Neveen Ghali

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Papers by Neveen Ghali

A rough k-means fragile watermarking approach for image authentication

In the past few years, various fragile watermarking systems have been proposed for image authenti... more In the past few years, various fragile watermarking systems have been proposed for image authentication and tamper detection. In this paper, we propose a rough k-means (RKM) fragile watermarking approach with 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. By combining image local properties with human visual system, authentication data are acquired. By ...

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Signature Identification and Verification Systems: A Comparative Study on the Online and Offline Techniques

Future Computing and Informatics Journal, 2020

Handwritten signature identification and verification has become an active area of research in re... more Handwritten signature identification and verification has become an active area of research in recent years. Handwritten signature identification systems are used for identifying the user among all users enrolled in the system while handwritten signature verification systems are used for authenticating a user by comparing a specific signature with his signature that is stored in the system. This paper presents a review for commonly used methods for pre-processing, feature extraction and classification techniques in signature identification and verification systems, in addition to a comparison between the systems implemented in the literature for identification techniques and verification techniques in online and offline systems with taking into consideration the datasets used and results for each system

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Enhanced Predictive Modelling for 30-Day Readmission Diabetes Patients Based on Data Normalization Analysis

International Journal of Intelligent Engineering and Systems, 2021

In the field of health care, one of the most important problems is predicting the possibility of ... more In the field of health care, one of the most important problems is predicting the possibility of hospital readmission due to its important role in caring for patients with chronic diseases such as diabetes. Such predictions affect the health care costs and the hospital's efficiency and reputation. In this paper, an intelligent-based model is developed to predict the reintroduction of the patient into the hospital. This model is based on using some Machine Learning (ML) algorithms such as Logistic Regression (LR), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). Also, it proposes the use of a Deep Learning (DL) based network such as a convolutional neural network (CNN). Both ML and DL are used as classifiers to predict hospital readmission. The main problem is the input noisy data to these classifiers. These noisy data reduce the accuracy of the readmission prediction model. Sequential pre-processing steps are proposed to get over such a problem. These pre-processing steps provide solutions to missing values, feature engineering, and normalization problems. The main contribution of this work is improving readmission prediction rate by solving the data normalization problem. Two types of data normalization (e.g. z-score and min-max normalization) are applied, results show there is a difference in accuracy, z-score normalization is better than min-max normalization when comparing ML methods and DL models, CNN is the best with an accuracy of 0.894% in case of z-score normalization. Moreover, the model performance is improved with an accuracy of 0.924% when non-normalized data is used as input to the model. The proposed Non-normalization technique successes in providing superior results compared to some previous techniques which are displayed data by using Ensemble, Normalization, and Ensemble by age group techniques.

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Transfer Learning Based Model for Pneumonia Detection in Chest X-ray Images

Pneumonia is a lung infectious disease caused by viral bacteria. It damages one or both lungs in ... more Pneumonia is a lung infectious disease caused by viral bacteria. It damages one or both lungs in humans. Expert radiotherapists must evaluate chest X-ray to detect pneumonia. As a result, designing an automated system for detecting pneumonia would be valuable for quickly treating the disease, especially in remote areas. This paper introduces a convolutional neural network-based model for reliably detecting pneumonic lungs from chest X-rays. This model can be used by doctors to treat pneumonia in the real world. This study proposes a hybrid model of EfficientNetB0 as a transfer learning-based model and support vector machine (SVM) hinge loss. The functionality of the pre-trained EfficientNetB0 model is used as feature-extractors followed by SVM classifier for the classification of abnormal and normal chest X-Rays. The statistical findings show that using a pre-trained EfficientNetB0 model and supervised classifier algorithm to evaluate chest X-ray images, specifically to detect Pneumonia, can be very beneficial. The proposed model achieves higher classification accuracy, precision, recall, and AUC values outperforming other state of art models with an overall accuracy of 97%.

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Social Networks: Computational Aspects and Mining

ABSTRACT

Aboul Ella Hassanien: An adaptive Watermarking Approach for Medical Imaging Using Swarm Intelligent

In this paper we present a secure patient medical images and authentication scheme which enhances... more In this paper we present a secure patient medical images and authentication scheme which enhances the security, confidentiality and integrity of medical images transmitted through the Internet. This paper proposes a watermarking by invoking particle swarm optimization (PSO) technique in adaptive quantization index modulation and singular value decomposition in conjunction with discrete wavelet transform (DWT) and discrete cosine transform (DCT). The proposed approach promotes the robustness and watermarked image quality. The experimental results show that the proposed algorithm yields a watermark which is invisible to human eyes, robust against a wide variety of common attacks and reliable enough for tracing colluders.

