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Robust pixel-level image encryption algorithm using 3D infinite collapse coupling map

Multimedia Tools and Applications 2025年 1-24页

作者： Song, Okchol Pak, Chanil Jong, Cholmin Erkan, Ugur Ri, Myongsong Institute of Information Technology Kim Chaek University of Technology Sungri Street Asia Pyongyang950003 Korea People's Democratic Rep Department of Computer Engineering Karamanoglu Mehmetbey University Karaman70200 Turkey

Chaotic map, due to its excellent unpredictability and complexity, is widely used in various fields, such as information security, information communication, and system control, etc., thus research work is being intensified to improve its chaotic characteristics. In this work, based on the published literatures, we proposed a noble 3D-ICCM (3D Infinite Collapse Coupling Map) by combining three 1D infinite collapse maps, so as to improve its chaotic performance and evaluated its chaotic characteristics. As can be seen from the bifurcation characteristic diagram from experiments, the distribution is very uniform and Lyapunov exponent has an average value of 2.5 over the whole chaotic characteristic range, and the information entropy also has a value of over 7.99. In addition, it has a value of over 0.1 for all 15 test parameters of NIST (National institute of Standards and technology) statistical tests. This demonstrates that the proposed 3D-ICCM is completely random, and has better chaotic properties than the previous 3D maps, especially the 3D-ICM (3D Infinite Collapse Map). In addition, in order to validate applicability of the proposed 3D-ICCM to image encryption, simple-structured pixel-level image encryption algorithm with our 3D-ICCM is designed and its robustness is verified through experiments. The experimental results convinced that the proposed image encryption algorithm has a sufficient key sensitivity and super ability to resist differential, Chosen-plaintext, cropping and noise attacks. The experimental results are fully uncovered in tables and images in this paper. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Encryption algorithms

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OCSO-CA:opposition based competitive swarm optimizer in energy efficient IoT clustering

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Frontiers of computer Science 2022年第1期16卷 77-87页

作者： Arpita BISWAS Abhishek MAJUMDAR Soumyabrata DAS Krishna Lal BAISHNAB Department of Electronics and Communication Engineering National Institute of Technology SilcharSilchar788010India Department of Computer Science&Engineering Karunya Institute of Technology&SciencesCoimbatore641114India Department of Electrical Engineering National Institute of Technology SilcharSilchar788010India

With the advent of modern technologies,IoT has become an alluring field of *** IoT connects everything to the network and transmits big data frequently,it can face issues regarding a large amount of energy *** this respect,this paper mainly focuses on reducing the energy loss problem and designing an energy-efficient data transfer scenario between IoT devices and ***,a layered architectural framework for IoT-cloud transmission has been proposed that endorses the improvement in energy efficiency,network lifetime and ***,an Opposition based Competitive Swarm Optimizer oriented clustering approach named OCSO-CA has been proposed to get the optimal set of clusters in the IoT device *** proposed strategy will help in managing intra-cluster and inter-cluster data communications in an energy-efficient ***,a comparative analysis of the proposed approach with the state-of-the-art optimization algorithms for clustering has been performed.

关键词： competitive swarm optimization cloud computing clustering IoT

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Blockchain based E-Voting System on Smartphones 7

Blockchain based E-Voting System on Smartphones

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7th IEEE Pune Section International Conference, PuneCon 2024

作者： Pillai, Sandeep Lahamage, Darshan Gurav, Shreya Ambawade, Dayanand Sardar Patel Institute of Technology Department of Electronics & Telecommunication Mumbai India Sardar Patel Institute of Technology Department of Computer Science & Engineering Mumbai India

ISBN: (纸本)9798331527822

India, the world's largest democracy, faces significant challenges in conducting free and fair elections due to the prevalence of vote tampering, booth capturing, and rigging. To address and solve these challenges, a blockchain-based e-voting system will be developed that is secure, transparent, and accessible to all eligible voters in India. The decentralized nature of blockchain, combined with the transparency and security of smart contracts written in Solidity, will ensure that the voting process is tamper-proof and transparent. The system will be developed and tested on Ethereum testnet, and the complexity of existing systems will be simplified into a simple smartphone application that can be accessed by all eligible voters in India. The system will remove dependency on crypto wallets like Meta-mask, the backend api's are developed using ***, *** and ***. SHA-3 will be used for hashing and encryption purposes. The frontend will be developed using React Native, ensuring a user-friendly and accessible interface. The successful implementation of this blockchain-based e-voting system could revolutionize the democratic process in India, making it more accessible, secure, and transparent, and setting an example for other countries to follow. © 2024 IEEE.

