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Cybersecurity advancements for medical image transmission: a hybrid optical-based cryptosystem harnessing chaos, DNA sequences, and mandelbrot keys

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Multimedia Tools and Applications 2025年 1-41页

作者： Alalwan, Nasser El-Shafai, Walid Amoon, Mohammed Benjdira, Bilel Department of Computer and Communication Engineering King Saud University Riyadh Saudi Arabia Prince Sultan University Riyadh11586 Saudi Arabia Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh12435 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt

In today's advanced technological age, characterized by innovations like big data processing, cloud computing, and the Internet of Things (IoT), there is a rising utilization of medical multimedia data, especially medical images. These images, integral to the Internet of Healthcare Things (IoHT), necessitate secure transmission due to the increasing risks of unauthorized breaches and tampering. Current security methods, especially for cloud and mobile platforms, often struggle with challenges related to processing capacity, memory use, data size, and energy, making them ill-suited for extensive medical data or resource-limited environments. To address these challenges, this study introduces a novel hybrid cryptosystem, drawing on the unique qualities of the optical Arnold chaotic map, DNA (DeoxyriboNucleic Acid) sequences, and Mandelbrot keys, providing a fortified approach to the secure streaming of medical images. The proposed framework operates via a precise and structured procedure. It begins by applying the optical Arnold chaotic map cipher to each of the three-color channels (R, G, and B) within a medical image. This is followed by overlaying DNA encoding sequences on the resultant encrypted image from the earlier ciphering phase. Leveraging this groundwork, we incorporate an advanced Mandelbrot set-driven shift mechanism specifically designed to create complex confusion patterns within the R, G, and B segments of the encrypted medical imagery. The efficacy of the proposed cryptosystem is rigorously substantiated through an extensive array of simulations supported by a comprehensive security analysis. The results highlight its unparalleled resilience and security capabilities in the realm of medical image encryption, marking a significant leap over previous systems in the literature. Essentially, our work pioneers a solution to a pressing challenge in medical image security, ensuring enhanced protection of delicate health data among the rapidly evolving advanc

关键词： Cybersecurity

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Broken Rotor Bar Fault Detection in Induction Machines Based on Rectified Three-Phase Stator Currents 10

Broken Rotor Bar Fault Detection in Induction Machines Based...

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10th International Conference on Signal Processing and Intelligent Systems, ICSPIS 2024

作者： Hajnayeb, Saeed Amerian, Fatemeh Marzebali, Mohammad Hoseintabar Abolghasemi, Vahid Seyyedbarzegar, Seyyed Meysam Shahrood University of Technology Faculty of Electrical Engineering Department Shahrood Iran School of Computer Science and Electronic Engineering Department University of ESSEX Colchester United Kingdom

ISBN: (纸本)9798331532543

Induction machines are widely used in industrial and household applications due to their efficiency in electromechanical energy conversion. However, broken rotor bars can significantly disrupt machine performance, typically manifesting as sideband harmonics near the fundamental frequency which can be utilized for fault detection. Nonetheless, frequency leakage can impede fault detection, concealing fault until substantial damage occurs. The proposed method, based on the rectified three-phase stator current (RTPSC), effectively reduces leakage frequency while maintaining the fault characteristic frequency (FCF) at its original amplitude. In addition, generate the fundamental harmonic at a frequency of 6 times. This approach aims to is to enhance diagnostic capabilities in the maintenance and monitoring of induction machines, improving operational efficiency and it also reduces the chance of catastrophic failures. The proposed methodology is tested on cases involving one, two, and three broken rotor bars, with the simulation results validated through experimental verification. © 2024 IEEE.

关键词： Stators

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Deciphering Stem Cell Fate with an Integrative Multi-Omics Examination of Microenvironmental Dynamics

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SN computer Science 2025年第1期6卷 1-14页

作者： Shanthanam, Radha Rammohan Selvam, Janani Vajravelu, Ashok Pradeep, T. Post Doctoral Fellowship (PDF) programme in Computer Science Engineering Lincoln University College Petaling Jaya Malaysia Faculty of Engineering Lincoln University College Petaling Jaya Malaysia Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Kongu Engineering College Tamilnadu Erode India

The evidence-based literature on healthcare is akin to a vast universe, continually expanding with new discoveries and insights. In this dynamic landscape, the integration oftools and multi-omics approaches a beacon of hope, illuminating the intricate pathways that govern stem cell fate within the microenvironment. Still, figuring out how stem cell fate is determined is complicated and calls for a multifaceted understanding that cuts beyond traditional discipline lines. This review navigates through the evolutionary trajectory of AI integration in medicine, tracing its transformative impact on hematology and beyond. It explores the burgeoning field of AI applications in hematopoietic cell transplantation (HCT), from diagnosis to prognosis, heralding a new era of precision medicine. Through the lens of integrative multi-omics methodologies, the review delves into the molecular signatures intricately woven within the stem cell niche, deciphering the regulatory networks orchestrating stem cell fate decisions. Emerging technologies like single-cell multi-omics profiling and spatial transcriptomics offer newfound vistas to explore cellular heterogeneity and spatial organization within the stem cell niche, paving the way for transformative advances in regenerative medicine. Harnessing the power of AI and multi-omics methodologies, this review embarks on a quest to dissect stem cell fate with unparalleled precision, ushering in a new era of personalized therapeutics and regenerative interventions. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cellular heterogeneity Hematology Molecular signatures Precision medicine Stem cell niche

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Machine Learning Approach to QoS Adjustment Leveraging LCR in Mobile Networks Limited by Beaulieu-Xie Fading and Co-Channel Interference 10

Machine Learning Approach to QoS Adjustment Leveraging LCR i...

