Informatics Publishing Limited

Shimaa Ali ¹, Mona Shokair ², Moawad I. Dessouky ³, Nagy Messiha ², Hala S. El-Sayed ²

Affiliations
1 Electronics and Electrical Communications Department, Menoufia, University, Menouf, EG
2 Electronics and Electrical Communications, Department, Menoufia, University, Menouf, EG
3 Electronics and Electrical Communications, Department, Menoufia, University, Menouf, EG

Abstract

This paper investigates the spectrum handoff problem in Cognitive Radio Network. Making the   Handoff decision in wireless networks designs is one of the most challenging issues because the sources of information that available are interpreted qualitatively, inexactly or uncertainly and there are many parameters which have to take into account when the secondary user makes the handoff decision. Secondary user makes handoff if it cannot modify its transmitted power within the tolerable interference limits or if the quality of service received by a secondary user is not satisfactory. This paper proposes a fuzzy based approach that able to make effective spectrum handoff decisions using new information for handoff operation. The parameters data rate, the received power at the secondary user from the primary user and the probability of primary user's occupancy are considered as inputs of the proposed system. Therefore, it reduces the probability of spectrum handoff. Consequently; the performance of Secondary user's communication will be improved.

Keywords

Cognitive Radio, Fuzzy Logic Control, Spectrum Handoff.

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Ayman E. A. Abdelaal ¹, Fathi E. Abd El-Samie ², Moawad I. Dessouky ¹

Affiliations
1 Menoufia University, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG

Abstract

The demand on high bandwidth internet connections and applications is growing very fast due to the variety of internet arising usage either on business or entertainment. The Internet Service Providers (ISPs) have to enhance their internal networks in terms of bandwidth utilization and resources management. Two different technologies have been provided to help in solving the bandwidth utilization issues inside the ISPs networks, the diffserv Quality of Service (diffserv-QoS) and the Multi-Protocol Label Switching-Traffic Engineering (MPLS-TE). In this paper, the two technologies are used in conjunction with each other to get the highest performance, the best resources management and the efficient bandwidth utilization.

Keywords

MPLS-TE, Diffserv-QoS, VPN.

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Rania A. Ghazy ¹, El-Sayed M. El-Rabaie ², Moawad I. Dessouky ², Nawal A. El-Feshawy ³, Fathi E. Abd El-Samie ³

Affiliations
1 Department of Electronics and Communications, Menoufia University, Menouf, EG
2 Department of Electronics and Communications, Menoufia University, Menouf-32952, EG
3 Department of Electronics and Communications, Menoufia University, Menouf-32952, EG

Abstract

Intrusions and attacks have become a very serious problem in network world. This paper presents a statistical characterization of packet counts that can be used for network intrusion detection. The main idea is based on detecting any suspicious behavior in computer networks depending on the comparison between the correlation results of control and data planes in the presence and absence of attacks using histogram analysis. Signal processing tools such as median filtering, moving average filtering, and local variance estimators are exploited to help in developing network anomaly detection approaches. Therefore, detecting dissimilarity can indicate an abnormal behavior.

Keywords

Anomaly Detection, Statistics, Network Intrusion Detection Systems (NIDS).

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Rania A. Ghazy ¹, El-Sayed M. El-Rabaie ², Moawad I. Dessouky ², Nawal A. El-Feshawy ², Fathi E. Abd El-Samie ²

Affiliations
1 Menoufia University, Menouf, EG
2 Department of Electronics and Communications, Menoufia University, Menouf-32952, EG

Abstract

This Paper proposes a network based intrusion detection approach using anomaly detection in the presence of Denial of Service attacks (DoS). Flood based attacks are a common class of DoS attacks. DoS detection mechanisms that aim at detecting floods mainly look for sudden changes in the traffic and mark them anomalous. In this approach, network traffic is decomposed into control and data planes to study the relationship between them. As the data traffic generation is based on control traffic, the behavior of the two planes is expected to be similar during normal behavior. Therefore, detecting dissimilarity between the traffic of the two planes can indicate an abnormal behavior. Toward that objective, an Auto Regressive (AR) model has been used. Simulation results show that both the accuracy of the detection and less false positives.

