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2023 IEEE Asia-Pacific Conference on computer science and Data engineering, CSDE 2023

作者： Zhu, Haoyun Suzuki, Takuya Yamana, Hayato Waseda University Department of Computer Science Tokyo Japan Waseda University Department of Computer Science and Communications Engineering Tokyo Japan Waseda University Faculty of Science and Engineering Tokyo Japan

ISBN: (纸本)9798350341072

Homomorphic encryption (HE) offers a promising solution for maintaining data privacy even during calculation, as it allows for the evaluation of ciphertexts. Several HE libraries have been released, but selecting the best-suited library for HE beginners can be challenging. This paper provides insights into the selection process by comparing three popular HE libraries: HElib, Microsoft SEAL, and OpenFHE. To evaluate the performance of these libraries, we implemented a convolutional neural network inference using each of the three libraries and analyzed its latency. Our experimental results show that Microsoft SEAL achieves the shortest latency, less than 56% of OpenFHE and less than 17% of HElib. In terms of ease of use, OpenFHE surpasses the other libraries because it eliminates the need for programmers to consider rescaling during calculations and has more choices on different key-switching algorithms. In contrast, utilizing automatic rescaling with OpenFHE results in 5x longer latency than manual rescaling. © 2023 IEEE.

关键词： Libraries

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Implementation of Secure and Verifiable Access Control Procedures using the NTRU Cryptosystem to Store Big Data in the Cloud Environment

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Recent Patents on engineering 2025年第2期19卷 57-70页

作者： Babu B, Ravindra Saxena, Swati Widjaja, Gunawan Vinodha D, Vedha Omarov, Batyrkhan Ramaiah, Gurumurthy B. Vats, Prashant Adama Ethiopia Department of Computer Science KCG College of Technology Chennai India Universitas Krisnadwipayana Jawa Barat 13077 Indonesia Department of Electronics and Communication Engineering JCT College Of Engineering and Technology Pichanur Coimbatore India International University of Tourism and Hospitality Turkistan Kazakhstan Technical and Vocational Training Institute Addis Ababa Ethiopia Department of Computer Science and Engineering Faculty of Engineering and Technology SGT University Haryana Gurugram India

Background: Due to their complexity and size, deploying ciphertexts for clouds is considered the most useful approach to accessing large data stores. Methods: However, access to a user's access legitimacy and improving a decrypted text on the cloud depending on an improved access policy (AP) specified by the data owner are the key challenges for making large data storage realistic and effective in clouds. The traditional ways either totally remove the problem of AP development or offer renewal to arbiter power, but in real-time, enhancing the AP is essential to maximising security and handling agility. Results: In this patent paper, a safe and verifiable access control program characterised by the NTRU cryptographic system for large storage of data in the clouds is proposed. Primarily, an improved NTRU decryption protocol to deal with the decryption failures of the prime NTRU is established, and in addition, the program is analysed for its security strength and computational performance. When a new AP is specified by the data owner, the cloud server allows the program to improve ciphertext and allows the owner to verify the upgrade to oppose the cloud's fraudulent behaviour. Conclusion: It enables (i) checking the user's legitimacy to access the data owner and qualified users, and (ii) allowing the user to verify the data provided by other users for the recovery of the right user. Strong analysis can prevent and block delinquency from various attacks, namely the collusion attack that could potentially target fraud users. © 2025 Bentham science Publishers.

关键词： Cloud security

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Working Pattern Recognition of Phased Array Radar based on Attention Mechanism and Feature Fusion 16

Working Pattern Recognition of Phased Array Radar based on A...

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16th International Conference on Signal Processing Systems, ICSPS 2024

作者： Qu, Zhiyu Li, Linjie Feng, Yun Faculty of Information Science and Engineering Hohai University Nanjing China College of Computer and Information Hohai University Nanjing China

ISBN: (纸本)9781510689251

In the modern battlefield environment, it is very important to realize the working pattern recognition of the enemy phased array radar accurately for subsequent accurate jamming and resource scheduling. In view of the existing radar mode recognition methods, there are problems such as insufficient use of feature parameters and difficulty in paying attention to the relationship between various features of radar signals. This paper provides a method of working pattern recognition for phased array radar based on attention mechanism and feature fusion. The radar signal pulse sequence is preprocessed by feature enhancement and feature fusion, and then fed into the deep learning neural network. We propose an improved Deep learning neural network called CBAM-DenseNet, which is a combination of DenseNet module and CBAM (Convolutional Block Attention Module). The algorithm can grasp the relation between each parameter of the radar signal, and then identify the radar working mode effectively. The experimental findings demonstrate that the identification precision of feature fusion and CBAM-DenseNet for each radar working pattern is more than 99%. © 2025 SPIE.

