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Blockchain-based color medical image cryptosystem for industrial Internet of Healthcare Things (IoHT)

Multimedia Tools and Applications 2024年 1-55页

作者： Khallaf, Fatma El-Shafai, Walid El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Faculty of Engineering Ahram Canadian University 6th October City Giza Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

In recent years, the proliferation of smart devices and associated technologies, such as the Internet of Things (IoT), Industrial Internet of Things (IIoT), and Internet of Medical Things (IoMT), has witnessed a substantial growth. However, the limited processing power and storage capacity of smart devices make them vulnerable to cyberattacks, rendering traditional security and cryptography techniques inadequate. To address these challenges, blockchain (BC) technology has emerged as a promising solution. This study introduces an efficient framework for the Internet of Healthcare Things (IoHT), presenting a novel cryptosystem for color medical images using BC technology in conjunction with the IoT, Secure Hash Algorithm 256-bit (SHA256), shuffling, and bitwise XOR operations. The encryption scheme is specifically designed for an IIoT grid network computing system, relying on diffusion and confusion principles. In this paper, the proposed cryptosystem strength is evaluated against differential attacks with several comprehensive metrics. Simulation results and theoretical analysis demonstrate the cryptosystem effectiveness, showcasing its ability to provide high levels of security and immunity to data leakage. The proposed cryptosystem offers a versatile range of technical solutions and strategies that are adaptable to various scenarios. The evaluation metrics, with approximate values of 99.61% for Number of Pixels Change Rate (NPCR), 33.46% for Unified Average Changed Intensity (UACI), and 8 for information entropy, closely align with the desired ideal outcomes. Consequently, this paper contributes to the advancement of secure and private systems for medical image encryption based on BC technology, potentially mitigating the risks associated with cyberattacks on smart medical devices. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

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Advancing Stroke Prediction: Explainable Machine Learning Models and Data Augmentation Strategies 25

Advancing Stroke Prediction: Explainable Machine Learning Mo...

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25th International Arab Conference on information technology, ACIT 2024

作者： Salma, Rahma Abu Al-Qerem, Ahmad Iessa, Abedalhakeam Rajab, Mohammed Alauthman, Mohammad Jeadi, Mohammad Elrashidi, Ali Zarqa University Faculty of Information Technology Computer Science Department Zarqa13110 Jordan University Headquarter University of Anbar Ramadi Iraq University of Petra Department of Information Security Amman11196 Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

Stroke, a leading global disability cause, affects 12 million people annually, with 6.5 million dying. Preventing at least half of strokes requires public policy action and increased awareness. Early diagnosis is crucial and enhances patients' opportunities to survive a stroke. This research looks into how well machine learning (ML) models can predict when strokes will happen and how data augmentation affects those predictions.. Five ML models (Logistic Regression, Decision Tree, K-Nearest Neighbors, XGBoost, and Random Forest) are assessed and their performance is compared using an imbalanced and augmented dataset. Data augmentation techniques, including Random Oversampling, SMOTE, and Cluster Centroids, are employed to address class imbalance. The results demonstrate that some models achieve relatively high accuracy without data augmentation (XGBoost: 0.95). However, data augmentation techniques further improve performance across all models. Random Oversampling leads to the highest Accuracy for Random Forest (0.99), while SMOTE achieves the best Precision for Logistic Regression (1.00). The results found that age, occupation type, BMI, blood glucose level, and history of cardiovascular disease are risk factors for stroke. This study highlights the effectiveness of ML models, particularly when combined with data augmentation, for stroke prediction and emphasizes the importance of specific features in identifying stroke risk. © 2024 IEEE.