Keywords

Auto Regressive (AR), Denial-of-Service (DoS), Network Intrusion Detection Systems (NIDS).

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Nahed Tawfik ¹, Mahmoud Fakhr ², Moawad I. Dessouky ³

Affiliations
1 Computers and Systems Department, The Electronics Research Institute, EG
2 Electronics and Communications Department, Cairo University, IN
3 Department of Electronics and Electrical Communications, Menoufia University, IN

Abstract

This paper presents a proposed method for corneal pattern classification using a Cepstral approach and SVMs. This approach based on the transformation of the corneal image to 1D signal, the feature extraction process and finally the classification process. MFCCs are one of the best feature extraction techniques used in 1D signal. This approach composed of two phases: a training phase and testing phase. In the first phase, a database of the corneal patterns is applied to obtain features from each corneal image, and then these features are used to train Support Vector Machines. In the second phase, features are extracted with the same steps in training phase from a set of new corneal images and finally a feature matching process is carried out. In this work, 1D signal used with time domain or in different discrete transform domains. The experimental results indicate that this technique achieves high classification rate up to about 100%.

Keywords

Corneal Images, MFCCs, Support Vector Machines (SVMs), DCT, DST, and DWT.

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Abdelrahman Selim ¹, Moawad I. Dessouky ², Mohiy M. Hadhoud ², Fathi E. Abd El-Samie

Affiliations
1 Menoufia University, Menouf, EG
2 Menoufia University, EG

Abstract

In this paper, we study the affect of using the spiral architecture instead of the square block decomposition in fractal compression. Comparisons with other systems like the conventional square and the simplified fractal compression systems are presented. A comparison with standard JPEG system is also introduced. We apply these types of fractal compression on a video sequence. We have found that in the case of using the spiral architecture in fractal compression, the produced or decoded image or video has a better visual quality than that produced with the conventional square system and the previously presented simplified system. We found also that all types of fractal compression are better than the JPEG standard.

Keywords

Image Compression, Fractal, Decomposition, Spiral.

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Nahed Tawfik ¹, Mahmoud Fakhr ¹, Al-Nuaimy Waleed ², Moawad I. Dessouky ³, Fathi E. Abd EI-Samie ⁴

Affiliations
1 Computers and Systems Department, The Electronic Research Institute, EG
2 Department of Electrical and Electronic Engineering, University of Liverpool, GB
3 Department of Electronics and Electrical Communications, Menoufia University, EG
4 Menoufia University, Menouf, EG

Abstract

In this paper, a new technique for feature extraction from corneal images is presented which can be applied for corneal pattern recognition. Most of the previous methods are based on segmentation of the corneal images which are restricted to certain planes. In this paper, a proposed method is applied on corneal images which have two main phases. Firstly, the 2-D images are lexicographically ordered to 1-D signals, and then the Mel Frequency Cepstral Coefficients (MFCCs) and polynomial coefficients are extracted from these 1-D signals or from their transforms. Secondly, the SVM is used to match the extracted features in the testing phase to those of the training phase. Experimental results show that the recognition rate for features extracted from Discrete Sine Transform DST and Discrete Cosine Transform (DCT) achieve better performance compared to other cases. The method in this paper is limited to feature extraction for pattern recognition and the automatic diagnosis case is left for future work.

Keywords

Corneal Images, Pattern Recognition, Mel Frequency Cepstral Coefficients (MFCCs), Polynomial Coefficients, Support Vector Machine (SVM), Discrete Cosine Transforms (DCT), Discrete Sine Transforms (DST), Discrete Wavelet Transforms (DWT).

