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Stationary, continuous, and discrete wavelet-based approach for secure medical image transmission

Research on Biomedical engineering 2023年第1期39卷 167-178页

作者： Sayah, Moad Med Redouane, Kafi Med Amine, Khaldi Electrical Engineering Laboratory Department of Electronics Faculty of Sciences and Technology University of Kasdi Merbah Ouargla30000 Algeria Computer Science Department Faculty of Sciences and Technology University of Kasdi Merbah Ouargla30000 Algeria

Purpose: Watermarking is one of the techniques used to protect multimedia data, and images in particular, from malicious attacks by inserting a signature into these images. However, traditional watermarking schemes encounter limitations for sensitive images such as medical images. Methods: In this work, a robust and blind watermarking approach is proposed to secure medical images exchanged in telemedicine. Marking medical images allows precise authentication of the patient and avoids confusing scans and thus avoiding diagnostic errors that can have serious consequences. In this approach, the frequency content of the image is acquired using three different transforms. Schur decomposition is then applied to the low-frequency sub-bands. Finally, the obtained upper triangular matrix values are modifier to integrate the watermark bits. Result and conclusion: Imperceptibility and robustness experimental results show that the proposed methods adequately maintain a significant quality of watermarked images and are remarkably robust against several conventional attacks. Indeed, the average peak signal-to-noise ratio (PSNR) obtained is 44.90 dB which proves that the integration process generates few distortions to the original image. For the robustness, the obtained results show that the watermark is resistant to the most common attacks used in watermarking with a normalized cross correlation rate higher than 0.9 for the majority of the attacks. © 2023, The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering.

关键词： Discrete wavelet transforms

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Refined Neural Attention Network for Aspect Phrases Retrieval in Opinion Mining 15

Refined Neural Attention Network for Aspect Phrases Retrieva...

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

作者： Chauhan, Ganpat Singh Garg, Neeraj Nahta, Ravi Meena, Yogesh Kumar Manipal University Department of Information Technology Jaipur India Skit Department of Computer Engineering Jaipur India Iiit Department of Cse Vadodara India Mnit Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350370249

Recent advances in deep learning have seen accomplishments in a variety of academic fields, notably text processing, image processing, machine translation, and social network screening. On numerous social media platforms, a lot of user-generated content is accessible. that can be applied to precisely analyze opinions in light of evolving market conditions. In sentiment analysis at aspect-level, the aspect phrase retrieval (APR) operation finds the users' intended topics in the content of the document. The bulk of aspect retrieval techniques are context or domain dependent. Additionally, due to a lack of topical and situational expertise, it is challenging to pinpoint the most important domain-specific element phrases. Due to their inability to recognize noun phrase relationships as time passes, the present extraction techniques have no way to determine several essential aspect terms. This study suggests using linguistic patterns with deep attention network to improve the APR problem. Findings from investigations and tests are analyzed across a variety of factors on common review datasets. © 2024 IEEE.

关键词： aspect phrase retrieval attention model natural language processing opinion mining

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Exploring the Potential of Secure Shell (SSH) as a Wireless Network Security Tool 15

Exploring the Potential of Secure Shell (SSH) as a Wireless ...

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

作者： Mishra, Abhinav Sahoo, Girija Shankar Sekaran, Ramesh Umamaheswari, B. Futane, Pravin R. Choudhary, Sanjay Chitkara University Institute of Engineering and technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi University of Information Technology Maharishi School of Engineering and Technology UttarPradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Ramnagar District562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India

ISBN: (纸本)9798350370249

Comfy Shell is an open-source protocol used for many years to comfy community logins and communication over the net. It is primarily based on public key cryptography and is well known for being one of the maximum cozy strategies of authentication and communication. It is now being explored as a Wi-Fi network security device for defensive information transmitted over WiFi networks, including those typically determined in cafes, airports, and other public locations. Its safety capabilities, which include robust authentication and encryption, make it an excellent desire to securely access assets, shift information, and connect to far-off structures. Moreover, it can be used as a digital private network (VPN) to safely establish connections between two or extra computers in a public community. At the same time as SSH is properly-appropriate for relaxed far-off connections, it can be configured to provide additional ranges of authentication and encryption to ensure the WiFi network's safety from malicious assaults. This paper will explore the capability of SSH as a Wi-Fi network safety tool, discuss diverse implementations, and focus on the particular components of using SSH as a security device for WiFi networks. © 2024 IEEE.

