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A Barrier-Based Machine Learning Approach for Intrusion Detection in Wireless Sensor Networks

computers, Materials & Continua 2025年第3期82卷 4181-4218页

作者： Haydar Abdulameer Marhoon Rafid Sagban Atheer Y.Oudah Saadaldeen Rashid Ahmed Information and Communication Technology Research Group Scientific Research CenterAl-Ayen UniversityThi-Qar64011Iraq College of Computer Sciences and Information Technology University of KerbalaKarbala56001Iraq Enginerring Technical College Al-Ayen UniversityThi-Qar64011Iraq Information Technology College University of BabylonHilla51002Iraq Department of Computer Science College of Education for Pure ScienceUniversity ofThi-QarNasiriyah64001Iraq Artificial Intelligence Engineering Department College of EngineeringAl-Ayen UniversityThi-Qar64001Iraq Department of Computer Science Bayan UniversityErbilKurdistan44001Iraq

In order to address the critical security challenges inherent to Wireless Sensor Networks(WSNs),this paper presents a groundbreaking barrier-based machine learning *** applications like military operations,healthcare monitoring,and environmental surveillance increasingly deploy WSNs,recognizing the critical importance of effective intrusion detection in protecting sensitive data and maintaining operational *** proposed method innovatively partitions the network into logical segments or virtual barriers,allowing for targeted monitoring and data collection that aligns with specific traffic *** approach not only improves the *** are more types of data in the training set,and this method uses more advanced machine learning models,like Convolutional Neural Networks(CNNs)and Long Short-Term Memory(LSTM)networks together,to see coIn our work,we used five different types of machine learning *** are the forward artificial neural network(ANN),the CNN-LSTM hybrid models,the LR meta-model for linear regression,the Extreme Gradient Boosting(XGB)regression,and the ensemble *** implemented Random Forest(RF),Gradient Boosting,and XGBoost as baseline *** train and evaluate the five models,we used four possible features:the size of the circular area,the sensing range,the communication range,and the number of sensors for both Gaussian and uniform sensor *** used Monte Carlo simulations to extract these *** on the comparison,the CNN-LSTM model with Gaussian distribution performs best,with an R-squared value of 99%and Root mean square error(RMSE)of 6.36%,outperforming all the other models.

关键词： Intrusion detection system(IDS) hybrid models of CNN-LSTM WSN extreme gradient boosting(XGBoost)regressor ensemble model

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Design and Implementation of a Following Vehicle Based on ROS and UWB 7

Design and Implementation of a Following Vehicle Based on RO...

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7th International Conference on Automation, Control and Robots, ICACR 2023

作者： Yu, Yun-Shuai Chen, Chin-Wei National Formosa University Department of Computer Science and Information Engineering Yunlin Taiwan Software Research & Development Center New Taipei City Taiwan

ISBN: (纸本)9798350302882

Autonomous vehicle technology has gained significant attention in various industries recently. This paper presents the design and implementation of a following vehicle that utilizes the Robot Operating System (ROS) and Ultra-Wideband (UWB) RF transceiver modules to achieve precise target localization, map the surrounding environment, and navigate accordingly. A mobile application has also been developed to track the following vehicle's position. © 2023 IEEE.

关键词： Radio transceivers

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On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods 38

On Partial Optimal Transport: Revising the Infeasibility of ...

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38th AAAI Conference on Artificial Intelligence, AAAI 2024

作者： Nguyen, Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Toh, Kim-Chuan Department of Mathematics National University of Singapore Singapore Department of Computer and Information Science University of Pennsylvania United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States School of Industrial and Systems Engineering Georgia Institute of Technology United States IBM Research Thomas J. Watson Research Center United States Institute of Operations Research and Analytics National University of Singapore Singapore

ISBN: (纸本)1577358872

This paper studies the Partial Optimal Transport (POT) problem between two unbalanced measures with at most n supports and its applications in various AI tasks such as color transfer or domain adaptation. There is hence a need for fast approximations of POT with increasingly large problem sizes in arising applications. We first theoretically and experimentally investigate the infeasibility of the state-of-the-art Sinkhorn algorithm for POT, which consequently degrades its qualitative performance in real world applications like point-cloud registration. To this end, we propose a novel rounding algorithm for POT, and then provide a feasible Sinkhorn procedure with a revised computation complexity of Oe(n2/Ε4). Our rounding algorithm also permits the development of two first-order methods to approximate the POT problem. The first algorithm, Adaptive Primal-Dual Accelerated Gradient Descent (APDAGD), finds an Ε-approximate solution to the POT problem in Oe(n2.5/Ε). The second method, Dual Extrapolation, achieves the computation complexity of Oe(n2/Ε), thereby being the best in the literature. We further demonstrate the flexibility of POT compared to standard OT as well as the practicality of our algorithms on real applications where two marginal distributions are unbalanced. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Gradient methods

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Secure key-alternating Feistel ciphers without key schedule

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science China(Information sciences) 2021年第1期64卷 251-253页

作者： Yaobin SHEN Hailun YAN Lei WANG Xuejia LAI Department of Computer Science and Engineering Shanghai Jiao Tong University Westone Cryptologic Research Center

Dear editor,Blockciphers play an fundamental role for cryptography in information security,which usually consist of round functions and key *** one of the significant modules in blockciphers,key schedules have not received deserved ***,the key schedule takes as input a master key and outputs the so-called round keys that are used in each *** the case of AES-128,the master key is a 128-bit string and the total length of the round keys is11×128=1408 *** AES-128 key schedule can be seen as a function from{0,1}128 to{0,1}1408.

