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Proposed Biometric Security system Based on Deep Learning and Chaos Algorithms

computers, Materials & Continua 2023年第2期74卷 3515-3537页

作者： Iman Almomani Walid El-Shafai Aala AlKhayer Albandari Alsumayt Sumayh S.Aljameel Khalid Alissa Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Computer Science Department King Abdullah II School of Information TechnologyThe University of Jordan11942Jordan Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Applied CollegeImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Computer Science Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia SAUDI ARAMCO Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

Nowadays,there is tremendous growth in biometric authentication and cybersecurity ***,the efficient way of storing and securing personal biometric patterns is mandatory in most governmental and private ***,designing and implementing robust security algorithms for users’biometrics is still a hot research area to be *** work presents a powerful biometric security system(BSS)to protect different biometric modalities such as faces,iris,and *** proposed BSSmodel is based on hybridizing auto-encoder(AE)network and a chaos-based ciphering algorithm to cipher the details of the stored biometric patterns and ensures their *** employed AE network is unsupervised deep learning(DL)structure used in the proposed BSS model to extract main biometric *** obtained features are utilized to generate two random chaos *** first random chaos matrix is used to permute the pixels of biometric *** contrast,the second random matrix is used to further cipher and confuse the resulting permuted biometric pixels using a two-dimensional(2D)chaotic logisticmap(CLM)*** assess the efficiency of the proposed BSS,(1)different standardized color and grayscale images of the examined fingerprint,faces,and iris biometrics were used(2)comprehensive security and recognition evaluation metrics were *** assessment results have proven the authentication and robustness superiority of the proposed BSSmodel compared to other existing *** example,the proposed BSS succeeds in getting a high area under the receiver operating characteristic(AROC)value that reached 99.97%and low rates of 0.00137,0.00148,and 3516 CMC,2023,vol.74,no.20.00157 for equal error rate(EER),false reject rate(FRR),and a false accept rate(FAR),respectively.

关键词： Biometric security deep learning AE network 2D CLM cybersecurity and authentication applications feature extraction unsupervised learning

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Efficient UAV Routing Strategies for Wireless Sensor Network Data Retrieval

Efficient UAV Routing Strategies for Wireless Sensor Network...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Al-Sharhanee, Kareem Ali Malalah Najim, Ali Hamza Alheeti, Khattab M. Ali Satar, Nurhizam Safie Mohd Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University Baghdad10011 Iraq Department of Computer Technical Al-Diwaniyah Iraq College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

WSNs are applied in many disciplines where certain conditions require the ability to adapt to network sink mobility and changes in the dynamics of the area coverage. To meet these needs, it is necessary to develop integrated systems where the ''terrestrial' systems and the Unmanned Aerial Vehicles (UAVs)' collect data from sensors efficiently. Planning of UAV trajectories is another challenging issue if many WSN nodes are randomly deployed. This challenge has a big impact on the overall effectiveness of the system. This paper presents a novel approach for reducing the traveled distance of unscrewed aerial vehicles (UAVs) to improve the data collection efficiency in WSNs with poor node density. Yet the method that has been developed is aimed at increasing 'the efficiency and efficacy of data collection... with the assistance of Unmanned Aerial Vehicles (UAVs)' which means this work reveals practical application solutions. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Performance Improvement Technique of RSA Algorithm in Document Data Security 12

Performance Improvement Technique of RSA Algorithm in Docume...

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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Wandira, Agtori Nasution, Benny Benyamin Zarlis, M. Universitas Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia Politeknik Negeri Medan Departement of Computer Engineering Medan Indonesia

ISBN: (纸本)9798331528799

One of the first public key schemes was developed in 1977 by Ron Rivest, Adi Shamir, and Len Adleman at MIT and first published in 1978. Since then, the RSA scheme has become the most widely accepted and applied public-key encryption approach. RSA is a block cipher where the plaintext and ciphertext are integers between 0 and n - 1 for some $n$. However, since the calculations involved (both in key generation and in encryption/decryption) are complex, the larger the key size, the slower the system will run. To overcome the performance constraints of the RSA algorithm, various techniques such as iteration, Divide and Conquer, and Square and Multiply have been developed. Tests were conducted on files with various key lengths to evaluate encryption and decryption performance. The results show that all three algorithms experience an increase in computation time as the key length increases. The iteration algorithm shows the best performance for short keys, while the square and multiply algorithm provides the highest efficiency for medium to long keys. Further testing recommends using square and multiply for keys of 128 bits and above due to its superior efficiency. It can be concluded that the selection of appropriate support algorithms can overcome RSA's performance issues without compromising security, as well as provide suggestions for further security analysis and development of more efficient algorithms. © 2024 IEEE.