关键词： Wi-Fi

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EFFECTS OF CUTTING AND WELDING ON ELECTRIC STEELS' FERROMAGNETIC MATERIAL

EFFECTS OF CUTTING AND WELDING ON ELECTRIC STEELS' FERROMAGN...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Agarhari, Abishek Singh, Thakur Meenu Balaji, N.V. Arul Antran Vijay, S. Borade, Monali Ravindra Department of Computer Science & Engineering Invertis University Uttar Pradesh Bareilly243123 India School of Mechenical Engineering Dev Bhoomi Uttarakhand University Uttarakhand 248007 India Department of Computer Science & Engineering School of Engineering & Technology K. R. Mangalam University Haryana Gurugram122103 India Department of Computer Science Karpagam Academy of Higher Education Coimbatore641021 India Department of Computer Science Engineering Karpagam College of Engineering Coimbatore641032 India AI & Ds Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350355338

This study examines the crucial function that silicon steels, sometimes referred to as electric steels, serve in electromagnetic applications like transformers and motors. The need of preserving ferromagnetic characteristics for effective energy exchange is emphasized in particular. In order to fill in knowledge gaps about the precise effects of the two processes on these materials, this investigation presents a methodology that emphasizes the significance of careful material selection, thorough recording of the cutting and welding procedures, and an organized method of measurement and *** study recognizes the broad implications for industrial, power distribution, and automotive sectors, where ferromagnetic properties are necessary for electrical equipment to remain reliable. The study attempts to provide understanding of the unique effects of the two processes on electric steels, suggesting mitigating measures via a thorough analysis of the body of current literature. The transparent and reproducible technique presented in this study contributes to our knowledge of how electric steels behave in various contexts. The ultimate goal of the study is to improve production methods and guarantee that electromagnetic gear operates as well it can in our environment of growing electricity. © 2024 IEEE.

关键词： Automotive industry

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Multiple Instances Fingerprint Image Data Acquisition

Multiple Instances Fingerprint Image Data Acquisition

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2023 IEEE International Conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Jooda, Janet O. Ogundokun, Roseline Oluwaseun Adedeji, Oluyinka T. Ajagbe, Sunday Adeola Adigun, Matthew O. Oke, Alice O. Omidiora, Elijah O. Redeemer's University Department of Computer Engineering Osun State Ede Nigeria Kaunas University of Technology Department of Multimedia Engineering Kaunas Lithuania Landmark University Department of Computer Science Omu Aran Nigeria Ladoke Akintola University of Technology Department of Information System Science Ogbomoso Nigeria University of Zululand Department of Computer Science Kwadlangezwa3886 South Africa First Technical University Department of Computer Engineering Ibadan200255 Nigeria Ladoke Akintola University of Technology Department of Computer Engineering Ogbomoso Nigeria

ISBN: (纸本)9798350327816

Using public fingerprint databases to validate the multi-instance fusion approach of a Multi-instance Biometric Authentication System (MBAS) for accurate authentication is a means of overcoming some of the limitations of a Unimodal Biometric System (UBS). Nevertheless, a significant portion of the web databases used for MBAS (Machine Learning-Based Automated Systems) were obtained under controlled conditions, with the photos being curated to align with a certain algorithmic objective. The performance of biometric systems exhibits variability when the datasets used in the algorithms undergo modifications as a result of discrepancies in the settings under which the photos were obtained. In this study, a database containing multiple fingerprint instances was developed locally in an uncontrolled environment. The aim was to create a database containing numerous examples of fingerprints for the same person from one or multiple data collection sessions. The database was produced locally by acquiring six samples of ten fingerprint instances of 150 subjects in an uncontrolled environment using a Futronic fingerprint scanner. The created database and results will be helpful to all researchers in the biometrics field as a tool for improving multi-instance fusion methods and enabling an unbiased evaluation of algorithms. © 2023 IEEE.

