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Improved RC6 Block Cipher Based on Data Dependent Rotations

Computers, Materials & Continua 2022年第1期70卷 1921-1934页

作者： Osama S.Faragallah Ibrahim F.elashry Ahmed AlGhamdi Walid el-Shafai S.el-Rabaie fathi e.abd el-samie Hala S.el-sayed Mohamed A.elaskily Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of electrical Communications Faculty of EngineeringKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electrical engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Informatics Electronic Research Institute(ERI)CairoEgypt

This paper introduces an Improved RC6(IRC6)cipher for data encryption based on data-dependent *** proposed scheme is designed with the potential of meeting the needs of the Advanced encryption Standard(AeS).Four parameters are used to characterize the proposed *** parameters are the size of the word(w)in bits,the number of rounds(r),the length of the secret key(b)in bytes,and the size of the block(L)in *** main feature of IRC6 is the variable number of working registers instead of just four registers as in RC6,resulting in a variable block size for plaintext and *** IRC6 cipher is designed to improve the robustness against attacks by increasing the diffusion for each round and providing greater security with fewer *** effectiveness of the proposed IRC6 scheme is verified against theoretical *** proposed IRC6 scheme depends on full diffusion and confusion mechanisms regardless of the utilized block *** proposed IRC6 scheme saves 70%of the encryption time and 64%of the decryption time of *** simulation results prove that the IRC6 achieves a better encryption/decryption time compared to the ***,the proposed IRC6 is anticipated to fulfill the market needs and system security requirements.

关键词： Cryptography block cipher RC6,IRC6,AeS

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An efficient CNN-Based Automated Diagnosis Framework from COVID-19 CT Images

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Computers, Materials & Continua 2021年第10期69卷 1323-1341页

作者： Walid el-Shafai Noha A.el-Hag Ghada M.el-Banby Ashraf A.M.Khalaf Naglaa F.Soliman Abeer D.Algarni fathi e.abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of EngineeringMinia UniversityEgypt Department of Industrial electronics and Control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the *** has dramatically affected daily lives,public health,and the world *** paper presents a segmentation and classification framework of COVID-19 images based on deep ***,the classification process is employed to discriminate between COVID-19,non-COVID,and pneumonia by Convolutional Neural Network(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT ***,the resulting segmented images are used to identify the infected region,whether COVID-19 or *** proposed CNN consists of four Convolutional(Conv)layers,four batch normalization layers,and four Rectified Linear Units(RelUs).The sizes of Conv layer used filters are 8,16,32,and *** maxpooling layers are employed with a stride of 2 and a 2×2 *** classification layer comprises a Fully-Connected(FC)layer and a soft-max activation function used to take the classification decision.A novel saliencybased region detection algorithm and an active contour segmentation strategy are applied to segment COVID-19 and pneumonia CT *** acquired findings substantiate the efficacy of the proposed framework for helping the specialists in automated diagnosis applications.

关键词： Classification segmentation COVID-19 CNN deep learning diagnosis applications

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An Improved Convolutional Neural Network Model for DNA Classification

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Computers, Materials & Continua 2022年第3期70卷 5907-5927页

作者： Naglaa.F.Soliman Samia M.abd-Alhalem Walid el-Shafai Salah eldin S.e.abdulrahman N.Ismaiel el-Sayed M.el-Rabaie Abeer D.Algarni fathi e.abd el-samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Computer Science and engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt

Recently,deep learning(DL)became one of the essential tools in bioinformatics.A modified convolutional neural network(CNN)is employed in this paper for building an integratedmodel for deoxyribonucleic acid(DNA)*** any CNN model,convolutional layers are used to extract features followed by max-pooling layers to reduce the dimensionality of features.A novel method based on downsampling and CNNs is introduced for feature *** downsampling is an improved form of the existing pooling layer to obtain better classification *** two-dimensional discrete transform(2D DT)and two-dimensional random projection(2D RP)methods are applied for *** convert the high-dimensional data to low-dimensional data and transform the data to the most significant feature ***,there are parameters which directly affect how a CNN model is *** this paper,some issues concerned with the training of CNNs have been *** CNNs are examined by changing some hyperparameters such as the learning rate,size of minibatch,and the number of *** and assessment of the performance of CNNs are carried out on 16S rRNA bacterial *** results indicate that the utilization of a CNN based on wavelet subsampling yields the best trade-off between processing time and accuracy with a learning rate equal to 0.0001,a size of minibatch equal to 64,and a number of epochs equal to 20.

