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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Securing Electronics Gadgets using Blockchain based Framework 2

Securing Electronics Gadgets using Blockchain based Framewor...

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2nd IEEE International Conference on Emerging Research in Computational science, ICERCS 2024

作者： Prakash, P. N. Senthil Lanitha, B. Sundaram, Karthic Vellore Institute of Technology School of Computer Science and Engineering Chennai India Karpagam Academy of Higher Education Department of Artificial Intelligence and Data Science Coimbatore India KPR Institute of Engineering and Technology Department of Information Technology Coimbatore India

ISBN: (纸本)9798331534950

The usage of electronic gadgets has grown dramatically in the current digital era. Devices like mobile phones and smart watches are unavoidable and has ingrained themselves into every person's daily routine. Almost everyone owns at least one portable electronic device and these devices are usually expensive. Due to this widespread use, there is also an increase in the number of lost or stolen cases reported. In a recent study, it has been revealed that the number of devices lost is mostly because of misplacing in public places like home, office, public transport. Such incidents will not only cause financial loss but it may also lead to data breaches stored in the portable devices. Hence there is a need for a secure eco-system which helps to identify the genuine owners of electronic devices. A blockchain-based framework is deployed on an Ethereum-based network and adopts the Proof of Stake (PoS) mechanism to protecting gadgets. Further, it is designed using the smart contract defined using solidity programming language. The system enables the owner's details to be recorded upon purchase of a device. The complete specification details of the devices along with owner details is contained in a block and then appended to network. Later on, if the owner wants to resale the device, then the transfer of ownership information is stored in a block and added to the network. The proposed system provides an appropriate interface to check the genuine owner. The proposed framework has been implemented using solidity language, Remix IDE and Sepolia testnet. Obtained results highlights the suitability of the method and its performance in terms of gas consumption and execution latency. © 2024 IEEE.

关键词： Ethereum

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Classification of Sarcoma Based on Genomic data Using Machine Learning Models

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Procedia computer science 2025年 252卷 317-330页

作者： Pratham Gala Yash Pandloskar Shubham Godbole Fayed Hakim Pratik Kanani Lakshmi Kurup Dept. of Computer Science and Engineering (Data Science) Dwarkadas J. Sanghvi College of Engineering Mumbai India Dept. of Artificial Intelligence and Data Science Dwarkadas J. Sanghvi College of Engineering Mumbai India

The proposed work provides a new machine-learnt classification approach for the various types of soft tissue sarcoma based on genomics data which addresses a considerable gap in sarcoma diagnostics. The previous studies have investigated various aspects of sarcoma but this study is unique in that it targets the predicting sarcoma variant types using genetic information, which has not been done before. Random Forest was used as the meta-estimator and a stacking ensemble model comprising of Random Forest, Extreme Gradient Boosting and LightGBM were used for this study. The model which was trained and validated on a complete dataset of 206 adult soft tissue sarcoma samples containing genomic alterations, transcriptomic, epigenomic and proteomic data achieved an accuracy of 89.44% at a precision level as high as 91%. Stratified k-fold cross validation is employed to ensure that class imbalance is not a hindrance to performance. This innovative approach outmatches single classifiers and traditional single model methods at great length hence making it possible and effective to use machine learning on genomic data for predicting sarcoma variants. Thus, the findings from this research could change cancer diagnosis forever; they promise more accurate classification as well as personalized treatment modalities while also providing a framework for analogous applications in other rare complex cancers.

关键词： Sarcoma Classification Stacking Ensemble Model Genomic data

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Efficient Relaxed Functional Dependency Discovery with Minimal Set Cover 40

Efficient Relaxed Functional Dependency Discovery with Minim...

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40th IEEE International Conference on data engineering, ICDE 2024

作者： Ding, Xiaoou Liu, Yida Wang, Hongzhi Wang, Chen Song, Yichen Yang, Donghua Wang, Jianmin School of Computer Science and Technology Harbin Institute of Technology China National Engineering Research Center for Big Data Software EIRI Tsinghua University China

ISBN: (纸本)9798350317152

Assessing data quality through Functional Depen-dencies (FDs) is a crucial aspect of data governance. However, with the diverse range of data sources and the exponential growth in data volume, exact FDs can sometimes be impractical for real-world applications. In contrast, relaxed functional dependencies (RFDs), which allows for some flexibility in attribute value comparisons, demonstrates greater adaptability and flexibility for big data scenarios. To address the efficient discovery of RFDs, this paper proposes a novel mining method to supplement the current research gaps. By establishing a difference table for tuples, we transform the problem into a specialized minimal set covering problem. Additionally, we introduce two optimization strategies: reducing the time complexity of enumerating the left-hand side of the base RFDs to 0 (1) and decreasing the search complexity for feasible LHS attributes and threshold candidates from O(2m-l) to O(1.5m-1). We rigorously proof that our mining approach guarantees the identification of validity and minimal RFDs. Experiments on nine real-world datasets reveal that our method significantly improves efficiency compared to existing techniques. Furthermore, it uncovers more concise and higher-quality RFDs. Importantly, the RFDs extracted through our methodology exhibit better performance in downstream cleaning tasks. © 2024 IEEE.

