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Enhancing Data Security Using Steganography in Spatial Domain images

Enhancing Data Security Using Steganography in Spatial Domai...

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Emerging Trends in Information technology and Engineering (ic-ETITE), conference on

作者： Dimas Wahono Hilmy Rahman Hisyam Syarif Ntivuguruzwa Jean De La Croix Tohari Ahmad Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia African Centre of Excellence in Internet of Things University of Rwanda Kigali Rwanda

The evolution of technology in transmitting information across public networks has highlighted the need to focus on data security to safeguard information. Numerous research endeavours have introduced diverse data protection approaches to enhance the security of confidential information transferred over publicly shared networks. Nevertheless, prior solutions have fallen short of delivering effectiveness to safeguard the sensitive data. To surmount this drawback, this article introduces a new data hiding approach based on steganography paradigm to improve the confidentiality of the hidden information by utilizing adjacent pixels-based difference expansion within a digital image. Experimental outcomes indicate that our method outperforms existing approaches, notably enhancing the state-of-the-art Peak signal-to-noise Ratio (PSNR). This signifies a notable advancement in visibility quality of the stego image with the proposed method.

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5th international Workshop on New Approaches for Multidimensional signal Processing, NAMSP 2024

5th International Workshop on New Approaches for Multidimens...

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5th international Workshop on New Approaches for Multidimensional signal Processing, NAMSP 2024

ISBN: (纸本)9789819624812

The proceedings contain 28 papers. The special focus in this conference is on New Approaches for Multidimensional signal Processing. The topics include: Jamming image Recognition Problem;Performance Evaluation of Surface Defect Segmentation with an Novel Battery Surface RGB Dataset;dynamic Tensor Least Angle Regression Using L1 Homotopy;multidimensional signal Analysis of Colorectal Cancer Using Bioinformatic Techniques;performance Evaluation of Workpiece Counting Neural Network with a Novel Sketch Dataset for Reducing Background Noise;entity Resolution Using Transformers for Synthetic Datasets;sound-Driven Identification of South African Birds;application of Deep Learning Models for Multimodal Information Fusion in Intelligent Information Classification;an Introductory Glimpse of Machine Learning Applications in Multidimensional signal Analysis;electromyography-based Hand Movement Detection Using Machine Learning Algorithm;research on the Application of Reinforcement Learning in Film Script Generation and Narrative Innovation;design of Publicity Animation Sample based on Dynamic Simulation technology;research on image Enhancement technology based on Semi-Supervised Learning for Oil Painting image;performance Analysis of Digital Control Oscillator Using Ant Colony Optimization;a Study on the Application of Different Types of Electric Motors as Electric Vehicles’ Drives and on the Necessity of 3D image Analysis;a Deep Learning-based Study of Adolescents’ Self-Esteem Developmental Patterns: Exploring the Intersection of Psychology and Data Science;research on Interactive Experience of Virtual Reality technology in Oral English Teaching;A SOM Algorithm for Chronic Hepatitis B Drug Expenditure Forecast;construction of Knowledge Map and Design of Decision Support System for Diagnosis of Tumor Disease;intelligent Hotel Management System Combined with Facial Recognition technology.

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Approach for Double Security with Watermarking and Chaos based Encryption for e-Healthcare systems

Approach for Double Security with Watermarking and Chaos Bas...