关键词： Ethereum

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Evaluation of CatBoost for Diabetes Prevention in Comparison to XGBoost: To avert mortality by developing an AI model capable of predicting the onset of diabetes

Evaluation of CatBoost for Diabetes Prevention in Comparison...

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2024 IEEE International Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Gifta Jerith, G. Jagadeesh, S. Ponmathi Jeba Kiruba, P. Mahesh, C. Anantha Babu, S. Samsudeen Shaffi, S. Hyderabad India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Saveetha Engineering College Department of Computer Science and Engineering Chennai India Panimalar Engineering College Department of Information Technology Chennai India GITAM University GITAM School of Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331522988

Diabetes is a metabolic condition defined by consistently elevated blood glucose levels. Hyperglycemia is characterized by heightened hunger, thirst, and urination. Numerous consequences may arise from untreated diabetes. Diabetic ketoacidosis, hyperosmolarity, hyperglycemia, and even mortality may occur as acute consequences. Heart disease, stroke, chronic renal failure, foot ulcers, and eye impairment are some of the worst long-term consequences. A total of 463 million individuals were found to have diabetes in 2019, according to the worldwide diabetes organisation. Assuming predictions come true, that number will soar to 700 million by 2045, up 578 million by 2030. It has modern medical applications, allowing for the rapid and precise diagnosis of illness. Thus, we may use machine learning to avert mortality by developing an AI model capable of predicting the onset of diabetes;to determine which algorithm is most suited for this task, we will compare the CatBoost and XGBoost methods. In the end, the research compared two diabetes prediction models, XGBoost and CatBoost, using a variety of health indicators from the dataset. Using a real-world dataset obtained from Kaggle, our suggested system is trained and built using Python. Performance assessment criteria such as precision, recall, F1score and accuracy measurements are used to thoroughly analyse our methods. In comparison to XGBoost's 88.33% accuracy rate, 85.25 percent precision, 85.63 percent recall, and an F1 Score of 86.50. CatBoost's 91.08% percent accuracy, 85.25 percent precision, 85.63 percent recall, and 87.38 F1 Score. CatBoost marks it as the most successful ensemble approach. © 2024 IEEE.

关键词： Prediction models

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User Experience and Usability Challenges in E-Tourism: Bangladesh Perspective 23th

User Experience and Usability Challenges in E-Tourism: Ban...

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

作者： Hossain, Md Zahid Zaman, Syed Rohit Islam, Muhammad Nazrul Department of Computer Science and Engineering Military Institute of Science and Technology Mirpur Cantonment Dhaka1216 Bangladesh

ISBN: (纸本)9783031647789

Usability plays a critical role in ensuring the efficient delivery of services on e-tourism websites, particularly for travelers in developing countries. This study’s objectives aim to assess the current usability status of e-tourism websites, focusing on prominent tourist destinations in a developing nation. Through a heuristic evaluation of three randomly selected mostly used e-tourism websites (Discovery Bangladesh, Beautiful Bangladesh, and Travel BD) in Bangladesh, this research has revealed 23 usability problems across the selected websites. These usability issues encompass aspects such as system status visibility, flexibility, efficiency of use, consistency, adherence to standards, alignment with real-world usage, and user control. Some usability problems are characterized by high severity ratings, with the majority falling within the 2.5 to 3.5 range on a 0 to 4 scale. Among the selected websites, Discovery Bangladesh website showed the maximum number of problems, while the problems found in Travel BD website showed the highest average severity. As such, the outcomes of this research highlight that addressing the revealed usability concerns is crucial to enhance user experiences, attract more tourists, promote sustainable tourism growth of such context. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Developing countries

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Memristive effects on an improved discrete Rulkov neuron model

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Science China(Technological Sciences) 2023年第11期66卷 3153-3163页

作者： BAO Han LI KeXin MA Jun HUA ZhongYun XU Quan BAO BoCheng School of Microelectronics and Control Engineering Changzhou UniversityChangzhou 213159China Department of Physics Lanzhou University of TechnologyLanzhou 730050China School of Computer Science and Technology Harbin Institute of TechnologyShenzhenShenzhen 518055China