关键词： DNA classification CNN downsampling hyperparameters DL 2D DT 2D RP

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embedded Coded Relay System for Molecular Communications

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Computers, Materials & Continua 2022年第8期72卷 2729-2748页

作者： eman S.Attia Ashraf A.M.Khalaf fathi e.abd el-samie Saied M.abd el-atty Konstantinos A.Lizos Osama Alfarraj Farid Shawki Imran Khan Ki-Il Kim Department of electrical engineering Faculty of EngineeringMinia UniversityMiniaEgypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)Norway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of electrical engineering University of Engineering&TechnologyPeshawar814Pakistan Department of Computer Science and engineering Chungnam National UniversityDaejeon34134Korea

With the emergence of the COVID-19 pandemic,the World Health Organization(WHO)has urged scientists and industrialists to exploremodern information and communication technology(ICT)as a means to reduce or even eliminate *** World Health Organization recently reported that the virus may infect the organism through any organ in the living body,such as the respiratory,the immunity,the nervous,the digestive,or the cardiovascular *** the abovementioned goal,we envision an implanted nanosystem embedded in the intra living-body *** main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system(i.e.,delivery of the therapeutic drug to the diseased tissue or targeted cell).The communication among the nanomachines is accomplished via communication-based molecular *** control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things(IoBNT).The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward(DF)principle to ensure reliable drug delivery to the targeted ***,both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into *** this paper,a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate(BeR)performance and high signal-to-noise ratio(SNR),while the detection process is based on maximum likelihood(ML)probability and minimum error probability(MeP).The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position,number of released molecules,relay and receiver *** results are validated through simulation and demonstrate that the proposed scheme can

关键词： Molecular communication nanonetwork internet of bio-nano things coded relay scheme coding

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Securing Healthcare Data in IoMT Network Using enhanced Chaos Based Substitution and Diffusion

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Computer Systems Science & engineering 2023年第11期47卷 2361-2380页

作者： Musheer Ahmad Reem Ibrahim Alkanhel Naglaa FSoliman Abeer D.Algarni fathi e.abd el-samie Walid el-Shafai Department of Computer engineering Jamia Millia IslamiaNew Delhi110025India Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia

Patient privacy and data protection have been crucial concerns in ehealthcare systems for many *** modern-day applications,patient data usually holds clinical imagery,records,and other medical ***,the Internet of Medical Things(IoMT),equipped with cloud computing,has come out to be a beneficial paradigm in the healthcare ***,the openness of networks and systems leads to security threats and illegal ***,reliable,fast,and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT *** paper presents an image protection scheme for healthcare applications to protect patients’medical image data exchanged in IoMT *** proposed security scheme depends on an enhanced 2D discrete chaotic map and allows dynamic substitution based on an optimized highly-nonlinear S-box and diffusion to gain an excellent security *** optimized S-box has an excellent nonlinearity score of *** new image protection scheme is efficient enough to exhibit correlation values less than 0.0022,entropy values higher than 7.999,and NPCR values around 99.6%.To reveal the efficacy of the scheme,several comparison studies are *** comparison studies reveal that the novel protection scheme is robust,efficient,and capable of securing healthcare imagery in IoMT systems.