关键词： blockciphers key schedule key-alternating Feistel provable security H-coefficient technique

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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

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engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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Social engineering attack types and prevention techniques- A survey 1

Social engineering attack types and prevention techniques- A...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Bhatia, Shruti Yadav, Satya Prakash Near East University Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Nicosia Turkey Near East University Ai and Robotics Institute Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

The term "Cyber Security"is getting more and more popular and important over the last few years. Since computers and most of the devices are connected to the internet, they are likely to be hacked by the hackers. In the past, this issue was not a big problem, because not every device is required to be connected to the internet or the internet was not popular as today. But the case has changed over the years. All the changes in the technology area also changed the cyber-attack models as well. With the development of technology and the change of usage of the internet over the last years cyber-attacks have become more common and popular by the hackers. Hackers have discovered that they have an opportunity to steal or earn money in a short time without having to spend too much effort. These days, the type of cyber-attacks is not the same as the ones in the past. As time passes, the cyber-attack methods are also changing and evolving. Today, hackers are using more advanced and effective cyber-attack methods compared to past years. There are many methods that are impossible to cover all of them in this article. Our main focus will be on social engineering attacks in this article. Social engineering attacks use different approaches to cyber attacking. Unlike trying to explode a victim's social media password etc. using advanced exporting programs, algorithms or techniques, social engineering attacks focus on fooling victims into providing their data to hackers by themselves without using or implementing any password cracking, exploiting techniques etc. We will go over what social media engineering is, type of social engineering methods, what countermeasures can be used to protect from social engineering and more in this article. © 2023 IEEE.

关键词： Crime

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MR Image Quality Assessment via Enhanced Mamba: A Hybrid Spatial-Frequency Approach

MR Image Quality Assessment via Enhanced Mamba: A Hybrid Spa...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Lou, Yiwei Xu, Dexuan Zhang, Rongchao Zhang, Jiayu Cao, Yongzhi Wang, Hanpin Huang, Yu Key Laboratory of High Confidence Software Technologies Peking University Ministry of Education China Peking University School of Computer Science Beijing China Peking University School of Software and Microelectronics Beijing China Peking University National Engineering Research Center for Software Engineering Beijing China

ISBN: (纸本)9798350386226

Magnetic resonance (MR) image quality assessment plays a crucial role in disease diagnosis and data analysis. Existing methods typically treat the data as images and process them with convolutional networks, thereby ignoring the sequential characteristics of MR data. In this paper, we propose a hybrid spatial-frequency network (HSFNet) for MR image quality assessment, which extracts MR image quality features in both spatial and frequency domains. Specifically, within each data domain, information from local images and global sequences is iteratively integrated by applying a Mamba-based cascading processing module for multiple times. Extensive experiments on both T1-weighting and T2-weighting MR datasets demonstrate the proposed method's effectiveness and generalization ability in comparison with state-of-the-art MR image quality assessment methods. © 2024 IEEE.

关键词： Image quality

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Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

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Autonomous Network Optimization and Dynamic Channel Allocation for Cognitive Radio-Based Consumer IoT

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IEEE Transactions on Consumer Electronics 2024年第1期71卷 53-61页

作者： Abbas, Laraib Shoaib, Umar Omar, Marwan Bashir, Ali K. University of Gujrat Department of Computer Science Gujrat Pakistan Illinois Institute of Technology Information Technology and Management United States Manchester Metropolitan University Department of Computing and Mathematics Ukraine Chitkara University Institute of Engineering and Technology Center for Research Impact and Outcome Chitkara University Punjab Rajpura140401 India

The heterogeneous environment of next-generation Consumer Internet of Things (CIoT) demands efficient resource utilization and reliable network services. On the contrary, the proliferation in the diverse nature of smart consumer IoT devices is causing spectrum scarcity and uneven utilization of available resources. Cognitive Radios (CRs) provide the most suitable solution for spectrum scarcity through dynamic spectrum access. To achieve spectral efficiency and provide consumer-centric network services we propose a novel Cognitive Radio based Autonomous Network Management framework called (CR-ANM). The framework combines the benefits of cognitive radios, Network Function Virtualization (NFV), and Software Defined Networking (SDN), to decouple the control plane from the data plane and is divided into two further operations called Dynamic Priority Determination (DPD) and Efficient Channel Allocation (ECA). DPD is responsible for determining the SUs priority using a fuzzy logic-based decision controller. Whereas ECA optimizes the channel allocation process and allocates the best available channel to SU. Which increases the channel availability by 77% and reduces the service drop rate by 81.8%. Both schemes run as Virtual Utility Functions (VUFs) on dedicated virtual machines assigned by the SDN controller. This approach increases energy efficiency for low-power consumer IoT devices and improves network reliability. © 1975-2011 IEEE.

关键词： Fuzzy logic

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A Novel Obstacle Avoidance Consensus Control for Multi-AUV Formation System

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1304-1318页

作者： Linling Wang Daqi Zhu Wen Pang Chaomin Luo the Shanghai Engineering Research Center of Intelligent Maritime Search&Rescue and Underwater Vehicles Shanghai Maritime UniversityShanghai 201306China the Shanghai Maritime University Shanghai 201306China the School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China the Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMS 39762 USA

In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and the communication energy consumption can be decremented. The time-varying formation obstacle avoidance control algorithm based on IAPF-LF is designed to avoid static and dynamic obstacles, the desired formation is maintained in the presence of external disturbances, and there is no Zeno behavior under the fixed-time event-triggered consensus control *** stability of the system is proved by the Lyapunov function and inequality scaling. Finally, simulation examples and water pool experiments are reported to verify the performance of the proposed theoretical algorithms.

关键词： Autonomous underwater vehicle(AUV) event-triggered control fixed-time consensus formation obstacle avoidance improved artificial potential field and leader-follower strategy(IAPF-LF)

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