关键词： Biometrics Fingerprint Image data acquisition Multiple instances Unimodal biometric system

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An IoT-Assisted Real-Time Urban Air Pollution Data Collection System 5th

An IoT-Assisted Real-Time Urban Air Pollution Data Collectio...

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5th International Conference on Computing and Network Communications, CoCoNet 2023

作者： Ghose, Banani Minsar, Sk. Ghosh, Udayan Arif Mohammad, Sk. Mallick, Adil Hossain Rehena, Zeenat Department of Information Technology Haldia Institute of Technology West Bengal Haldia India Department of Computer Science and Engineering Aliah University West Bengal Kolkata India

ISBN: (纸本)9789819745395

Air pollution is one of the innumerable menaces an individual comes across every moment. Countless means to make urban lives smoother are indebted to witnessing air pollution and other types of pollution. It is contributed by unrestricted urbanization, traffic, industrial emissions, etc., causing life-threatening diseases;even death. Monitoring air pollution should be the primary objective of any society. For an effective air pollution monitoring system to run and deliver a real-time Air Quality Index (AQI) a prompt IoT-enabled air pollution sensor-based data collection system is a prerequisite. In this letter, a real-time hardware-based IoT-enabled air pollution-related data collection module is designed. This will be portable and will be recording both pollutant concentrations and meteorological factors. It consists of a number of sensors and a Wi-Fi module. Collected data will be directly sent to the cloud for further analysis. Thus, as a part of the air pollution monitoring system, this module will be capable of recording real-time data, that will lead to real-time air health monitoring. It will assist urban residents and policymakers in taking decisions that will guide them to have healthier lives. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Air quality

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An Effective Cyber Security Threat Detection in Smart Cities Using Dueling Deep Q Networks 4

An Effective Cyber Security Threat Detection in Smart Cities...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Stanly Jayaprakash, J. Kodati, Sarangam Kanchana, A. Al-Farouni, Mohammed Ramachandra, A.C. Mahendra Institute of Technology Department of Computer Science and Engineering Namakkal India Cvr College of Engineering Department of Information Technology Hyderabad India Mahendra Engineering College for Women Department of Computer Science and Engineering Namakkal India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350352931

In recent days, smart city technologies are developing rapidly with the incorporation of IoT devices and AI-driven systems has modernized and thus facilitated for enhancing productivity, sustainability, and connectivity. The motive is to mitigate the rising cyber threats which are affecting the interrelated organizations of smart cities. Despite advancements in threat detection technologies, challenges persist, including real-time anomaly detection in vast data streams, managing resource constraints on IoT devices, and ensuring adaptability against evolving attack vectors. Therefore, this research suggests a novel approach by using Dueling Deep Q Networks (DDQN) method. Initially, the data is collected from the dataset and then Inter Quartile Range (IQR) is imposed at the preprocessing stage for detection of outliers. Then, extraction of optimal features is done by using Term Frequency-Inverse Document Frequency (TF-IDF) and Recursive Feature Elimination (RFE) which transforms the data into statistical vectors and eliminates the least significance feature respectively. Finally, the obtained optimal features are detected using DDQN method as it has the ability to detect effectively with respect to the state of action. The proposed DDQN has resulted with accuracy of 99.32% when compared with Improved Bacterial Foraging Optimization using optimum deep learning for Anomaly detection (IBFO-ODLAD). © 2024 IEEE.

关键词： Cyber attacks

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Statistical Analysis of Electromagnetic Coupling to Printed Circuit Boards

Statistical Analysis of Electromagnetic Coupling to Printed ...