关键词： Logistic regression

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IoT Network Forensics based on Transport Layer

IoT Network Forensics based on Transport Layer

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2023 IEEE Conference on computer Applications, ICCA 2023

作者： Naing, Soe Kalayar Oo, Su Thet Oo, Hnin Wit Yi Lin, Phyo Yatanar Nwe, Khin Mya Thwin, Mie Mie Su University of Computer Studies Faculty of Computer Science Yangon Yangon Myanmar University of Computer Studies Yangon Yangon Myanmar University of Computer Studies Faculty of Computer System and Technology Yangon Yangon Myanmar University of Computer Studies Information Technology Support and Maintenance Yangon Yangon Myanmar University of Computer Studies Cyber Security Lab Yangon Yangon Myanmar

ISBN: (纸本)9781665435994

The IoT is concerned in every part of the human beings such as medical care, education, smart cities, home automation, and many business fields. While the IoT gives a myriad of benefits, security remains the biggest issues for using of many IoT applications in various environments. The emergence of new technologies in various fields also pose challenges in the field of forensic researches. It is said that Device Level forensics, Network Level forensics, and Cloud Level forensics are the three types of IoT forensics levels. Among them, Network Level forensics shows all kinds of communication networks that connected to IoT devices over the Internet. In this study, detecting and analyzing TCP-SYN flooding attacks and UDP flooding attacks based on Transport Layer (one type of DoS attacks), network forensics investigation over the traffics are presented. Capturing TCP-SYN flooding attacks and UDP flooding attacks and analyzing them with IO graphs by using Wireshark Network Analysis Tool is also described in this paper. © 2023 IEEE.

关键词： Floods

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CrossCert: A Privacy-Preserving Cross-Chain System for Educational Credential Verification Using Zero-Knowledge Proof 10th

CrossCert: A Privacy-Preserving Cross-Chain System for Educ...

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10th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2024

作者： Tran, Tuan-Dung Minh, Phong Khuu Thuy, Trang Le Tran Duy, Phan The Cam, Nguyen Tan Pham, Van-Hau Faculty of Computer Networks and Communications University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh City Viet Nam Information Security Laboratory University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9783031673566

Across various industries, credential verification stands as a critical requirement, yet traditional approaches face limitations in security, privacy, and interoperability. Although recent blockchain innovations promise decentralization, deploying them independently in institutions creates data isolation. While there are theoretical frameworks, lack of practical studies achieving a balance between credential mobility and privacy is noteworthy. This paper introduces CrossCert, a privacy-focused cross-chain system for verifying credentials between educational and employer blockchains. By incorporating zero-knowledge proofs, CrossCert facilitates anonymous checks without disclosing user details. Extensive experiments have consistently demonstrated CrossCert’s real-time performance, even within blockchain limitations. Its security features, including cryptographic proofs and on-chain data management, demonstrate strong resilience against typical attacks and web vulnerabilities. CrossCert pioneers bridging the research gap between education, employment, and privacy, striving to achieve a balanced balance of credential accessibility and ethical information practices with its innovative cross-chain architecture. The system hence merits further research as a feasible solution to streamline decentralized credential validation across diverse stakeholders. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Blockchain

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Reimagine Sentiments in Nature Language through Crystalize- Water Visualization 5

Reimagine Sentiments in Nature Language through Crystalize- ...

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5th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2024

作者： Png, Wen-Hao Chang, Fang-Yu Lo, Jie-Jin Hsu, Su-Chu Faculty of Information and Computer Technology Universiti Tunku Abdul Rahman Kampar Malaysia Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Institute of Information Security National Tsing Hua University Hsinchu Taiwan Research Center for Technology and Art National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9798331528553

Text art translates words into artworks through various mediums, including neon signage, light art, and hand- painted or drawn text. The visual representations focus on the typographical design and the ideas and meaning conveyed through human language. While sentiment analysis is a pivotal area of study in natural language processing (NLP) that aims to determine the sentiment expressed in text data with wide range of applications span various domains, including marketing, social media monitoring, and opinion mining. In this work, we reimagine the sentiments in nature language for artworks through a creative tandem composition of machine learning, physics, and art. By reframing the textual sentiment as virtual snow crystal fabrication, we created charming yet representative visualizations based on wide variety of cyber and literature texts, including classical poems and social network comments. The visualization aims to creatively generate text-based art and raise awareness of how sentiment in natural language can affect human emotion. © 2024 IEEE.

