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Secure and Robust Optical Multi-Stage Medical Image Cryptosystem

Computers, Materials & Continua 2022年第1期70卷 895-913页

作者： w.lid el-shafai Moustafa H.Aly Abeer D.Algarni Fathi E.Abd el-Samie Naglaa F.Soliman Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and Communications Engineering College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Due to the rapid grow.h of telemedicine and healthcare services,color medical image security applications have been expanded *** this paper,an asymmetric PTFrFT(Phase Truncated Fractional Fourier Transform)-based color medical image cryptosystem is *** different phases in the fractional Fourier and output planes are provided as deciphering ***,the ciphering keys w.ll not be employed for the deciphering ***,the introduced PTFrFT algorithm comprises asymmetric ciphering and deciphering processes in contrast to the traditional optical symmetric OSH(Optical Scanning Holography)and DRPE(Double Random Phase Encoding)*** of the principal impacts of the introduced asymmetric cryptosystem is that it eliminates the onedimensionality aspects of the related symmetric cryptosystems due to its remarkable feature of phase nonlinear truncation *** comparisons on various colormedical images are examined and analyzed to substantiate the cryptosystem *** achieved experimental outcomes ensure that the introduced cryptosystem is robust and *** has terrific cryptography performance compared to conventional cryptography algorithms,even in the presence of noise and severe channel attacks.

关键词： Optical encryption medical image security symmetric and asymmetric encryption OSH DRPE PTFrFT

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Shadow.Extraction and elimination of Moving Vehicles for Tracking Vehicles

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Computers, Materials & Continua 2023年第11期77卷 2009-2030页

作者： Kalpesh Jadav Vishal Sorathiya w.lid el-shafai Torki Altameem Moustafa HAly Vipul Vekariya Kaw.ar Ahmed Francis MBui Department of electronics&Communication Engineering Faculty of Engineering and TechnologyParul Institute of Engineering and TechnologyParul UniversityVadodaraGujarat391760India Department electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Community CollegeKing Saud UniversityRiyadh11362Saudi Arabia electronics and Communications Engineering Department College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt Department of Computer Engineering Faculty of Engineering and TechnologyParul Institute of Engineering and TechnologyParul UniversityVadodaraGujarat391760India Department of electrical and Computer Engineering University of Saskatchewan57 Campus DriveSaskatoonSK S7N5A9Canada

Shadow.extraction and elimination is essential for intelligent transportation systems(ITS)in vehicle tracking *** shadow.is the source of error for vehicle detection,w.ich causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting,vehicle detection,vehicle tracking,and *** of the existing research is on shadow.extraction of moving vehicles in high intensity and on standard datasets,but the process of extracting shadow. from moving vehicles in low.light of real scenes is *** real scenes of vehicles dataset are generated by self on the Vadodara–Mumbai highw.y during periods of poor illumination for shadow.extraction of moving vehicles to address the above *** paper offers a robust shadow.extraction of moving vehicles and its elimination for vehicle *** method is distributed into tw. phases:In the first phase,w. extract foreground regions using a mixture of Gaussian model,and then in the second phase,w.th the help of the Gamma correction,intensity ratio,negative transformation,and a combination of Gaussian filters,w. locate and remove the shadow.region from the foreground *** to the outcomes proposed method w.th outcomes of an existing method,the suggested method achieves an average true negative rate of above 90%,a shadow.detection rate SDR(η%),and a shadow.discrimination rate SDR(ξ%)of 80%.Hence,the suggested method is more appropriate for moving shadow.detection in real scenes.

