, "Bio-inspired Swarm Techniques for Thermogram Breast Cancer Detection", Medical Imaging in Clinical Applications: Springer International Publishing, pp. 487–506, 2016. Abstract
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Hassanien, A. E., T. - H. Kim, J. Kacprzyk, and A. I. Awad, Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations, : Springer, 2014. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "Bio-inspiring Techniques in Watermarking Medical Images: A Review", Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations: Springer Berlin Heidelberg, pp. 93–114, 2014. Abstract
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Asmaa Hashem Sweidan, Nashwa El-Bendary, O. M. H. A. E. H.:, "Biomarker-Based Water Pollution Assessment System Using Case-Based Reasoning", Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2015, pp. 547-557,, Ostrava, Czech Republic, June 29 - July , 2015. Abstract

This paper presents Case-Based Reasoning (CBR) system to asses water pollution based on fish liver histopathology as biomarker. The proposed approach utilizes fish liver microscopic images in order to asses water pollution based on knowledge stored in the case-based database and stores likelihood description of the previous solutions in order to make the knowledge stored more flexible. The proposed case-based reasoning system consists of 5 phases; namely case representation (pre-processing and feature extraction), retrieve, reuse/adapt, revise, and retain phases. After applying pre-processing and feature extraction algorithms on the input images, similarity between the input and case base database is being calculated in order to retrieve similarity. Experimental results show that the performance of CBR systems increases according to the number of retrieved cases in each scenario against each strategy. The proposed system achieved 95.9

Asmaa Hashem Sweidan, N. El-Bendary, O. M. Hegazy, and A. E. Hassanien, "Biomarker-Based Water Pollution Assessment System Using Case-Based Reasoning", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 547–557, 2015. Abstract
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Amin, R., T. Gaber, G. ElTaweel, and A. E. Hassanien, "Biometric and traditional mobile authentication techniques: Overviews and open issues", Bio-inspiring cyber security and cloud services: trends and innovations: Springer Berlin Heidelberg, pp. 423–446, 2014. Abstract
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Gaber, T., Alaa Tharwat, A. E. Hassanien, and V. Snasel, "Biometric cattle identification approach based on Weber’s Local Descriptor and AdaBoost classifier", Computers and Electronics in Agriculture, vol. 122 , issue March 2016 , pp. 55–66, 2016. Website
Gaber, T., Alaa Tharwat, A. E. Hassanien, and V. Snasel, "Biometric cattle identification approach based on weber’s local descriptor and adaboost classifier", Computers and Electronics in Agriculture, vol. 122: Elsevier, pp. 55–66, 2016. Abstract
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Raffat, M. M., R. Ahmed, and A. E. Hassanien, "Blind 2D vector data watermarking approach using random table and polar coordinates", 2nd IEEE International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE) , Jalarta Turky , 14-15 Aug., pp. 67 – 70, 2012. Abstract

In this paper, a blind robust watermark approach for authentication 2D Map based on random table and polar coordinates mapping is presented. Firstly, All vertices will mapped into polar coordinate system. Then, the watermark is embedded using the random table of the decimal valued of the polar coordinates through the digit substitution of the decimal part. Theoretical analysis and excremental results shows that the presented approach is robust against a various attacks such as rotation, scaling and translation and also good imperceptibility.

