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An IoMT image crypto-system based on spatial watermarking and asymmetric encryption

Multimedia Tools and Applications 2024年第39期83卷 86681-86706页

作者： Kahla, Mohammed El Habib Beggas, Mounir Laouid, Abdelkader AlShaikh, Muath Hammoudeh, Mohammad LIAP Laboratory University of El Oued PO Box 789 El Oued39000 Algeria Computer science department college of Computing and Informatics Saudi Electronic University Abi Bakr As Siddiq Rd Ar Rabi Riyadh11673 Saudi Arabia Information & amp Computer Science Department King Fahd University of Petroleum & ampMinerals Academic Belt Road Dhahran31261 Saudi Arabia

In the growing field of the Internet of Medical Things (IoMT), securing the transmission of medical images over public networks is a critical challenge. Medical images, being highly sensitive and often containing personally identifiable information, require robust protection against unauthorized access and tampering. This paper addresses this challenge by introducing a novel cryptosystem specifically tailored to the resource limitations inherent in IoMT environments. To meet the demand for protecting sensitive information in medical images, the proposed system integrates two layers of security: spatial watermarking and asymmetric encryption. At the core of our approach lies a newly developed, cost-effective spatial watermarking algorithm that seamlessly embeds watermarks within host images to facilitate tamper detection. Complementing this, we employ a resource-efficient Twin Message Fusion (TMF) encryption scheme to ensure confidentiality and integrity during transmission. The proposed cryptosystem is evaluated for both watermarking effectiveness and encryption robustness. Additionally, we assess the system’s suitability for IoMT environments in terms of cost-effectiveness. Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) metrics have been used to assess watermarking resilience against various attacks, while encryption efficacy is analyzed through histogram and entropy evaluations. Furthermore, we compare the complexity of our cryptosystem with five recently proposed techniques in both traditional and IoMT environments, demonstrating superior execution time, reduced image size, and enhanced encryption efficiency. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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Model Sensitivity Aware Continual Learning 38

Model Sensitivity Aware Continual Learning

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wang, Zhenyi Huang, Heng Department of Computer Science Institute of Health Computing University of Maryland College Park College ParkMD20742 United States

Continual learning (CL) aims to adapt to non-stationary data distributions while retaining previously acquired knowledge. However, CL models typically face a trade-off between preserving old task knowledge and excelling in new task performance. Existing approaches often sacrifice one for the other. To overcome this limitation, orthogonal to existing approaches, we propose a novel perspective that views the CL model ability in preserving old knowledge and performing well in new task as a matter of model sensitivity to parameter updates. Excessive parameter sensitivity can lead to two drawbacks: (1) significant forgetting of previous knowledge;and (2) overfitting to new tasks. To reduce parameter sensitivity, we optimize the model's performance based on the parameter distribution, which achieves the worst-case CL performance within a distribution neighborhood. This innovative learning paradigm offers dual benefits: (1) reduced forgetting of old knowledge by mitigating drastic changes in model predictions under small parameter updates;and (2) enhanced new task performance by preventing overfitting to new tasks. Consequently, our method achieves superior ability in retaining old knowledge and achieving excellent new task performance simultaneously. Importantly, our approach is compatible with existing CL methodologies, allowing seamless integration while delivering significant improvements in effectiveness, efficiency, and versatility with both theoretical and empirical supports. © 2024 Neural information processing systems foundation. All rights reserved.

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Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling 38

Provably Faster Algorithms for Bilevel Optimization via With...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Li, Junyi Huang, Heng Department of Computer Science Institute of Health Computing University of Maryland College Park College ParkMD20742 United States

Bilevel Optimization has experienced significant advancements recently with the introduction of new efficient algorithms. Mirroring the success in single-level optimization, stochastic gradient-based algorithms are widely used in bilevel optimization. However, a common limitation in these algorithms is the presumption of independent sampling, which can lead to increased computational costs due to the complicated hyper-gradient formulation of bilevel problems. To address this challenge, we study the example-selection strategy for bilevel optimization in this work. More specifically, we introduce a without-replacement sampling based algorithm which achieves a faster convergence rate compared to its counterparts that rely on independent sampling. Beyond the standard bilevel optimization formulation, we extend our discussion to conditional bilevel optimization and also two special cases: minimax and compositional optimization. Finally, we validate our algorithms over both synthetic and real-world applications. Numerical results clearly showcase the superiority of our algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

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International Journal of Advanced computer science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (science and Information Organization). All rights reserved.

关键词： Quantum cryptography

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Robust Reinforcement Learning with General Utility 38

Robust Reinforcement Learning with General Utility

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Ziyi Wen, Yan Hu, Zhengmian Huang, Heng Department of Computer Science Institute of Health Computing University of Maryland College Park College ParkMD20742 United States

Reinforcement Learning (RL) problem with general utility is a powerful decision making framework that covers standard RL with cumulative cost, exploration problems, and demonstration learning. Existing works on RL with general utility do not consider the robustness under environmental perturbation, which is important to adapt RL system in the real-world environment that differs from the training environment. To train a robust policy, we propose a robust RL framework with general utility, which subsumes many existing RL frameworks including RL, robust RL, RL with general utility, constrained RL, robust constrained RL, pure exploration, robust entropy regularized RL, etc. Then we focus on popular convex utility functions, with which our proposed learning framework is a challenging nonconvex-nonconcave minimax optimization problem, and design a two-phase stochastic policy gradient type algorithm and obtain its sample complexity result for gradient convergence. Furthermore, for convex utility on a widely used polyhedral ambiguity set, we design an algorithm and obtain its convergence rate to a global optimal solution. © 2024 Neural information processing systems foundation. All rights reserved.