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10th International Conference on Electrical, electronic and Computing engineering, IcETRAN 2023

作者： Krstić, Dragana Suljović, Suad Petrović, Nenad Nestorović, Goran Milić, Dejan Telecommunications University of Niš Faculty of Electronic Engineering Niš Serbia The Academy of Applied Technical Studies Belgrade Applied Engineering Science Belgrade Serbia University of Niš Faculty of Electronic Engineering Computer Science Niš Serbia

ISBN: (纸本)9798350307115

Future applications of wireless systems requires as better channel models as possible. For this reason, a few years ago new fading model was discovered by Norman Beaulieu and Xie Jiandong for wireless systems containing multiple dominant specular components. This fading model is named after the authors Beaulieu-Xie fading and distribution is given in closed form. It has been shown that this model can be more useful than the known Ricean and Nakagami models for describing wireless environments with line-of-sight (LoS) and multiple reflected specular components (non-line-of-sight (NLoS) environment). In this work, we analyzed wireless system with selection combining in the presence of Beaulieu-Xie fading and co-channel interference. For such scenario, we derived the formula for level crossing rate (LCR) and plotted some graphs. Then, we examined the influence of the fading parameters, having real physical meaning and allow setting up of the fading severities. At the end, we make use of the calculated value of LCR for classification-based machine learning approach to Quality of Service (QoS) degree estimation, together with other factors (network load, temporal aspects). © 2023 IEEE.

关键词： Quality of service

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Development of a Smart IOT Enabled Arduino Glove Supporting Sign Language Communication 26

Development of a Smart IOT Enabled Arduino Glove Supporting ...

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26th International Conference on computer and Information Technology, ICCIT 2023

作者： Zaman, Muhammad Shahriar Victor Biswas, Richard Faculty of Science and Technology Department of Computer Science and Engineering Dhaka1229 Bangladesh Faculty of Engineering Department of Electrical and Electronic Engineering 408/1 Kuratoli Dhaka1229 Bangladesh

ISBN: (纸本)9798350359015

Deafness is an unfortunate issue of our society impairing many people. Around 3 million people in Bangladesh suffer from partial or complete deafness. One key challenge for these individuals is communicating with regular people. Various sign languages are available but very few people are knowledgeable about it. Keeping this issue in consideration this project has been developed. The smart Arduino glove allows the user to express their ideas by translating their fingerspelling as well as the gestures into comprehensible messages. The system also allows identification of common sentences by identifying simple gestures. The suggested system if applied in daily life can bring a positive change in the lives of deaf-mute individuals. © 2023 IEEE.

关键词： Accelerometer Alphabets Deaf Digits Fingerspelling Flex sensor Gesture Recognition I2C MPU-6050 Mute PAJ7620 Sign language

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Security Analysis for SCKHA Algorithm:Stream Cipher Algorithm Based on Key Hashing Technique

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Chinese Journal of electronics 2022年 1-16页

作者： Souror Samia El-Fishawy Nawal Badawy Mohammed Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University

The strength of any cryptographic algorithm is mostly based on the difficulty of its encryption key. However, the larger size of the shared key the more computational operations and processing time for cryptographic algorithms. To avoid increasing the key size and keep its secrecy, we must hide it. The authors proposed a stream cipher algorithm that can hide the symmetric key[1]through hashing and splitting techniques. This paper aims to measure security analysis and performance assessment for this algorithm. This algorithm is compared with three of the commonly used stream cipher algorithms: RC4, Rabbit, and Salsa20 in terms of execution time and throughput. This comparison has been conducted with different data types as audio, image, text,docs, and pdf. Experiments proved the superiority of SCKHA algorithm over both Salsa20 and Rabbit algorithms. Also, results proved the difficulty to recover the secret key for SCKHA algorithm. Although RC4 has a lower encryption time than SCKHA, it is not recommended for use because of its vulnerabilities. Security factors that affect the performance as avalanche effect, correlation analysis, histogram analysis, and Shannon information entropy are highlighted. Also, the ciphertext format of the algorithm gives it the ability to search over encrypted data.