Object-Based Image Retrieval System Using Rough Set Approach

Intelligent Systems Reference Library, 2012

In this chapter, we present an object-based image retrieval system using the rough set theory. Th... more In this chapter, we present an object-based image retrieval system using the rough set theory. The system incorporates two major modules: Preprocessing and Object-based image retrieval. In preprocessing, an imagebased object segmentation algorithm in the context of the rough set theory is used to segment the images into meaningful semantic regions. A new object similarity measure is proposed for the image retrieval. Performance is evaluated on an image database and the effectiveness of proposed image retrieval ...

Genetic Algorithms for Multi-Objective Community Detection in Complex Networks

Studies in Computational Intelligence, 2013

Abstract: Community detection in complex networks has attracted a lot of attention in recent year... more Abstract: Community detection in complex networks has attracted a lot of attention in recent years. Community detection can be viewed as an optimization problem, in which an objective function that captures the intuition of a community as a group of nodes with better internal connectivity than external connectivity is chosen to be optimized. Many single-objective optimization techniques have been used to solve the problem however those approaches have its drawbacks since they try optimizing one objective function and this ...

An Improved Hashing Function for Human Authentication System

International Journal of Computer Vision and Image Processing, 2013

Biometrics have the great advantage of recognition based on an intrinsic aspect of a human being ... more Biometrics have the great advantage of recognition based on an intrinsic aspect of a human being and thus requiring the person to be authenticated for physical presentation. Unfortunately, biometrics suffer from some inherent limitation such as high false rejection when the system works at a low false acceptation rate. In this paper, near set are implemented to improve the Standard Secure Hash Function SHA-1 (ISHA-1) for strict multi-modal biometric image authentication system. The proposed system is composed of five phases, starting from feature extraction and selection phase, hashing computing that uses the ISHA-1 phase, embedding watermark phase, extraction and decryption watermark phase, and finally the authentication phase. Experimental results showed that the proposed algorithm guarantees the security assurance and reduces the time of implementation.

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Strict Authentication of Multimodal Biometric Images Using Near Sets

Advances in Intelligent and Soft Computing, 2011

In this paper, a strict authentication watermarking scheme based on multi-modal biometric images ... more In this paper, a strict authentication watermarking scheme based on multi-modal biometric images and near sets was designed and introduced. The proposed scheme has a number of stages including feature enrolment for extracting the human facial features. Three human facial features which are nose length, nose width and distance between eyes balls are extracted. The near sets approach is adapted to choose the best feature among the considered features. The watermark is generated from hashing the extracted facial ...

Virtual Reality Technology for Blind and Visual Impaired People: Reviews and Recent Advances

Intelligent Systems Reference Library, 2012

Virtual reality technology enables people to become immersed in a computer-simulated and three-di... more Virtual reality technology enables people to become immersed in a computer-simulated and three-dimensional environment. In this chapter, we investigate the effects of the virtual reality technology on disabled people such as blind and visually impaired people (VIP) in order to enhance their computer skills and prepare them to make use of recent technology in their daily life. As well as, they need to advance their information technology skills beyond the basic computer training and skills. This chapter describes what best tools and practices in information technology to support disabled people such as deaf-blind and visual impaired people in their activities such as mobility systems, computer games, accessibility of e-learning, web-based information system, and wearable finger-braille interface for navigation of deaf-blind. Moreover, we will show how physical disabled people can benefits from the innovative virtual reality techniques and discuss some representative examples to illustrate how virtual reality technology can be utilized to address the information technology problem of blind and visual impaired people. Challenges to be addressed and an extensive bibliography are included.

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A Symmetric Bio-Hash Function Based on Fingerprint Minutiae and Principal Curves Approach

ABSTRACT In this paper, a fingerprint-based biometric is used and protected by a computationally ... more ABSTRACT In this paper, a fingerprint-based biometric is used and protected by a computationally efficient symmetric bio hash function and generate a digest. The extracted minutiae points from a fingerprint are represented by a fixed length code vector, called bio-minutiae fingerprint code and does not assume a pre-alignment between the test and the stored fingerprint templates. The principal curves algorithm were used to extract the minutiae points from the fingerprint, then using the systematic bio hash function to compute the ...

Known-plaintext attack of DES-16 using particle swarm optimization

Proceedings of the 2011 3rd World Congress on Nature and Biologically Inspired Computing, NaBIC 2011, 2011

Discovering the root key bits in the cryptanalysis of 16-rounded Data Encryption Standard (DES-16... more Discovering the root key bits in the cryptanalysis of 16-rounded Data Encryption Standard (DES-160 is considered to be a hard problem. In this paper we present an approach for cryptanalysis of DES-16 based on Particle Swarm Optimization (PSO) using Known-plaintext attack and some equations that deduced from the relationship between sub-key differences and root key information. In Knownplaintext attack the cryptanalyst possesses one or more plaintext/cipher text pairs formed with the secret key and attempts to deduce the root key that used to produce this cipher text. In our approach, PSO is used as optimization technique to collect the optimal effective plaintexts from a plaintext search space according to the proposed fitness function then the set of collected plaintexts and the corresponding cipher texts used to extract the best eight subkey differences from which most bits of the root key are discovered.