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Electrical, Computer and Energy Technologies (ICECET), international conference on

作者： Suvita Rani Sharma Birmohan Singh Manpreet Kaur Harpreet Singh Department of Computer Science and Engineering Sant Longowal Institute of Engineering and Technology Sangrur Punjab India Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology Sangrur Punjab India

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

Medical data of the patients includes sensitive information and needs security while transmit over the internet. The double security approach based on watermarking and encryption method has been purposed in this work to secure the patient information consisting personal information, clinical information, and diagnostic records along with the medical images. The watermarking method is introduced on the basis of the least significant bit (LSB) method that conceals the patient information in the LSB bit of the image to hide the information. As, the LSB bit of the image is consider as least informative bit. Thus, it reduces the loss of data in the image. Then, the watermarked image is secured using the hybrid encryption method based on the Self Adaptive Bald Eagle Search (SABES) optimization algorithm, multiple chaotic maps, and circular shift. Chaotic maps are employed in the proposed approach to increase randomness in the encrypted image and chaotic maps' parameters are optimized employing the SABES optimization method to increase the chaotic maps efficiency. The propounded approach is tested on different types of medical images i.e., Grayscale, RGB, and hyperspectral images having different modalities and sizes. The performance of the propounded approach has been analyzed utilizing the Normalized Correlation (NC), Peak signal-to-Noise Ratio (PSNR), entropy, histogram, Number of Changing Pixel Rate (NPCR), Structural Similarity Measure (SSIM), and Unified Averaged Changed Intensity (UACI) test. The proposed approach performance shows that the medical information secure from different types of attacks.

关键词： Measurement Histograms PSNR image resolution Optimization methods Watermarking Gray-scale Encryption Medical diagnostic imaging Hyperspectral imaging

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Computer Network Information Security Supervision and Protection Strategy with internet of Things Information technology

Computer Network Information Security Supervision and Protec...

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6th international conference on Intelligent Computing and signal Processing (ICSP)

作者： Xiang Nan Rajamohan Parthasarathy Chu Wang School of Information Technology NanTong Normal College Nantong Jiangsu China Faculty of Engineering Built Environment and Information Technology SeGi University Kota Damansara Malaysia School of Microelectronics Xidian University Xi'an Shaanxi China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

With the continuous development and popularisation of internet of Things (IoT) technology, the regulation and protection of computer network information security has become increasingly important. The application of IoT information technology enables various devices and systems to communicate and interact with each other, however, it also brings new security challenges and risks. In this context, it is particularly urgent and necessary to develop effective regulation and protection strategies. This paper focuses on computer network information security in the internet of Things environment, considering the rapid development of the internet of Things and its unique security challenges, to study the regulation and protection strategies to adapt to this field. First, this content investigates the shortcomings of traditional information security strategies in dealing with the diversity, large-scale deployment, data privacy protection, real-time monitoring and cross-border integration of the IOT, and discusses the important exploration results and existing defects in the field of IOT security in the current academia and industry. based on a step-by-step exploration of existing references and methods, this content designs a multi-level security protection system that covers security requirements from the device layer to the application layer. In threat detection, the system shows an average of 95% threat detection accuracy, ensuring efficient security monitoring. The system stability and performance evaluation experiment shows that the CPU usage maintenance rate is about 65% on average, and the memory usage is about 55% on average. The above data indicates that the system maintains good stability while operating efficiently. In the adaptive defense mechanism effect test, the system shows an average of about 3 defense mechanism adjustments per day, indicating its high adaptability in a dynamic security environment. The above experimental results jointly verify the effectiv

关键词： Adaptive systems Information security signal processing Threat assessment Regulation Computer networks Real-time systems internet of Things Protection Information technology

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Performance Comparison Between Moment Features and Using a Free Classification Service in Change-Robust Texture Recognition

Performance Comparison Between Moment Features and Using a F...

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international conference on Information technology (INCIT)

作者： Yukinobu Miyamoto Faculty of Science and Engineering Otemon Gakuin University Osaka Japan

ISBN: (数字)9798350366303

ISBN: (纸本)9798350366310

Texture is one of the important characteristics used to identify objects or target areas in images. One of the difficulties in texture recognition is to ensure robustness against movement, rotation, and scale changes. In the past, texture recognition has been based on features derived from wavelet transforms and classified by neural networks or other classifiers. However, it is difficult to classify textures of different scales and rotations using only these methods. We propose a texture recognition based on moment features. Wavelet coefficients corresponding to each signal band are used to compute moment features. For classification, each moment feature is fed to a neural network. The recognition results are compared with Google Teachable Machine, a free classification service, to verify the superiority of our proposed method. It is confirmed that our proposed method improves the recognition rate under certain conditions.