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Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

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Intelligent Automation & Soft computing 2023年第5期36卷 1915-1930页

作者： Rab Nawaz Bashir Imran Sarwar Bajwa Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel ABahaddad Khalid Ali Almarhabi Department of Computer Science COMSATS University IslamabadVehari CampusPakistan Department of Computer Science and IT Islamia University BahawalpurPakistan Department of Software Engineering Superior University Lahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be deﬁned by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.

关键词： Leaching fraction saline soil evapotranspiration machine learning calibrated evapotranspiration artiﬁcial intelligence blaney criddle method

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Towards characterizing bug fixes through dependency-level changes in Apache Java open source projects

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science China(Information sciences) 2022年第7期65卷 102-120页

作者： Di CUI Lingling FAN Sen CHEN Yuanfang CAI Qinghua ZHENG Yang LIU Ting LIU School of Computer Science and Technology Xi'an Jiaotong University College of Cyber Science Nankai University College of Intelligence and Computing Tianjin University Department of Computer Science Drexel University School of Computer Science and Engineering Nanyang Technological University School of Cyber Science and Engineering Xi'an Jiaotong University

The complexity and diversity of bug fixes require developers to understand bug fixes from multiple perspectives in addition to fine-grained code changes. The dependencies among files in a software system are an important dimension to inform software quality. Recent studies have revealed that most bug-prone files are always architecturally connected with dependencies, and as one of the best practices in the industry,changes in dependencies should be avoided or carefully made during bug fixing. Hence, in this paper, we take the first attempt to understand bug fixes from the dependencies perspective, which can complement existing code change perspectives. Based on this new perspective, we conducted a systematic and comprehensive study on bug fixes collected from 157 Apache open source projects, involving 140456 bug reports and182621 bug fixes in total. Our study results show that a relatively high proportion of bug fixes(30%) introduce dependency-level changes when fixing the corresponding 33% bugs. The bugs, whose fixes introduce dependency-level changes, have a strong correlation with high priority, large fixing churn, long fixing time,frequent bug reopening, and bug inducing. More importantly, patched files with dependency-level changes in their fixes, consume much more maintenance costs compared with those without these changes. We further summarized three representative patch patterns to explain the reasons for the increasing costs. Our study unveils useful findings based on qualitative and quantitative analysis and also provides new insights that might benefit existing bug prediction techniques. We release a large set of benchmarks and also implement a prototype tool to automatically detect dependency-level changes from bug fixes, which can warn developers and remind them to design a better fix.

关键词： empirical software engineering software maintenance software evolution software architecture software design

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Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

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computers, Materials & Continua 2024年第11期81卷 2357-2394页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Razaz Waheeb Attar Farman Ali Ahmed Alhomoud Babar Shah School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science College of ScienceNorthern Border UniversityArar91431Saudi Arabia College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates

Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely *** the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power *** optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in *** paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in *** energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient *** link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of *** simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing *** evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.

关键词： FANET UAV internet of UAVs relay mechanism energy consumption routing IEE-DLSA

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SwinVid:Enhancing Video Object Detection Using Swin Transformer

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computer Systems science & Engineering 2024年第2期48卷 305-320页

作者： Abdelrahman Maharek Amr Abozeid Rasha Orban Kamal ElDahshan Computer Science Department Faculty of Artificial Intelligence and InformaticsBenhaEgypt Mathematics Department Faculty of SciencesAl-Azhar UniversityCairoEgypt Department of Computer Science College of Science and Arts in QurayyatJouf UniversitySakakaSaudi Arabia

What causes object detection in video to be less accurate than it is in still images?Because some video frames have degraded in appearance from fast movement,out-of-focus camera shots,and changes in *** reasons have made video object detection(VID)a growing area of research in recent *** object detection can be used for various healthcare applications,such as detecting and tracking tumors in medical imaging,monitoring the movement of patients in hospitals and long-term care facilities,and analyzing videos of surgeries to improve technique and ***,it can be used in telemedicine to help diagnose and monitor patients *** VID techniques are based on recurrent neural networks or optical flow for feature aggregation to produce reliable features which can be used for *** of those methods aggregate features on the full-sequence level or from nearby *** create feature maps,existing VID techniques frequently use Convolutional Neural Networks(CNNs)as the backbone *** the other hand,Vision Transformers have outperformed CNNs in various vision tasks,including object detection in still images and image *** propose in this research to use Swin-Transformer,a state-of-the-art Vision Transformer,as an alternative to CNN-based backbone networks for object detection in *** proposed architecture enhances the accuracy of existing VID *** ImageNet VID and EPIC KITCHENS datasets are used to evaluate the suggested *** have demonstrated that our proposed method is efficient by achieving 84.3%mean average precision(mAP)on ImageNet VID using less memory in comparison to other leading VID *** source code is available on the website https://***/amaharek/SwinVid.

关键词： Video object detection vision transformers convolutional neural networks deep learning

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Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

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computer Modeling in Engineering & sciences 2024年第4期139卷 633-659页

作者： Nadeem Ahmed Khalid Mohammadani Ali Kashif Bashir Marwan Omar Angel Jones Fayaz Hassan School of Electronic Science Beijing University of Post and TelecommunicationBeijing100086China Department of Computer Science Huanggang Normal UniversityHuanggangChina Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabad502345India Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Information Technology and Management Illinois Institute of TechnologyChicagoUSA College of Computing Capital Technology UniversityLaurelUSA

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes *** the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against *** additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network *** testing of our solution has revealed its remarkable ability to enhance communication in ***,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and *** results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

关键词： Black hole attack IoV vehicular ad hoc network AODV routing protocol

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