A change in neuronal-action potential can generate a magnetically induced current during the release and propagation of intracellular *** better characterize the electromagnetic-induction effect,this paper presents an improved discrete Rulkov(ID-Rulkov)neuron model by coupling a discrete model of a memristor with sine memductance into a discrete Rulkov neuron *** ID-Rulkov neuron model possesses infinite invariant points,and its memristor-induced stability effect is evaluated by detecting the routes of period-doubling and Neimark-Sacker *** investigated the memristor-induced dynamic effects on the neuron model using bifurcation plots and firing ***,we theoretically expounded the memristor initial-boosting mechanism of infinite coexisting *** results show that the ID-Rulkov neuron model can realize diverse neuron firing patterns and produce hyperchaotic attractors that are nondestructively boosted by the initial value of the memristor,indicating that the introduced memristor greatly benefits the original neuron *** hyperchaotic attractors initially boosted by the memristor were verified by hardware experiments based on a hardware *** addition,pseudorandom number generators are designed using the ID-Rulkov neuron model,and their high randomness is demonstrated based onstrict test results.

关键词： neuron model invariant point memristive effect complex dynamics pseudorandom number generators

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Paillier Cryptography Based Message Authentication Code for IoMT Security

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computer Systems Science & engineering 2023年第3期44卷 2209-2223页

作者： S.Siamala Devi Chandrakala Kuruba Yunyoung Nam Mohamed Abouhawwash Department of Computer Science and Engineering Sri Krishna College of TechnologyCoimbatore641042India Department of Computer Science and Engineering Vignan Nirula Institute of Technology and ScienceGuntur522009India Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Health care visualization through Internet of Things(IoT)over wireless sensor network(WSN)becomes a current research attention due to medical sensor evolution of *** digital technology-based communication system is widely used in all *** of medical thing(IoMT)assisted health-care application ensures the continuous health monitoring of a patient and provides the early awareness of the one who is suffered without human *** smart medical devices may consume with limited resources and also the data generated by these devices are large in *** IoMT based applications suffer from the issues such as security,anonymity,privacy,and *** overcome these issues,data aggregation methods are the solution that can concatenate the data generated by the sensors and forward it into the base station through fog node with efficient encryption and *** article proposed a well-organized data aggregation and secured transmission *** data generated by the sensor are collected and *** nodes(AN)received the compressed data and concatenate *** concatenated and encrypted data is forward to fog node using the enhanced Paillier cryptogra-phy-based encryption with Message Authentication code(MAC).Fog node extracts the forwarded data from AN using Fog message extractor method(FME)with *** proposed system ensures data integrity,security and also protects from security *** proposed model is simulated in Net-work Simulator 2.35 and the evaluated simulation results proves that the aggregation with MAC code will ensures the security,privacy and also reduces the communication *** node usages in between Aggregator and base station,will reduce the cloud server/base station computational overhead and storage *** proposed ideology is compared with existing data aggregation schemes in terms of computational cost,storage cost,communication cost and energy *** of communica

关键词： Fog IoMT wireless sensor network cloud aggregation encryption decryption energy

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A Secure Fingerprint Transmission Protocol for Insecure Communication Channels 1

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2nd International Conference on Intelligent Computing Systems and Applications, ICICSA 2023

作者： Singh, Laiphrakpam Dolendro Arshad Ahmed, Md. Louis, Teresa Ali, Azad Thounaojam, Dalton Meitei Patgiri, Ripon Singh, Khoirom Motilal Department of Computer Science and Engineering National Institute of Technology Silchar Silchar India Department of CSE Indian Institute of Information Technology Manipur Senapati India

ISBN: (数字)9789819754120

ISBN: (纸本)9789819754113

A fingerprint is a recognizable pattern of ridges and valleys on a person’s finger surface. A person’s fingerprints are distinct and unchangeable throughout a person’s life unless distorted through external injury. The fingerprint is one of the most commonly utilized biometric identification techniques. As fingerprints are used in realistic authentication, securing fingerprints is a paramount concern. Moreover, enciphering the whole fingerprint image collected through a fingerprint scanner would require extensive computation. Research has shown that minutiae points are used to determine the uniqueness of a fingerprint. A method is proposed to store and transmit fingerprint data securely. The proposed technique enciphers only the internal angles subtended by the relevant minutiae points and the information about the type of minutiae points. The proposed techniques reduce the computation involved as only the internal angles information and type of minutiae points are enciphered rather than the whole scanned fingerprint image. Statistical and security analyses conducted on the cipher data suggest the proposed encryption is secure. A digital signature is incorporated while transmitting the fingerprint information, thereby maintaining the data integrity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Authentication Protocol