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Invariant of Enhanced AES Algorithm Implementations Against Power Analysis Attacks

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computers, Materials & Continua 2022年第7期72卷 1861-1875页

作者： Nadia Mustaqim Ansari Rashid Hussain Sheeraz Arif Syed Sajjad Hussain Department of Electronic Engineering Dawood University of Engineering&TechnologyKarachiPakistan Faculty of Engineering Sciences and Technology Hamdard UniversityKarachiPakistan Faculty of Information Technology Salim Habib UniversityKarachiPakistan Faculty of Computer Sciences SZABISTKarachiPakistan

The security of Internet of Things(IoT)is a challenging task for researchers due to plethora of IoT *** Channel Attacks(SCA)are one of the major *** prime objective of SCA is to acquire the information by observing the power consumption,electromagnetic(EM)field,timing analysis,and acoustics of the ***,the attackers perform statistical functions to recover the *** Encryption Standard(AES)algorithm has proved to be a good security solution for constrained IoT *** paper implements a simulation model which is used to modify theAES algorithm using logicalmasking *** invariant of the AES algorithm hides the array of bits during substitution byte transformation of *** model is used against SCAand particularly Power Analysis Attacks(PAAs).Simulation model is designed on MATLAB *** will give better solution by hiding power profiles of the IoT devices against *** future,the lightweight AES algorithm with false key mechanisms and power reduction techniques such as wave dynamic differential logic(WDDL)will be used to safeguard IoT devices against side channel attacks by using Arduino and field programmable gate array(FPGA).

关键词： Side channel attacks power analysis attacks network security masking advance encryption standard

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Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

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computers, Materials & Continua 2023年第2期74卷 3607-3625页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at School of Electrical Engineering Faculty of EngineeringUniversiti Teknologi MalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti Teknologi Malaysia(UTM)SkudaiJohorMalaysia Department of Electronics and Electrical Engineering Faculty of EngineeringInternational University of AfricaKhartoum12223Sudan Department of Communication Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu Pahat86400JohorMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond *** random movement of mobile terminals in the indoor environment is a challenge in the VLC *** model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)*** optimized optical attocells were examined and compared with previous *** novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 *** bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,*** optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,*** the results of the proposed model are optimal,it is suitable for standard office and room model applications.

关键词： Visible light communication(VLC) optical attocell received power signal-to-noise ratio(SNR) bit error rate(BER) coefficient of variation(CV)

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Comparison of Contrast Enhancement Methods in Adenocarcinoma Cancer Images 4

Comparison of Contrast Enhancement Methods in Adenocarcinoma...

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4th International Conference on electronic and Electrical engineering and Intelligent System, ICE3IS 2024

作者： Azizah, Laila Ma'rifatul Kanafiah, Siti Nurul Aqmariah Bt. Mohd. Jusman, Yessi Raof, Rafikha Aliana A. Zin, Anani Aila Mat Bin Mashor, Mohd Yusoff Perlis Arau Malaysia University Malaysia Perlis Mechatronic Engineering Faculty of Electrical Engineering and Technology Perlis Arau Malaysia Universitas Muhammadiyah Yogyakarta Electrical Engineering Faculty of Engineering Yogyakarta Indonesia University Malaysia Perlis Computer Engineering Faculty of Electronic Engineerin and Technology Perlis Arau Malaysia Hospital Universiti Sains Malaysia Pathology Kelantan Kubang Kerian Malaysia University Malaysia Perlis Faculty of Electronic Engineering and Technology Perlis Malaysia

ISBN: (纸本)9798350378368

This study quantifies the extent to which various image enhancement methods can improve the quality and visibility of adenocarcinoma cells on cytology slide images. The primary goal is to overcome the problems of low contrast and blurring inherent in microscopic imaging of such cells. The researchers analyzed the Partial Contrast, Contrast Limited Adaptive Histogram Equalization (CLAHE), and Histogram Equalization (HE) methods. Then, it was applied to a dataset of 418 cytology images, including benign and malignant adenocarcinoma cells. The results show that Partial Contrast offers the most superior performance. Partial contrast achieved the lowest Mean Squared Error (MSE) and the highest values in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). This method improves the overall brightness and contrast between light and dark areas of the image and maintains a better level of fine detail and structural integrity. Thus, Partial Contrast proved to be the best approach to improve the appearance of adenocarcinoma cells on cytology slides, offering better clarity and better contrast, which has great potential in improving the diagnosis of adenocarcinoma. © 2024 IEEE.

关键词： Mean square error

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Performance Evaluation of YOLO Models for Automatic Crop and Weed Detection 33

Performance Evaluation of YOLO Models for Automatic Crop and...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Stankovic, L. Nikolic, T. Talaska, T. Dlugosz, R. University of Nis Faculty of Electronic Engineering Nis Serbia Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz Poland

ISBN: (纸本)9798350347760

Accurate weed mapping is essential for the implementation of weed management in order to maintain high crop yields and less chemical pollution. This paper focuses on the performance evaluation of YOLO models for automatic crop and weed detection. The research aims to develop weed detection models using one-stage deep learning-based object detectors by transferring pre-trained object detection models to a selected weed dataset. The models are trained on annotated images from a public dataset and evaluated based on detection accuracy. Results demonstrate promising training performance, with approximately 70% mean average precision achieved in 100 training epochs. YOLOv5x exhibits the best performance among the studied models, achieving the highest precision, recall, and mean average precision (0.72, 0.75, and 0.74, respectively). The findings indicate that models with deeper or larger backbone networks tend to provide higher detection accuracy. © 2023 IEEE.

关键词： Crops

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