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E-contract securing system using digital signature approach

Communications in Computer and Information Science, 2011

This paper presents an e-contract securing system, using the digital signature approach, for vari... more This paper presents an e-contract securing system, using the digital signature approach, for various e-commerce applications. The proposed system is composed of three phases, namely, e-contract hashing and digital signing phases that are applied at sender's side, with addition to digital signature verification phase that is applied at the corresponding receiver's side. The implementation of the proposed system shows accurate and effective results in terms of signing and verification.

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A fast and secure one-way hash function

Communications in Computer and Information Science, 2011

Abstract. One way hash functions play a fundamental role for data integrity, message authenticati... more Abstract. One way hash functions play a fundamental role for data integrity, message authentication, and digital signature in modern information security. In this paper we proposed a fast one-way hash function to optimize the time delay with strong collision resistance, assures a good compression and one-way resistance. It is based on the standard secure hash function (SHA-1) algorithm. The analysis indicates that the proposed algorithm which we called (fSHA-1) is collision resistant and assures a good compression ...

Social Networks Analysis: Tools, Measures and Visualization

Computational Social Networks, 2012

Social Network Analysis (SNA) is becoming an important tool for investigators, but all the necess... more Social Network Analysis (SNA) is becoming an important tool for investigators, but all the necessary information is often available in a distributed environment. Currently there is no information system that helps managers and team leaders monitor the status of a social network. This chapter presents an overview of the basic concepts of social networks in data analysis including social network analysis metrics and performances. Different problems in social networks are discussed such as uncertainty, missing data and finding the shortest path in a social network. Community structure, detection and visualization in social network analysis is also illustrated. This chapter bridges the gap among the users by combining social network analysis methods and information visualization technology to help a user visually identify the occurrence of a possible relationship amongst the members in a social network. The chapter illustrates an online visualization method for a DBLP

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An associative watermarking based image authentication scheme

2010 10th International Conference on Intelligent Systems Design and Applications, 2010

In this paper, we propose an associative watermarking scheme which is conducted by the concept of... more In this paper, we propose an associative watermarking scheme which is conducted by the concept of Association Mining Rules (AMRs) and the ideas of Vector Quantization (VQ) and Soble operator. Performing associative watermarking rules to the images will reduct the amount of the embedded data, and using VQ indexing scheme can easily recall the embedded watermark for the purpose of image authentication, and establishing the relation between the association rules on both the original image and the watermark image. The Vector Quantization decoding technique is applied to reconstruct the watermarked image from the watermarked index table. The experimental result shows that the proposed scheme is robust. When the watermarked images suffered from various kinds of image-processing procedures, such as Gaussian noise, brightness, blurring, sharpening, cropping, and JPEG lossy compression can be detected without the original images assistance.

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Adaptive k-means clustering algorithm for MR breast image segmentation

Neural Computing and Applications, 2013

Image segmentation is vital for meaningful analysis and interpretation of the medical images. The... more Image segmentation is vital for meaningful analysis and interpretation of the medical images. The most popular method for clustering is k-means clustering. This article presents a new approach intended to provide more reliable magnetic resonance (MR) breast image segmentation that is based on adaptation to identify target objects through an optimization methodology that maintains the optimum result during iterations. The

An improvement of chaos-based hash function in cryptanalysis approach: An experience with chaotic neural networks and semi-collision attack

Memetic Computing, 2013

In this paper, the chaos-based hash function is analyzed, then an improved version of chaos-based... more In this paper, the chaos-based hash function is analyzed, then an improved version of chaos-based hash function is presented and discussed using chaotic neural networks. It is based on the piecewise linear chaotic map that is used as a transfer function in the input and output of the neural network layer. The security of the improved hash function is also discussed and a novel type of collision resistant hash function called semi-collision attack is proposed, which is based on the collision percentage between the two hash values. In the proposed attack particle swarm optimization algorithm is used to define the fitness function parameters. Finally, numerical and simulation results provides strong collision resistance and high performance efficiency.

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Intelligent Machine Learning in Image Authentication

Journal of Signal Processing Systems, 2013

Image authentication techniques have recently gained great attention due to its importance for a ... more Image authentication techniques have recently gained great attention due to its importance for a large number of multimedia applications. Digital images are increasingly transmitted over non-secure channels such as the Internet. Therefore, military, medical and quality control images must be protected against attempts to manipulate them; such manipulations could tamper the decisions based on these images. To protect the authenticity of multimedia images, there are several approaches including conventional cryptography, fragile and semi-fragile watermarking and digital signatures that are based on the image content. The aim of this paper is to present a review on different Machine learning techniques as

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