关键词： Convolutional neural networks

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Translating Words to Pixels: An Effective Text-To-Image System Utilizing Upsampling and CLIP Models

Translating Words to Pixels: An Effective Text-To-Image Syst...

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2024 International Conference on engineering and Computing, ICECT 2024

作者： Saeed, Nuaima Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Faculty of Computer Science and Engineering Department of Artificial Intelligence Topi Pakistan

ISBN: (纸本)9798350349719

Generative AI and text-based image synthesis are being pursued with more interest than ever and adopt a growing audience. This work offers a new way of producing images within a broad range of quality levels, deducing the extra value of the increase resolution. The system applies sophisticated technologies such as diffusion and upscaling models that are guided by the pre-Training of the Contrastive Language-Image PreTraining (CLIP). However, the model shines primarily in its ability to generate visually cohesive and artistic images which are a good illustration of each specified textual prompt. Upsampling technique resolved the major translation problems by generating more high resolution and detailed resultant images of base images. Beyond that, the system also thoroughly illustrated its diversity by accurately producing a comprehensive collection of images based on the text input. This work would largely be a demonstration of the suitability of it for different fields like digital art, advertising, and content creation. Moreover, it delimits the chances of producing innovative and unique content. Future development of many other applications of the system will include the improvement of the system handling more complex textual descriptions, the addition of user-interactive generation features, the optimization of system performance and expanding to multimodal content generation. Our results here only represent a small but important step in this exciting direction. By means of this survey we enrich further knowledges on the field and its farther issues. © 2024 IEEE.

关键词： Signal sampling

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Detection of Mobile Phone Usage Among Motorcycle Riders: A computer Vision Approach 5th

Detection of Mobile Phone Usage Among Motorcycle Riders: A C...

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5th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Charef, Ayoub Jarir, Zahi Quafafou, Mohamed LAMIGEP EMSI Moroccan School of Engineering Marrakesh Marrakesh Morocco Department of Computer Science Faculty of Science Cadi Ayyad University Marrakech Marrakesh Morocco Department of Computer Science University of Aix-Marseille Marseille Marseille France

ISBN: (纸本)9789819791118

This study examines the prevalence of mobile phone use among motorcycle riders at signalized intersections in Marrakech, utilizing advanced computer vision techniques. Employing the YOLOv8 object detection model and the DeepSORT tracking algorithm, our approach effectively detects and tracks mobile phone usage in real-time traffic scenarios. By analyzing data from strategically placed cameras at high-traffic intersections, the research identifies patterns in mobile phone usage among motorcyclists and evaluates the impact on traffic safety. The findings highlight significant times of day for phone usage and offer insights into behavioral trends, providing a foundation for developing targeted interventions to enhance road safety. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Motorcycles

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Design And Implementation Of A PID Control System On A UAV Tracker Antenna

Design And Implementation Of A PID Control System On A UAV T...

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2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023

作者： Jayadi, Akhmad Adhinata, Faisal Dharma Persada Sembiring, Jaka Setyo Adhi, Canggih Gelar Herman Selsily, Wendel Amiruddin, Ahmad Universitas Teknokrat Indonesian Faculty of Engineering and Computer Science Lampung Indonesia Institut Teknologi Telkom Purwokerto Faculty of Informatics Jawa Tengah Indonesia Universitas Bina Nusantara Faculty of Computer Science Semarang Indonesia Universitas Kristen Indonesia Maluku Faculty of Computer Science Maluku Indonesia