关键词： Sentiment analysis

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Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

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computers, Materials & Continua 2023年第3期74卷 5607-5623页

作者： Abdallah Elhigazi Abdallah Mosab Hamdan Shukor Abd Razak Fuad A.Ghalib Muzaffar Hamzah Suleman Khan Siddiq Ahmed Babikir Ali Mutaz H.H.Khairi Sayeed Salih Faculty of Engineering Future UniversityKhartoum 10553Sudan Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Information Assurance and Security Research School of ComputingUniversiti Teknologi MalaysiaJohor81310Malaysia School of Psychology and Computer Science University of Central LancashirePreston PR12HEUK Deaptement of Management Information Systems College of Administrative ScienceApplied Science UniversityAl Eker623Bahrain Deaptement of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11461Saudi Arabia

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 *** to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate ***,the security design of the wireless structure is vulnerable to versatile *** example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false *** security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world *** paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks *** proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the *** scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in *** proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related *** experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

关键词： 802.11 media access control(MAC) wireless local area network(WLAN) artificial neural network denial-of-service(DoS)

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Medichain: A Multi-chain Based System for Managing Prescription Medications Using Zero Knowledge Proofs

Medichain: A Multi-chain Based System for Managing Prescrip...

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International Conference on Intelligent Systems and Networks, ICISN 2024

作者： Tran, Tuan-Dung Duc, Minh Tran Thuy, Trang Le Tran Duy, Phan The Cam, Nguyen Tan Pham, Van-Hau Faculty of Computer Networks and Communications University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh City Viet Nam Information Security Laboratory University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9789819755035

The abuse of prescription medications has become a severe public health crisis fueled by limited coordination and oversight across healthcare systems. Current frameworks lack interoperability between doctors, pharmacies, and regulators, enabling abusive practices like doctor shopping and pharmacy hopping. To address these issues, this research proposes Medichain, a novel multichain-based system to establish end-to-end transparency and provenance tracking for prescription medications. Medichain creates an auditable, tamper-proof ledger interconnecting doctors, pharmacies, and governing bodies through a decentralized multi-chain architecture. Powered by zero-knowledge proof, Medichain verifies prescription details and tokenizes records as non-fungible assets without compromising patient privacy. Additionally, by enabling private verification of credentials, Medichain introduces decentralization, coordination, and access control absent from traditional centralized tracking systems. This approach is further emphasized through extensive experiments demonstrating the ability to uphold transparency while preserving confidentiality across heterogeneous entities. Medichain ultimately mitigates prescription misuse by reconstructing fractured supply chains into an interoperable ecosystem fortified by cryptographic accountability. Our solution not only balances coordination with ethical information handling but also merits further exploration of this privacy-first approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi-chain Non fungible token Prescription medications Privacy-preserving Zero knowledge proof

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Game Theory-Based IoT Efficient Power Control in Cognitive UAV

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computers, Materials & Continua 2022年第7期72卷 1561-1578页

作者： Fadhil Mukhlif Norafida Ithnin Omar B.Abdulghafoor Faiz Alotaibi Nourah Saad Alotaibi Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia Electronic and Telecommunication Department College of EngineeringThe American University of KurdistanIraq Faculty of Computer Science and Information Technology Universiti Putra MalaysiaSelangorMalaysia Computer Department Faculty of Applied CollegeImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia

With the help of network densification,network coverage as well as the throughput can be improved via ultra-dense networks(UDNs).In tandem,Unmanned Aerial Vehicle(UAV)communications have recently garnered much attention because of their high agility as well as widespread *** this paper,a cognitive UAV is proposed for wireless nodes power pertaining to the IoT ground ***,the UAV is included in the IoT system as the source of power for the wireless nodes as well as for resource *** quality of service(QoS)related to the cognitive node was considered as a utility function based on pricing scheme that was modelled as a non-cooperative game theory in order to maximise users’net utility ***,an energy efficiency non-cooperative game theory power allocation with pricing scheme(EE-NGPAP)is proposed to obtain an efficient power control within IoT wireless ***,uniqueness and existence of the Nash equilibrium have been demonstrated mathematically and through *** results show that the proposed energy harvest algorithm demonstrated considerable decrease in transmitted power consumption in terms of average power reduction,which is regarded to be apt with the 5Gnetworks’***,the proposed algorithm requires around 4 iterations only to converge to NE which makes the algorithm more suitable in practical heterogeneous scenarios.