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Zeinab F. Elsharkawy ¹, Safey A. Abdelwahab ¹, Moawad I. Dessouky ², Sayed M. Elaraby ³, Fathi E. Abd El-Samie ²

Affiliations
1 Engineering Department, Nuclear Research Center, Atomic Energy Authority, Cairo, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG
3 Engineering Department, Nuclear Research Center, Atomic Energy Authority, Cairo, IN

Abstract

Scanner identification is the ability to discern the devices by which an image was scanned. In this paper, a new and robustness individual source scanner identification scheme is proposed. This scheme formulates a unique fingerprint for each scanner using traces of dust, dirt, scratches, and source imperfection pattern over scanner platen on scanned images. A single Support Vector machine (SVM) classifier is implemented and trained using correlation features of scanned images to classify different scanners brands and different models for the same scanner brand, and a 99.79% detection accuracy is obtained. In addition, the robustness of the used individual source scanner identification scheme on resized different resolutions is experimentally tested. The aging effect is also experimentally tested by re-applying the proposed algorithm on the scanned images after a continuous usage of the scanners under test for certain long periods. The experimental results using the proposed classifier for different scanner brands and different models for the same scanner brand approved the validity, efficiency, and robustness of the proposed scheme to match the scanned image to its unique source.

Keywords

Image Classification, Digital Image Forensics, Support Vector Machine.

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Amany F. Eldaoshy ¹, Moawad I. Dessouky ², Al-Dalil Sami ³, Fathi E. Abd El-Samie ²

Affiliations
1 Department of Electronics and Electrical Communications, Menoufia University, Menouf-32952, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf 32952, EG
3 Department of Electronics and Electrical Communications, Menoufia University, Menouf 32952, EG

Abstract

This paper presents a block-by-block SVD watermarking algorithm with variable block sizes. The paper makes a comparison between the traditional method of Liu and the proposed method. In the proposed approach, the original image is divided into blocks, and then the watermark is embedded in the singular values (SVs) of each block, separately. This segmentation and watermarking on a block-by-block basis makes the watermark more robust to the attacks such as noise, compression, cropping and other attacks as the results reveal. Watermark detection is implemented by extracting the watermark from the SVs of the watermarked blocks.  Extracting the watermark from one block at least is enough to ensure the existence of the watermark. Experimental results show that the proposed method with different block sizes is superior to the traditional method of Liu for embedding unencrypted watermarks.

Keywords

Image Processing, Cryptography, Watermarking, Singular Value Decomposition.

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Samir Abd Elghafar ¹, Salaheldin M. Diab ², Bassiouny M. Sallam ³, S. El-Rabaie ⁴, Moawad I. Dessouky ⁵, Fathi E. Abd El-Samie ⁶

Affiliations
1 Jazan University, SA
2 Helwan University, Cairo, EG
3 Menoufia University, Menou, EG
4 Menoufia University, EG
5 Dept. Electronics and Electrical Communications, Menoufia University, EG
6 Menoufia University, Menouf, EG

Abstract

This paper presents a new implementation of Discrete Multi-Tone (DMT) systems based on the Discrete Wavelet Transform (DWT) and time-domain equalization to maximize the bit rate. The objective of the proposed DWT-DMT system is to make use of the sub-band decomposition property of the DWT to reduce the channel effects on the transmitted signals. The mathematical model of the Time-domain Equalizer (TEQ) utilized in this paper is presented. This equalizer is tested in the Fast Fourier Transform Discrete Multi-Tone (FFT-DMT) system, and in the proposed DWT-DMT system for comparison. Simulation experiments shows that the performance of the proposed DWT-DMT system with the TEQ filter bank is better than that of the FFT-DMT system with the TEQ filter bank over the eight standard Carrier Serving Area (CSA) loops. The results show that employing the TEQ filter bank in the proposed DWT-DMT system can achieve high bit rates ranging from 2.899 Mbps to 5.369 Mbps.

Keywords

DMT System, DWT, FFT, TEQ.

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