关键词： Quality management

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Modeling of metaheuristic-based dual cluster head selection with routing protocol for energy-efficient wireless sensor networks

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Soft Computing 2025年第6期29卷 2999-3020页

作者： Reddy, Maddikera Krishna Veluswamy, Anusha Sowbarnika Selvanayaki, S. Harini, C. Kumar, Pavan Shameem, Syed Department of Electronics and Communication Engineering Rajeev Gandhi Memorial College of Engineering and Technology Andhra Pradesh Nandyal India Department of Mathematics and Computer Science Susquehanna University Pennsylvania SelinsgrovePA United States Department of Artificial Intelligence and Data Science Saveetha Engineering College Chennai India Maisamma Guda Secunderabad India Department of Computer Science and Engineering Raghu Engineering College Andhra Pradesh Dakamarri Vizayanagaram India Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India

Wireless Sensor Networks (WSN) are decentralized networks of spatially distributed sensors that gather and monitor environmental information for various applications, including industrial automation and environmental monitoring. This enables real-time information gathering without relying upon wired connections. In WSN, clustering and routing are essential techniques for improving data transmission. Clustering comprises grouping sensor nodes (SN) into clusters to optimize energy efficacy and extend the network's lifetime. However, selecting suitable and efficient cluster head (CH) components is crucial to harness their benefits. Selecting appropriate CHs and finding optimum coefficients for all the parameters of applicable fitness function (FF) in CH selection is a non-deterministic polynomial-time (NP-hard) problem that needs additional processing. In contrast, routing focuses on defining the most effective path for data to traverse through the network, ensuring timely and reliable data delivery and reducing energy consumption. Therefore, this study proposes a new Metaheuristic-Based Dual Cluster Head Selection with Routing Protocol (MBDCHS-RP) method for energy-efficient WSNs. The MBDCHS-RP method aims to cluster the nodes and select optimum routes for transmitting information in the WSN. To achieve this, the MBDCHS-RP method follows a two-stage clustering process, including tentative CH (TCH) and final CH (FCH) selection. The MBDCHS-RP technique utilizes a cheetah optimization algorithm (COA) with FF comprising residual energy (RE) and average node distance as input parameters for the TCH selection process. In addition, the flower pollination algorithm (FPA) is used to select final CHs with multiple input parameters, namely average intra-cluster distance, RE, and average sink distance. A carnivorous plant algorithm (CPA) is employed for the optimal route selection process with two parameters, RE and distance to the base station, to enable an effective data transm

关键词： Sensor nodes

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Aggregation-based dual heterogeneous task allocation in spatial crowdsourcing

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Frontiers of computer science 2024年第6期18卷 215-227页

作者： Xiaochuan LIN Kaimin WEI Zhetao LI Jinpeng CHEN Tingrui PEI College of Information Science and Technology&Cyberspace Security Jinan UniversityGuangzhou 510632China National&Local Joint Engineering Research Center of Network Security Detection and Protection Technology Guangzhou 510632China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou 510632China School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China

Spatial crowdsourcing(SC)is a popular data collection paradigm for numerous *** the increment of tasks and workers in SC,heterogeneity becomes an unavoidable difficulty in task *** researches only focus on the single-heterogeneous task ***,a variety of heterogeneous objects coexist in real-world SC *** dramatically expands the space for searching the optimal task allocation solution,affecting the quality and efficiency of data *** this paper,an aggregation-based dual heterogeneous task allocation algorithm is put *** investigates the impact of dual heterogeneous on the task allocation problem and seeks to maximize the quality of task completion and minimize the average travel *** problem is first proved to be ***,a task aggregation method based on locations and requirements is built to reduce task ***,a time-constrained shortest path planning is also developed to shorten the travel distance in a *** that,two evolutionary task allocation schemes are ***,extensive experiments are conducted based on real-world datasets in various *** with baseline algorithms,our proposed schemes enhance the quality of task completion by up to 25% and utilize 34% less average travel distance.