ISBN: (纸本)9798350309225

Antennas are essential components in communication systems, serving as both transmitters and receivers. Their efficient operation depends on precise alignment with the strongest signal source, facilitated by tracker antennas. A recent research study focused on enhancing the responsiveness of these tracker antennas. By manually inputting PID (Proportional-Integral-Derivative) values for direction control, the study achieved notable *** results demonstrated that by fine-tuning PID values, particularly setting Kp=5, Ki=0.21812, and Kd=12, and targeting an angle of 90°, the response time was reduced to 1.2 seconds with an overshoot of 28.8% and 1.6 seconds of oscillation. This optimized control mechanism significantly improved antenna direction accuracy, aligning it with the desired setpoint. Furthermore, the importance of antenna alignment and polarization matching in communication systems was emphasized. Ensuring alignment between the receiving antenna's polarization and the incoming wave polarization is crucial for maintaining a strong signal reception power level. This alignment enables accurate tracking of antenna positions, supporting real-time GPS data communication. Additionally, the study involving horizontal azimuth angle measurements with tracker antennas demonstrated their capability to transmit real-time data from multiple positions, achieving 360° horizontal azimuth angles, along with varying elevations. These precise measurements play a vital role in object monitoring and effective communication. © 2023 IEEE.

关键词： Global positioning system

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Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

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computers, Materials & Continua 2022年第5期71卷 2497-2513页

作者： Mohammad Alamgeer Fahd N.Al-Wesabi Huda G.Iskandar Imran Khan Nadhem Nemri Mohammad Medani Mohammed Abdullah Al-Hagery Ali Mohammed Al-Sharafi Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA

Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication *** this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed *** researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English ***,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any *** has been implemented using PHP with VS code *** robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and *** SFASCDW was found to be effective and could be applicable in detecting any possible tampering.

关键词： Watermarking soft computing text analysis hidden Markov model content authentication

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Object Detection in Remote Sensing Images Using Picture Fuzzy Clustering and MapReduce

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computer Systems science & engineering 2022年第12期43卷 1241-1253页

作者： Tran Manh Tuan Tran Thi Ngan Nguyen Tu Trung Faculty of Computer Science and Engineering Thuyloi University175 Tay SonDong DaHanoi010000Vietnam

In image processing, one of the most important steps is image segmentation. The objects in remote sensing images often have to be detected in order toperform next steps in image processing. Remote sensing images usually havelarge size and various spatial resolutions. Thus, detecting objects in remote sensing images is very complicated. In this paper, we develop a model to detectobjects in remote sensing images based on the combination of picture fuzzy clustering and MapReduce method (denoted as MPFC). Firstly, picture fuzzy clustering is applied to segment the input images. Then, MapReduce is used to reducethe runtime with the guarantee of quality. To convert data for MapReduce processing, two new procedures are introduced, including Map_PFC and Reduce_*** formal representation and details of two these procedures are presented in thispaper. The experiments on satellite image and remote sensing image datasets aregiven to evaluate proposed model. Validity indices and time consuming are usedto compare proposed model to picture fuzzy clustering model. The values ofvalidity indices show that picture fuzzy clustering integrated to MapReduce getsbetter quality of segmentation than using picture fuzzy clustering only. Moreover,on two selected image datasets, the run time of MPFC model is much less thanthat of picture fuzzy clustering.

关键词： Remote sensing images picture fuzzy clustering image segmentation object detection MapReduce

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Assessing the Effects of Blackhole Attacks on MANET Reliability and Security

Assessing the Effects of Blackhole Attacks on MANET Reliabil...

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

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

ISBN: (纸本)9798350369106

Mobile Ad Hoc Networks (MANETs) are characterized by some important attributes, including infrastructure, mobile, and dynamic nature, which makes them have vast applications in different areas of computer networks. The black hole attack falls among the strongly criticized security threats within the framework of the MANETs. This deceptive behavior captures data packets from a source destined for the malicious node and then declines them when they are received. This paper comprehensively reviews prior studies done to analyze and mitigate black hole attacks in MANETs. Besides this, we will conduct a comparative analysis of the research above projects. The present paper extends prior work by actually performing the black hole assault simulations in a MANETs environment. This is done with the aid of the NS2 simulator and the Ad Hoc On-Demands Distance Vector (AODV) routing protocol. In this study, the black hole attack is analyzed and the consequences of the attack are assessed in terms of the system performance and security. We analyze crucial parameters like end-to-end latency, PDR, packet drop, and throughput to evaluate the consequences of this assault. From our results derived from the analysis of our simulations, we aim to present substantial points to do with the impacts of blackhole attacks on MANETs. In this way, our goal is to participate in the perpetually evolving efforts aimed at enhancing the security and reliability of such dynamic networks. © 2024 IEEE.

关键词： Mobile ad hoc networks

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.E.Al-Atroush A.E.Aboelela Ezz El-Din Hemdan Civil and Environmental Engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural Engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and Materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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