Raffat, M. M., R. Ahmed, and A. E. Hassanien, "Blind 2D vector data watermarking approach using random table and polar coordinates", 2nd IEEE International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE): 14-15 Aug., 2012. Abstract
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Mouhamed, M. R., A. M. Rashad, and A. E. Hassanien, "Blind 2D vector data watermarking approach using random table and polar coordinates", Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on: IEEE, pp. 67–70, 2012. Abstract
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Raffat, M. M., R. Ahmed, and A. E. Hassanien, "Blind 2D vector data watermarking approach using random table and polar coordinates", 2nd IEEE International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE): 14-15 Aug., 2012. Abstract
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Mona M. Soliman, A. E. Hassanien, and H. M. Ons, "A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods", IJCVIP - International Journal of Computer Vision and Image Processing, vol. 3, issue 2, pp. 43-53, 2013. Website
Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods", International Journal of Computer Vision and Image Processing (IJCVIP), vol. 3, no. 2: IGI Global, pp. 43–53, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods", International Journal of Computer Vision and Image Processing (IJCVIP), vol. 3, no. 2: IGI Global, pp. 43–53, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind Robust 3D-Watermarking Scheme Based on Progressive Mesh and Self Organization Maps", Advances in Security of Information and Communication Networks: Springer Berlin Heidelberg, pp. 131–142, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind Roubst Watermarking Scheme based on Progresive Mesh and Self Organization Maps", International conference on Advances in Security of Information and Communication Networks, (SecNet 2013) , Egypt, Springer , pp. 3-5 Sept, 2013, 2013. blind_compressed_wm.pdf
Alshabrawy, O. S., A. E. Hassanien, W. A. Awad, and A. Salama, "Blind Separation of Underdetermined Mixtures with Additive White and Pink Noises", 13th IEEE International Conference on Hybrid Intelligent Systems (HIS13) Tunisia, pp. 306-312, 2013, Tunisia, 4-6 Dec, 2013.
Alshabrawy, O. S., A. E. Hassanien, W. A. Awad, and A. A. Salama, "Blind separation of underdetermined mixtures with additive white and pink noises", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 305–311, 2013. Abstract
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Mouhamed, M. R., H. M. Zawbaa, E. Al-Shammari, A. E. Hassanien, and V. Snasel, "Blind Watermark Approach for Map Authentication using Support Vector Machine", International conference on Advances in Security of Information and Communication Networks, (SecNet 2013) , Springer pp. 84–97, Cairo - Egypt, 3-5 Sept, 2013, . blind_watermark_approach_for_map_authentication_svm.pdf
Mouhamed, M. R., H. M. Zawbaa, E. T. Al-Shammari, A. E. Hassanien, and V. Snasel, "Blind watermark approach for map authentication using support vector machine", Advances in security of information and communication networks: Springer Berlin Heidelberg, pp. 84–97, 2013. Abstract
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Lamiaa M. El Bakrawy, N. I.Ghali, T. - H. Kim, and A. E. Hassanien, "A Block-wise-based Fragile Watermarking Hybrid Approach using Rough Sets and Exponential Particle Swarm Optimization ", Journal of Future Generation Communication and Networking, , vol. 4, issue 4, 2011. Abstractblock-wise-based_fragile_watermarking.pdf

In this paper, we propose a fragile watermarking hybrid approach using rough set kmeans and exponential particle swarm optimization (EPSO) systems. It is based on a block-wise dependency mechanism which can detect any alterations made to the protected image. Initially, the input image is divided into blocks with equal size in order to improve image tamper localization precision. Then feature sequence is generated by applying rough k-means and EPSO clustering to create the relationship between all image blocks and cluster
all of them since EPSO is used to optimize the parameters of rough k-means. Both feature sequence and generated secret key are used to construct the authentication data. Each resultant 8-bit authentication data is embedded into the eight least significant bits (LSBs) of the corresponding image block. We gives experimental results which show the feasibility of using these optimization algorithms for the fragile watermarking and demonstrate the
accuracy of the proposed approach. The performance comparison of the approach was also realized. The performance of a fragile watermarking approach has been improved in this paper by using exponential particle swarm optimization (EPSO) to optimize the rough kmean parameters. The proposed approach can embed watermark without causing noticeable visual artifacts, and does not only achieve superior tamper detection in images accurately,
it also recovers tampered regions effectively. In addition, the results show that the proposed approach can effectively thwart different attacks, such as the cut-and paste attack and collage attack, while sustaining superior tamper detection and localization accuracy.

El Bakrawy, L. M., N. I. Ghali, T. - H. Kim, and A. E. Hassanien, "A Block-wise-based Fragile Watermarking Hybrid Approach using Rough Sets and Exponential Particle Swarm Optimization", International Journal of Future Generation Communication and Networking, vol. 4, no. 4, pp. 77–88, 2011. Abstract
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El Bakrawy, L. M., N. I. Ghali, T. - H. Kim, and A. E. Hassanien, "A Block-wise-based Fragile Watermarking Hybrid Approach using Rough Sets and Exponential Particle Swarm Optimization", International Journal of Future Generation Communication and Networking, vol. 4, no. 4, pp. 77–88, 2011. Abstract
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Ismail, F. H., E. A. Hassan, A. E. Hassanien, and T. - H. Kim, "Blog Clustering with Committee Approach", 2015 Fourth International Conference on Information Science and Industrial Applications (ISI): IEEE, pp. 61–64, 2015. Abstract
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