关键词： image recognition image coding Neural networks Training data Robustness internet Object recognition Information technology Wavelet coefficients Graphical user interfaces

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Study of the heterogeneity problem in the internet of Things and Cloud Computing integration 10

Study of the heterogeneity problem in the Internet of Things...

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10th international Symposium on signal, image, Video and Communications (ISIVC)

作者： Mafamane, Rachid Ouadou, Mourad Tahri Joutey Hassani, Adnane Minaoui, Khalid Univ Mohammed 5 Comp & Telecom Res Lab Rabat Morocco

ISBN: (纸本)9781728176680

Since the internet of Things will continue to grow in the coming years, the need for services covering several IoT application areas will grow in order to realize the efficiency gains promised by IoT. Cloud computing, in particular, is a technology closely related to the internet of Things. The synergy between the Cloud and IoT has emerged largely from the attributes of the Cloud that directly benefit IoT and enable its continued growth. The adoption of cloud services by IoT faces new challenges. However, service developers looking to add value to existing IoT systems are faced with very heterogeneous devices and systems. These systems implement a wide variety of network connectivity options, proprietary or standards-based protocols, and communication methods unknown to an innovative IoT service developer. In this paper, the problem of heterogeneity in the internet of Things and Cloud Computing integration is studied, and some existing solutions are compared.

关键词： internet of Things Cloud Computing heterogeneity interoperability Cloud of Things

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An IoT based Electromyography signal Transmission from sEMG Electrodes to Client's Server with ICT Infrastructure

An IoT Based Electromyography Signal Transmission from sEMG ...

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international conference on Advanced Computing and Communication systems (ICACCS)

作者： P. M. Pavithra M. Balakrishnan A. Anandaraj M. Ramya R. Raja Sudharsan Department of Artificial intelligence and Data Science Sri Shanmugha College of Engineering and Technology Salem India Department of Artificial intelligence and Data Science Dr. Mahalingam College of Engineering and Technology Pollachi India Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore India Department of Information Technology Sri Shanmugha College of Engineering and Technology Salem India Department of Biomedical Engineering Sri Shanmugha College of Engineering and Technology Salem India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

Bio-electric signal like Electromyography (EMG) can measure signal data from nerves and muscles separately in the particular region of affected nerve or muscles from a Human Being. For incorporating these measurements, can use a non-invasive technique. The Surface electrode can be used for measuring these problems in non-invasive fashion. Here, the idea of internet of Things (IoT) can bring included advantage to applications with bio-electric signals to communicate to the doctors and patients such as human-PC cooperation by incorporating different advances for example, sensors, remote correspondence and information science. In this research, we worked on a remote bio-electric signals to another remote observing handling framework. A model with the contextual investigation of nerve and muscle signal acknowledgment utilizing 4-channel sEMG signals is executed. A Gaussian filter is prepared from one individual's sEMG signals with 4-nerve regions of human body such as ulnar, radial, median and radial. The introduced IoT application framework is actualized based on an 11-terminal bio-electric signal measuring device, with Arduino based Controller, Gateway, ESP8266 (Wifi) module, Server being the major mediums of remote transmission of signal data. The signal transmits at 35KB/s. In the framework, the ongoing sEMG signal from surface electrode is filtered from noise and other distortions using is given to the controller for performing the operation.

关键词： Performance evaluation Wires Estimation Muscles Electromyography Sensors internet of Things Servers Wireless fidelity Surface treatment

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Application of image Recognition Algorithms based on Deep Learning in the Field of Communication Science

Application of Image Recognition Algorithms Based on Deep Le...