关键词： Ciphertext

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ConvNeXt network with transfer learning for cumulative foot pressure images recognition

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International Journal of information technology (Singapore) 2024年 1-14页

作者： Iskandar, Ayman Alfonse, Marco Roushdy, Mohamed El-Horbaty, El-Sayed M. Computer Science Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Laboratoire Interdisciplinaire de L’Université Française d’Égypte (UFEID LAB) Université Française d’Égypte Cairo Egypt Computer Science Department Faculty of Computers and Information Technology Future University in Egypt Cairo Egypt

Humans can be differentiated by their walking style using cumulative foot pressure images, which are 2-D cumulative ground reaction forces during each gait cycle. In this paper, we propose a new model for cumulative foot pressure images in which we apply transfer learning to our ConvNeXt model after adjusting it based on our usage to acquire discriminative features that can identify humans using only cumulative foot pressure images. Our experiment was conducted on CASIA Dataset D using only cumulative foot pressure images of eighty-eight persons while neglecting the gait pose images captured by the camera. The evaluation indicates that our proposed method is effective, where we achieved an accuracy of 99.894%, a false acceptance rate of 0.002%, and a false rejection rate of 0.039%, which shows a significant improvement over the previous work, concluding that the cumulative foot pressure images have the potential to be used as a biometric identifier. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Biometrics ConvNeXt network Cumulative foot pressure images Gait recognition Transfer learning

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Ensuring purity, precision and consumption in every drop of water with IoT technology 4

Ensuring purity, precision and consumption in every drop of ...

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4th International Conference on Power, Energy, Control and Transmission systems, ICPECTS 2024

作者： Gomathi, S. Devi, D. Srinidhi, A. Shanthini, P. Sri Sairam Engineering College Department of Information Technology Chennai India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508845

In a world where access to clean and pure water is paramount, ensuring its quality and fair distribution is of utmost importance. Traditional water purification methods often fall short in providing real-time insights into water purity, leading to potential health risks. Moreover, the equitable distribution of water resources in shared residential spaces remains a challenge, often resulting in unfair billing practices. To address these issues, we present an innovative solution leveraging IoT technology. Our system comprises sensors measuring critical parameters such as pH, turbidity, ultrasonic, and dissolved oxygen, which are connected to an Arduino Mega board. This setup continuously monitors the quality of water stored in reservoirs managed by water cooperatives. Upon detecting any deviation from predefined purity standards, the system triggers alerts via SMS using a SIM 900 A module, ensuring prompt action by relevant authorities to maintain water quality. Furthermore, we propose the installation of individual water meters in each household within residential complexes. These meters accurately track daily water consumption, empowering residents to pay only for the water they use, eliminating unfair billing practices. Additionally, this initiative aims to raise awareness about water conservation by enabling users to visualize their consumption patterns and encouraging responsible usage. By implementing cost estimation algorithms based on water consumption data, our system facilitates transparent billing processes while enabling authorities to predict future water demands more accurately. Ultimately, this project not only ensures the purity and precision of every drop of water but also promotes equitable distribution and conservation of this precious resource, fostering a sustainable future for all. © 2024 IEEE.

关键词： Health risks

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Providing an Intelligent Hybrid Routing Method in Wireless Sensor Networks 23th

Providing an Intelligent Hybrid Routing Method in Wireless S...

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23rd International Conference on Intelligent systems Design and Applications, ISDA 2023

作者： Hosseinabadi, Ali Asghar Rahmani Mirkamali, Seyedsaeid Hajiabadi, Mahdi Rohani Abraham, Ajith Department of Computer Science University of Regina Regina Canada Department of Computer Engineering and IT Payame Noor University Tehran Iran Faculty of Computer and Information Technology Engineering Islamic Azad University Qazvin Qazvin Iran School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India

ISBN: (纸本)9783031647758

Optimal energy consumption in Wireless Sensor Networks (WSNs) is important. Previous research has shown that by organizing network nodes into a number of clusters, one can achieve greater energy efficiency leading to longer network life. The WSN is made up of a very large number of sensor nodes that communicate with each other to perform specific tasks. These nodes have limited energy, processing power, and memory. Because the lifetime of the network depends on the brightness of the nodes, the energy consumption of each node is very important. Therefore, we need to find solutions to reduce the energy consumption of the nodes. One way to reduce energy consumption is clustering, many algorithms have been introduced in this field. In this paper, we optimize Particle Swarm Optimization (PSO) algorithm based on fuzzy logic and PSO algorithm. The fitting criterion will be based on the minimum energy consumed by the nodes of the network during each operation period, It leads to a balance in the energy consumption of the headers and, as a consequence, a lengthening of the life of the network. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Fuzzy logic

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Towards Blockchain-based Decentralized Employee Transfer system 6

Towards Blockchain-based Decentralized Employee Transfer Sys...