关键词： Change illuminations ImageJ softw.re intelligent traffic systems mixture of Gaussian model National Institute of Health vehicle tracking

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An Efficient CNN-Based Automated Diagnosis Framew.rk from COVID-19 CT Images

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

作者： w.lid 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 w.rld *** paper presents a segmentation and classification framew.rk of COVID-19 images based on deep ***,the classification process is employed to discriminate betw.en COVID-19,non-COVID,and pneumonia by Convolutional Neural Netw.rk(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT ***,the resulting segmented images are used to identify the infected region,w.ether 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 w.th 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 framew.rk 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 Immutable Framew.rk for Smart Healthcare Using Blockchain Technology

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Computer Systems Science & Engineering 2023年第7期46卷 165-179页

作者： Faneela Muazzam A.Khan Suliman A.Alsuhibany w.lid el-shafai Mujeeb Ur Rehman Jaw.d Ahmad Department of Computer Science Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia James w.tt School of Engineering University of GlasgowG128QQUK School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

The advancements in sensing technologies,information processing,and communication schemes have revolutionized the healthcare *** Healthcare Records(EHR)facilitate the patients,doctors,hospitals,and other stakeholders to maintain valuable data and medical *** traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks.A single attempt of a successful Denial of Service(DoS)attack can compromise the complete healthcare *** article introduces a secure and immutable blockchain-based framew.rk for the Internet of Medical Things(IoMT)to address the stated *** proposed architecture is on the idea of a lightw.ight private blockchain-based netw.rk that facilitates the users and hospitals to perform multiple healthcare-related operations in a secure and trustw.rthy *** efficacy of the proposed framew.rk is evaluated in the context of service execution time and *** experimental outcomes indicate that the proposed design attained low.r service execution time and higher throughput under different control parameters.

关键词： Blockchain technology healthcare applications cybersecurity services IoMT DoS EHR

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Improved RC6 Block Cipher Based on Data Dependent Rotations

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

作者： Osama S.Faragallah Ibrahim F.elashry Ahmed AlGhamdi w.lid 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 w.th 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 w.rd(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 w.rking 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 w.th few.r *** 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 Medical Image Deep Fusion Model Based on Convolutional Neural Netw.rks

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Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： w.lid el-shafai Noha A.el-Hag Ahmed Sedik Ghada elbanby Fathi E.Abd el-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt 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 UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image w.th rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Netw.rk(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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Proposed Privacy Preservation Technique for Color Medical Images

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Intelligent Automation & Soft Computing 2023年第4期36卷 719-732页

作者： w.lid el-shafai Hayam A.Abd el-Hameed Noha A.el-Hag Ashraf A.M.Khalaf Naglaa F.Soliman Hussah Nasser AlEisa Fathi E.Abd el-Samie Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt 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

Now.days,the security of images or information is very *** paper introduces a proposed hybrid w.termarking and encryption technique for increasing medical image ***,the secret medical image is encrypted using Advanced Encryption Standard(AES)***,the secret report of the patient is embedded into the encrypted secret medical image w.th the Least Signiﬁcant Bit(LSB)w.termarking *** that,the encrypted secret medical image w.th the secret report is concealed in a cover medical image,using Kekre’s Median Codebook Generation(KMCG)***,the stego-image obtained is split into 16 ***,it is sent to the *** adopt this strategy to send the secret medical image and report over a netw.rk *** proposed technique is assessed w.th different encryption quality metrics including Peak Signal-to-Noise Ratio(PSNR),Correlation Coefﬁcient(Cr),Fea-ture Similarity Index Metric(FSIM),and Structural Similarity Index Metric(SSIM).Histogram estimation is used to conﬁrm the matching betw.en the secret medical image before and after *** results demonstrate that the proposed technique achieves good performance w.th high quality of the received medical image and clear image details in a very short processing time.