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2024 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2024

作者： Xia, Shengxuan Khilkevich, Victor Beetner, Daryl Missouri University of Science and Technology Emc Laboratory Electrical and Computer Engineering Department RollaMO United States

ISBN: (纸本)9798350360394

Determining electromagnetic (EM) coupling to printed circuit boards (PCBs) is essential to finding potential EM susceptibilities early in the design process. For realistic PCB structures, analysis usually relies heavily on time-consuming full-wave simulations because of the complexity of the geometries and the lack of analytical solutions. In this paper, we adopt a segmentation approach based on far-field reciprocity which allows for rapid estimation of the voltage induced at trace terminations over frequency, and which is then used to estimate statistical characteristic of coupling across trace geometries. Frequency-domain results can then be used to estimate time-domain responses with appropriate transformations. Super-position is then used to separate the coupling contributed by different PCB structures, which provides better insight into the mechanisms responsible for susceptibility. © 2024 IEEE.

关键词： Time domain analysis

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Improving Biometric Security Using PulsePrint: Real-Time Defense Against Fingerprint Spoofing 2

Improving Biometric Security Using PulsePrint: Real-Time Def...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Vigneshwaran, P. Maranco, M. Ivaturi, Kashyapa Abhiram Takur, Purab Acharya University Department of Computer Science and Engineering Karakul Bukhara Uzbekistan SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Networking and Communications Chengalpattu Kattankulathur603203 India

ISBN: (纸本)9798350365269

Biometric authentication systems have become increasingly popular due to their convenience and perceived security benefits. However, traditional biometric modalities such as fingerprint recognition are vulnerable to spoofing attacks, where fake fingerprints can be used to deceive the system. In this paper, we propose PulsePrint, a novel biometric authentication solution that enhances security by incorporating real-time pulse detection alongside fingerprint recognition. By leveraging the unique pulsatile nature of blood flow in the fingertip, PulsePrint adds an additional layer of authentication, making it significantly more difficult for attackers to spoof fingerprints. We present the design and implementation of the PulsePrint system, detailing the integration of pulse detection algorithms with existing fingerprint recognition technologies. Furthermore, we evaluate the performance of PulsePrint through extensive experimentation, including testing against various spoofing techniques and benchmarking against conventional fingerprint recognition systems. Our results demonstrate that PulsePrint offers robust protection against fingerprint spoofing attacks while maintaining user convenience and real-time authentication speed. Overall, PulsePrint represents a promising advancement in biometric security, offering enhanced protection for applications requiring reliable and secure authentication. © 2024 IEEE.

关键词： Authentication

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An Effective Ensemble Learning Method for Fault Diagnosis of Photovoltaic Arrays 3rd

An Effective Ensemble Learning Method for Fault Diagnosis of...

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3rd International Conference on Electronic engineering and Renewable Energy, ICEERE 2022

作者： Mellit, Adel Boubaker, Sahbi Department of Electronics Faculty of Science and Technology University of Jijel Jijel Algeria Department of Computer and Network Engineering College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9789811962226

In this paper, a novel fault diagnosis method for photovoltaic (PV) arrays is proposed. The method combines three machine learning (ML) algorithms: the first one is an unsupervised ML algorithm (principal component analysis, ‘PCA’) used for features reduction;the second one is a kind of a recurrent neural networks (long short-term memory, ‘LSTM’) employed to predict the PV power;and the third one is a supervised ensemble learning categorical boosting algorithm (CatBoost), used mainly for fault classification improvement. Four types of faults (dust deposit on PV modules surface, partial shading effect, shunted diode and open-circuit diode) are examined in this study. Results showed the effectiveness of the proposed method in terms of detection and classification accuracy, 98.70% and 98.58% respectively, and demonstrate the superiority of this method over other investigated ML algorithms (e.g. decision tree, support vector machine, k-nearest neighbours, and random forest). © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

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