关键词： UAV drones WSN IoT game theory energy efficiency 5G&B5G networks

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An Efficient Intrusion Detection Framework for Industrial Internet of Things security

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computer Systems Science & Engineering 2023年第7期46卷 819-834页

作者： Samah Alshathri Ayman El-Sayed Walid El-Shafai Ezz El-Din Hemdan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Recently,the Internet of Things(IoT)has been used in various applications such as manufacturing,transportation,agriculture,and healthcare that can enhance efficiency and productivity via an intelligent management console *** the increased use of Industrial IoT(IIoT)applications,the risk of brutal cyber-attacks also *** leads researchers worldwide to work on developing effective Intrusion Detection Systems(IDS)for IoT infrastructure against any malicious ***,this paper provides effective IDS to detect and classify unpredicted and unpredictable severe attacks in contradiction to the IoT infrastructure.A comprehensive evaluation examined on a new available benchmark TON_IoT dataset is *** data-driven IoT/IIoT dataset incorporates a label feature indicating classes of normal and attack-targeting IoT/IIoT ***,this data involves IoT/IIoT services-based telemetry data that involves operating systems logs and IoT-based traffic networks collected from a realistic medium-scale IoT *** is to classify and recognize the intrusion activity and provide the intrusion detection objectives in IoT environments in an efficient ***,several machine learning algorithms such as Logistic Regression(LR),Linear Discriminant Analysis(LDA),K-Nearest Neighbors(KNN),Gaussian Naive Bayes(NB),Classification and Regression Tree(CART),Random Forest(RF),and AdaBoost(AB)are used for the detection intent on thirteen different intrusion *** performance metrics like accuracy,precision,recall,and F1-score are used to estimate the proposed *** experimental results show that the CART surpasses the other algorithms with the highest accuracy values like 0.97,1.00,0.99,0.99,1.00,1.00,and 1.00 for effectively detecting the intrusion activities on the IoT/IIoT infrastructure on most of the employed *** addition,the proposed work accomplishes high performance compared to other recent rela

关键词： Attacks intrusion detection machine learning deep learning industrial IoT TON_IoT dataset

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Simulating a Finite-State Markov Chain for Rayleigh Block-Fading Channel based on its Mathematical Model, and Practical Representation 25

Simulating a Finite-State Markov Chain for Rayleigh Block-Fa...

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25th International Arab Conference on information technology, ACIT 2024

作者： Attar, Hani Ababneh, Jafar Al-Hihi, Mohammad Rachini, Ali Solyman, Ahmed Zarqa University Faculty of Engineering Zarqa Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Zarqa University Faculty of Information Technology Cyber Security Department Zarqa Jordan Erlangen Germany Department of Computer Science and Information Technology Jounieh Lebanon Glasgow Caledonian University School of Computing Engineering and Built Environment Glasgow United Kingdom

ISBN: (纸本)9798331540012

In the proposed paper, simulating the Finite State Markov Chain (FSMC) to be implemented as Rayleigh Block-fading channel. Indeed, FSMC is regarded as a practical fading channel because of its random choice for future transmission probability. Accordingly, this paper introduces the FSMC technology with the theoretical limits and equations;moreover, the uplink and downlink Rayleigh Block-fading channel scenarios are also investigated and supported by the simulation set-up. The results for the Rayleigh fading channel for the Long-Term Evaluation-Advanced network were obtained as an example of the channel's attitude. The findings demonstrate that FSMC provides such reliable results and is suitable for use as a practical fading channel, particularly in terms of burst error behavior. © 2024 IEEE.

关键词： Markov chains

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