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Integrated Intelligence and Communication systems (ICIICS), international conference on

作者： Yunxia Su Shanghai Publishing and Printing College Shanghai China

With the popularization of the internet, people have paid more and more attention to image processing, and deep learning has become a research hotspot. Analyzing images based on deep neural networks is a very valuable and promising direction for development. This article first introduced text representation methods and two commonly used classifiers in machine learning, namely the manual annotation model method. Then, it elaborated on the effectiveness and current application status of a fusion of multi-layer feedforward technology and convolutional neural networks for edge detection, feature extraction, and other fields. Finally, a new concept was proposed, and deep learning was applied to explain the important significance of image preprocessing in digital music file classification. Afterwards, a communication field training model based on image recognition algorithms was simulated and tested for its functionality. The test results showed that the image recognition algorithm based on deep learning had good noise processing performance during the propagation process, with an image clarity rate of over 90%. Through deep learning algorithms, automatic recognition and classification of radio signals can be achieved, including determining signal type, modulation method, frequency range, and other information. This is of great significance for radio spectrum monitoring, spectrum management, and interference source localization. By using deep learning algorithms, classification models for different types of radio signals can be trained, making the recognition of radio spectrum more accurate and reliable.

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A Deep Learning based-Convolutional Network Model for Wheat Leaf Disease Identification

A Deep Learning Based-Convolutional Network Model for Wheat ...

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Intelligent Cyber Physical systems and internet of Things (ICoICI), international conference on

作者： Somya Srivastav Kalpna Guleria Shagun Sharma Gurpreet Singh Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

Damage to cereal crops can be serious when this pathogenic fungus is present. Their cultural influences are diverse. Though it is difficult to eradicate an entire illness on a large scale, one effective technique is to monitor crop fields for signs of the disease so that preventative measures can be taken. Digital image analysis for disease identification, with the option to collect them in the field using handheld equipment, is an effective control strategy. Here, we present a technique that can detect wheat seedlings for five different fungal, either singly or in combination, and also predicts the disease stage. The proposed model has classified 1972 photos of wheat fungal illnesses into several databases. Unique disease labels are present in over 80% of the images in the collection (including seedlings), while over 13% have suggestions for healthy plants and 6% have labels for various ailments. This set was created using a method that used an image hashing algorithm to reduce the issue of training data homogeneity. An Efficient Net-the illness diagnosis algorithm utilizes based convolutional neural network. The most accurate networks were those that trained using image style augmentation and transfer (0.9897).

关键词： Deep learning Machine learning algorithms Databases Digital images Crops Training data Object recognition internet of Things Monitoring Diseases

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IoT based Localization and Tracking by Using MIMO Antenna technology

IoT Based Localization and Tracking by Using MIMO Antenna Te...

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international conference on signal Processing and Communication (ICSPC)

作者： P Prakash. G Manoj. Samson Immanuel.J ECE Department Karunya Institute of Technology and Sciences Coimbatore India

Multiple aspects of our life could benefit from the IoT. A component of the “connected house” is the internet of Things (IoT). All the programs below are the ones that need to be localized in some form. When applied to the first, IoT allows for the accurate localization of anything, even living creatures and humans. The second component tracks mobile targets such as toddlers and the elderly. When it comes to home safety and surveillance, smart homes offer features like geolocation and monitoring. A localization system is able to track almost anywhere or anything by combining information from multiple sources, such as wired and wireless networks. As time goes on, the internet of Things (IoT) becomes increasingly important and influences our daily lives in tangible ways. There is growing interest in the field of navigation IoT-based systems due to their widespread use in context-aware and localizationaware applications such as tracking, healthcare, and security. This subject has received a lot of attention as sensor technology and computational capacities improve. This study presents a brief overview of the localization techniques used by internet of Things-based indoor navigation systems at present.

关键词： Location awareness Bluetooth Target tracking Wireless networks Receiving antennas Adaptive arrays internet of Things

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