关键词： LSB steganography AES algorithm KMCG algorithm

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Automatic PV Grid Fault Detection System w.th IoT and LabVIEw.as Data Logger

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Computers, Materials & Continua 2021年第11期69卷 1709-1723页

作者： Rohit Samkria Mohammed Abd-elnaby Rajesh Singh Anita Gehlot Mamoon Rashid Moustafa H.Aly w.lid el-shafai Project Engineer NWTFIndian Institute of TechnologyKanpurIndia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of electronics and electrical Engineering Lovely Professional UniversityJalandharIndia School of Computer Science and Engineering Lovely Professional UniversityJalandharIndia Department of electronics and Communications Engineering College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria 1029Egypt Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Fault detection of the photovoltaic(PV)grid is necessary to detect serious output pow.r reduction to avoid PV modules’*** identify the fault of the PV arrays,there is a necessity to implement an automatic *** this IoT and LabVIEw.based automatic fault detection of 3×3 solar array,a PV system is proposed to control and monitor Internet connectivity *** component to automatically reconfigure the solar PV array from the series-parallel(SP)to the complete cross-linked array underneath partial shading conditions(PSC)is centered on the Atmega328 system to achieve maximum *** the LabVIEw.environment,an automated monitoring system is *** automatic monitoring system assesses the voltage drop losses present in the DC side of the PV generator and generates a decimal w.ighted value depending on the defective solar panels and transmits this value to the remote station through an RF modem,and provides an indicator of the faulty solar panel over the built-in Interface *** managing of this GUI indicator helps the monitoring system to generate a panel alert for damaged panels in the PV *** MCU in the receiver section enables transmission of the fault status of PV arrays via Internet *** IoT-based Blynk app is employed for visualizing the fault status of the 3×3 PV *** dashboard of Blynk visualizes every array w.th the status.

关键词： Blynk app IoT LabVIEw node MCU PV array RF modem w.N

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Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

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Computers, Materials & Continua 2022年第8期72卷 3687-3703页

作者： Ahmed M.Ayoup Ashraf A.M.Khalaf w.lid el-shafai Fathi E.Abd el-Samie Fahad Alraddady Salw. M.Serag eldin electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt electronics and electrical Communications Engineering Department Faculty of Electronic EngineeringMenoufia University32952MenoufEgypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of electronics and electrical Communications Engineering Faculty of EngineeringTanta UniversityTantaEgypt

The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric *** paper presents a cancellable multi-biometric identification scheme that includes four stages:biometric data collection and processing,Arnold’s Cat Map encryption,decimation process to reduce the size,and finalmerging of the four biometrics in a single generated ***,a 2D matrix of size 128×128 is created based on Arnold’s Cat Map(ACM).The purpose of this rearrangement is to break the correlation betw.en pixels to hide the biometric patterns and merge these patterns together for more *** decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data ***,some sort of aliasing occurs due to decimation,contributing to the intended distortion of biometric *** hybrid structure that comprises encryption,decimation,andmerging generates encrypted and distorted cancellable *** simulation results obtained for performance evaluation show.that the system is safe,reliable,and feasible as it achieves high security in the presence of noise.

关键词： Aliasing technique selective encryption ACM decimation process

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Efficient Deep CNN Model for COVID-19 Classification

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Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： w.lid el-shafai Amira A.Mahmoud el-Sayed M.el-Rabaie Taha E.Taha Osama F.Zahran Adel S.el-Fishaw. Mohammed Abd-elnaby Fathi E.Abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection w.s initially acknow.edged as a global pandemic in w.han in *** Health Organization(w.O)stated that the COVID-19 is an epidemic that causes a 3.4%death *** X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis *** are numerous w.ys to identify positive COVID-19 *** of the fundamental w.ys is radiology imaging through CXR,or CT *** comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high ***,automated classification techniques are required to facilitate the diagnosis *** Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical *** deep Convolutional Neural Netw.rks(CNNs)can learn and extract essential features from different medical image *** this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is *** activation functions as w.0}l as three optimizers are tested and compared for this *** proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train *** performance is tested and investigated on the CT and CXR *** activation functions:Tanh,Sigmoid,and RelU are compared using a constant learning rate and different batch *** optimizers are studied w.th different batch sizes and a constant learning ***,a comparison betw.en different combinations of activation functions and optimizers is presented,and the optimal configuration is ***,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early *** proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset w.th training times of 58 min and 46 min on CXR an

关键词： COVID-19 image classification CNN DL activation functions optimizers

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