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Blood Cell Classification and Counting in Hematology through Deep Learning 4

Blood Cell Classification and Counting in Hematology through...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Ananthi, P. Devi, K. Nirmala Ramya, T.E. Shanmugapriya, P. Aradhya, T. Kongu Engineering College Department of Computer Technology Perundurai Tamil Nadu Erode India Madanapalle Institute of Technology & Science Department of Computer Applications India Kongu Engineering College Perundurai Tamil Nadu Erode India

ISBN: (纸本)9798331540364

Medical diagnosis is one of the areas that has been greatly influenced by the progress of computer vision technologies. This study presents a unique approach for the detection and counting of blood cells in hematology: You Only Look One algorithm version 7 (YOLOv7). YOLO is designed for real-time object detection, making it ideal for applications such as blood vessel detection where speed is critical. The architecture allows the model to process images faster than other recognition models, such as R-CNN or SSD, which is very important for situations that require fast results, such as analysis automatic blood at clinical sites. The purpose of the proposed method is to overcome the shortcomings of conventional methods and to accurately and quickly identify blood cells in mechanical images. The YOLOv7 model has been utilizedbecause it can detect objects in real-time with highprecision and speed. The methodology for bloodcell counting involves the use of YOLOv7 togenerate bounding boxes around each detectedblood cell in an image, where the count of these bounding boxes directly corresponds to the number of cells. This advancement in hematology not onlyimproves blood cell analysis efficiency but also expedites the process of diagnosing and planningtreatment in various medical situations. This paper details how YOLOv7 was modified and adjusted to meet the specific requirements of hematologicalimage analysis, including training models, preparing datasets, and evaluating performance. The study also addresses the potential impact of this technology on clinical workflows, highlightinghow it might help medical practitioners make decisions more quickly and intelligently. Hematology analysis systems including YOLOv7 are able to improve laboratory diagnostics and help patients by providing better care and results. This workconcludes by demonstrating the revolutionary potential of YOLOv7 in blood cell identificationand counting in hematology, paving the way for accurate and better

关键词： Diagnosis

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A Bilateral Assessment of Human Activities Using PSO-Based Feature Optimization and Non-linear Multi-task Least Squares Twin Support Vector Machine

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SN computer Science 2024年第3期5卷 1-18页

作者： Thakur, Ujwala Vidyarthi, Ankit Prajapati, Amarjeet Department of Computer Science Engineering and Information Technology Jaypee Institute of Information Technology Noida Sector-62 Uttar Pradesh Noida 201309 India

Human activity recognition (HAR) is an essential part of many applications, including smart surroundings, sports analysis, and healthcare. Accurately categorizing intricate actions from sensor data is still difficult, though. This method infers an individual’s actions using a variety of sensor data, including magnetometers, gyroscopes, and accelerometers. This work suggests a unique method for classifying human activities by combining a non-linear multi-task least squares twin support vector machine (NMtLSSVM) with particle swarm optimization (PSO) for feature optimization. Utilizing the advantages of both approaches, the suggested strategy achieves excellent resilience and accuracy in activity identification. The suggested method reduces dimensionality and computing costs while maintaining pertinent information using PSO to extract the most important features from the raw sensor data. On the other hand, NMtLSSVM is used to construct a multi-task learning framework that learns several related tasks at the same time and shares information among them. As a result, generalization and resilience can be enhanced beyond single-task models. Two datasets that are available to the public, WISDM, and UCI-HAR, were used to assess the suggested method. The testing findings show that the suggested approach works noticeably better than the most advanced techniques already in use. Overall activities, the outcome achieves an average classification accuracy of 97.8% (UCI-HAR dataset) and 98.5% (WISDM dataset). Furthermore, the PSO-based feature optimization decreased the feature count by 60% without sacrificing efficiency. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Human action recognition Intelligent computing Machine learning classification Performance comparison Sensory data analysis

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