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6th International Conference on Blockchain Computing and Applications, BCCA 2024

作者： Zaib, Alam Mustafa, Ehzaz Khan, Ahsan Khattak, Hasan Ali Ibrahim, Isa Ali Namoun, Abdallah Shuja, Junaid Ahmad, Raja Wasim Department of Computer Science Comsats University Islamabad Abbottabad Campus Pakistan Faculty of Computing & Information Technology Sohar University Sohar Oman School of Information and Communication Technology Federal University of Technology Imo Owerri1526 Nigeria AI Centre Faculty of Computer and Information Systems Islamic University of Madinah Madinah42351 Saudi Arabia Department of Computer Science Southeast Missouri State University Cape GirardeauMO United States Department of Computer & Information Sciences Ajman University Ajman United Arab Emirates

ISBN: (纸本)9798350351538

Employees are the main driving force in organizations that undergo recruitment, promotion, and transfer. There are many employee management systems, but most of them are centralized. Centralization leads to problems such as lack of transparency, auditability issues, vulnerability, and a single point of failure. Blockchain technology addresses these concerns. Despite some blockchain-based HRM and employee management systems, none of the existing blockchain-based systems have addressed the problems of employee transfers. We propose a secure and transparent blockchain-based employee transfer (E-transfer) system to address this. The proposed system uses smart contracts for transfer management, recording outcomes on an unchangeable ledger. We conducted tests on Hyperledger Fabric for our proposed system. Our study aims to introduce an automated, auditable, and efficient transfer process. The findings of the study validate the effectiveness of the blockchain-based E-transfer system. © 2024 IEEE.

关键词： Smart contract

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Deep Learning Techniques for Advanced Large-Scale Data Processing 15

Deep Learning Techniques for Advanced Large-Scale Data Proce...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sunil, M.P. Shekhawat, Jyoti Vanaja, T. Mohammed, Vazeer Ali Thaware, Shailesh J. Singh, Vaishali Karnataka Bangalore India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer & Information System Lewis University Illinois United States Department of Computer Engineering Vishwakarma Institute of Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350370249

Deep getting to know techniques have become increasingly more popular due to their potential to improve huge-scale records processing performance. Leveraging specialized hardware which includes GPUs, deep getting to know algorithms can attain mind-blowing pace will increase compared to traditional algorithms. further, deep gaining knowledge of fashions can discover complicated non-linear relationships in big datasets, permitting greater accurate overall performance and less fake predictions. Latest advances in deep mastering have enabled it to be implemented to remedy a plethora of information processing duties, from photo recognition to natural language processing. CNNs, RNNs, and GANs are a number of the maximum famous deep gaining knowledge of fashions used in tackling complex data processing obligations. agencies consisting of Google, fb, and Amazon use these sophisticated frameworks to build predictive models that help improve numerous programs. Deep getting to know strategies offer exquisite ability to take massive-scale information processing to the following stage. corporations are increasingly more becoming privy to the emerging opportunities, and actively investing in deep mastering to liberate the untapped strength of their information. ©2024 IEEE.

关键词： Large datasets

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in Engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Assessing Student Visual Fatigue in Virtual Semiconductor Labs via Head-Mounted Displays: A computer Vision Syndrome Questionnaire (CVS-Q) 3

Assessing Student Visual Fatigue in Virtual Semiconductor La...

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3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2023

作者： Alnagrat, Ahmed Jamah Ahmed Ismail, Rizalafande Che Akeel, Abubaker Almintisir Abubaker Salem, Asma Almkhtar Miftah Alhaj Khalefah, Salah Eldeen Ali Saad Idrus, Syed Zulkarnain Syed Department of Communication Department of Computer Science and Information Technology Perlis Kangar01000 Malaysia Wadi al-Shati Fezzan Libya Arau02600 Malaysia Wadi Alshatti University Faculty of Education Department of Mathematics and Computer Fezzan Libya Higher Institute of Sciences and Technology Department of Computer Science and Information Technology Tripoli Libya Higher Institute of Science and Technology Department of Computer Science and Information Technology Fezzan Libya Department of Communication Perlis Kangar01000 Malaysia

ISBN: (纸本)9798350319897

This paper evaluates visual fatigue among students in a virtual semiconductor lab using HMDs - the HP Reverb G2 and Oculus Quest 2 - and the CVS-Q questionnaire. The study measures the frequency of visual fatigue symptoms (never, occasionally, or always) and aims to determine the effects of HMD usage on visual fatigue and eye strain, providing insight into the benefits and drawbacks of using HMDs in virtual labs. The study was conducted during the COVID-19 pandemic and aims to determine the effects of HMD usage on visual fatigue and eye strain among students in a virtual semiconductor laboratory learning environment. The results of this evaluation will provide insight into the potential benefits and drawbacks of HMD usage in virtual laboratory environments and inform the development of strategies to mitigate visual fatigue. © 2023 IEEE.

关键词： COVID-19

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