关键词： Secure communication healthcare data encryption Internet of Medical Things(IoMT) discrete chaotic map substitution box(S-box)

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Stock Market Trading Based on Market Sentiments and Reinforcement Learning

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Computers, Materials & Continua 2022年第1期70卷 935-950页

作者： K.M.Ameen Suhail Syam Sankar Ashok S.Kumar Tsafack Nestor Naglaa F.Soliman Abeer D.Algarni Walid el-Shafai fathi e.abd el-samie Department of Computer Science&engineering NSS College of EngineeringPalakkad678008KeralaIndia Department of electronics and Communication engineering NSS College of EngineeringPalakkad678008KeralaIndia Unitéde Recherche de Matière Condensée D’Electronique et de Traitement du Signal(URAMACETS)Department of PhysicsUniversity of DschangP.O.Box 67DschangCameroon Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Stock market is a place,where shares of different companies are *** is a collection of buyers’and sellers’*** this digital era,analysis and prediction in the stock market have gained an essential role in shaping today’s *** market analysis can be either fundamental or *** analysis can be performed either with technical indicators or through machine learning *** this paper,we report a system that uses a Reinforcement Learning(RL)network and market sentiments to make decisions about stock market *** system uses sentiment analysis on daily market news to spot trends in stock *** sentiment analysis module generates a unified score as a measure of the daily news about *** score is then fed into the RL module as one of its *** RL section gives decisions in the form of three actions:buy,sell,or *** objective is to maximize long-term future *** have used stock data of Apple from 2006 to 2016 to interpret how sentiments affect *** stock price of any company rises,when significant positive news become available in the public *** results reveal the influence of market sentiments on forecasting of stock prices.

关键词： Deep learning machine learning daily market news reinforcement learning stock market

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Hybrid of Distributed Cumulative Histograms and Classification Model for Attack Detection

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Computer Systems Science & engineering 2023年第5期45卷 2235-2247页

作者： Mostafa Nassar Anas M.Ali Walid el-Shafai Adel Saleeb fathi e.abd el-samie Naglaa F.Soliman Hussah Nasser Aleisa Hossam eldin H.Ahmed Department of electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of engineering&Technology(AIeT) AlexandriaEgypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Traditional security systems are exposed to many various attacks,which represents a major challenge for the spread of the Internet in the *** techniques have been suggested for detecting attacks using machine learning and deep *** significant advantage of deep learning is that it is highly efficient,but it needs a large training time with a lot of ***,in this paper,we present a new feature reduction strategy based on Distributed Cumulative Histograms(DCH)to distinguish between dataset features to locate the most effective *** histograms assess the dataset instance patterns of the applied features to identify the most effective attributes that can significantly impact the classification *** different models for detecting attacks using Convolutional Neural Network(CNN)and Long Short-Term Memory Network(LSTM)are also *** accuracy test of attack detection using the hybrid model was 98.96%on the UNSW-NP15 *** proposed model is compared with wrapper-based and filter-based Feature Selection(FS)*** proposed model reduced classification time and increased detection accuracy.

关键词： Feature selection DCH LSTM CNN security systems

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efficient Segmentation Approach for Different Medical Image Modalities

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Computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid el-Shafai Amira A.Mahmoud el-Sayed M.el-Rabaie Taha e.Taha Osama F.Zahran Adel S.el-Fishawy Naglaa F.Soliman Amel A.Alhussan fathi e.abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron emission Tomography(PeT),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PeT,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PeT MRI morphological operations FCM active contours

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Optimization of Cooperative RelayingMolecular Communications for Nanomedical Applications

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Computer Modeling in engineering & Sciences 2024年第2期138卷 1259-1275页

作者： eman S.Attia Ashraf A.M.Khalaf fathi e.abd el-samie Saied M.abd el-atty Konstantinos A.Lizos Osama Alfarraj Heba M.el-Hoseny Department of electrical engineering Faculty of EngineeringMinia UniversityMinia61111Egypt Department of electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)OsloNorway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer science The Higher Future Institute for Specialized Technological StudiesEl ShoroukEgypt

Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)***,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is *** this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift *** fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)*** the previous work,the probability of bit error is expressed in a closed-form *** is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano *** simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.

关键词： Nanomedical system molecular communication cooperative relay optimization

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Hybrid Segmentation Approach for Different Medical Image Modalities

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Computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid el-Shafai Amira A.Mahmoud el-Sayed M.el-Rabaie Taha e.Taha Osama F.Zahran Adel S.el-Fishawy Naglaa F.Soliman Amel A.Alhussan fathi e.abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PeT images MR images fuzzy c-mean morphological operations active contour

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