关键词： task allocation aggregation shortest path dual heterogeneous spatial crowdsourcing

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A New Tree Structure for Local Diagnosis

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Journal of Information science and engineering 2024年第2期40卷 231-244页

作者： Chen, Meirun Li, Xiao-Yan Lin, Cheng-Kuan Pai, Kung-Jui School of Mathematics and Statistics Xiamen University of Technology Xiamen361024 China College of Computer and Data Science Fuzhou University Fuzhou350108 China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology National Defense University Taoyuan30010 Taiwan Department of Industrial Engineering and Management Ming Chi University of Technology New Taipei City243303 Taiwan

Diagnosability is an important parameter to measure the fault tolerance of a multiprocessor system. If we only care about the state of a node, instead of doing the global diagnosis, Hsu and Tan proposed the idea of local diagnosis. Chiang and Tan provided an extended star structure to diagnose a node under comparison model. In this work, we evaluate the local diagnosability better by proposing a tree structure around this node. We provide the corresponding algorithm to diagnose the node. Simulation results are presented for different failure probability of a node in the tree and different percentage of faulty nodes in the tree, showing the performance of our algorithm. © 2024 Institute of Information science. All rights reserved.

关键词： comparison model diagnosis algorithm fault diagnosis local diagnosability tree

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Multi-View Dynamic Kernelized Evidential Clustering

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2435-2450页

作者： Jinyi Xu Zuowei Zhang Ze Lin Yixiang Chen Weiping Ding the Software Engineering Institute East China Normal UniversityShanghai 200062 Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China IEEE the School of Automation Northwestern Polytechnical UniversityXi’an 710072China the School of Artificial Intelligence and Computer Science Nantong UniversityNantong 226019 the Faculty of Data Science City University of MacaoMacao 999078China

It is challenging to cluster multi-view data in which the clusters have overlapping *** multi-view clustering methods often misclassify the indistinguishable objects in overlapping areas by forcing them into single clusters,increasing clustering *** solution,the multi-view dynamic kernelized evidential clustering method(MvDKE),addresses this by assigning these objects to meta-clusters,a union of several related singleton clusters,effectively capturing the local imprecision in overlapping *** offers two main advantages:firstly,it significantly reduces computational complexity through a dynamic framework for evidential clustering,and secondly,it adeptly handles non-spherical data using kernel techniques within its objective *** on various datasets confirm MvDKE's superior ability to accurately characterize the local imprecision in multi-view non-spherical data,achieving better efficiency and outperforming existing methods in overall performance.

关键词： Evidential clustering imprecision characterizing kernel technique multi-view clustering

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MLPFormer: MLP-integrated transformer for colorectal histopathology whole slide image segmentation

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Neural Computing and Applications 2025年第6期37卷 4651-4661页

作者： Wang, Yuxuan Li, Dan Li, Xuechen Guo, Yan Zuo, Yanfei Shen, Linlin Department of Computer Science Wenzhou-Kean University Wenzhou China School of Electronics and Information Engineering Wuyi University Jiangmen China Department of Histo Pathology Shanghai Histo Pathology Diagnostic Center Shanghai China College of Computer Sicence and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

Colorectal intraepithelial neoplasia is a precancerous lesion of colorectal cancer, which is mainly diagnosed using pathological images. According to the characteristics of lesions, precancerous lesions can be classified into four different grades, i.e., background, normal, low and high level. However, due to the continuity of lesion development, tissue in different stages has high similarity. Recently, visual transformers have achieved impressive results in different visual tasks, due to their capacity of capturing long-range dependencies. However, due to computational cost, transformer cannot well extract detailed feature, which is important for lesion grading. To accurately segment pathological tissues with high similarity, in this work, we embed the multi-head MLP mixer module in the transformer network to extract cell and edge information. Furthermore, we propose a hierarchical MLP decoder to facilitate multi-scale feature fusion. The proposed transformer, namely MLPFormer, achieves remarkable results against competitive baselines on the Histo-CRC Biopsy dataset. The experimental results demonstrate that MLPFormer significantly outperforms the competitive baselines, i.e., a 3% dice improvement is achieved over the SegFormer series. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Image segmentation

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Exploring blockchain solutions: Integrating cryptocurrency with IoT for enhanced security

Exploring blockchain solutions: Integrating cryptocurrency w...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Shravan, M. Kakad, Shital Mulani, Umar M Sharma, Geeti Tiwari, Mohit Mary Shiba, C. Sr University School of Business Telangana Warangal India Vishwakarma Institute of Technology Artificial Intelligence and Data Science Maharashtra Pune India Kj College of Engineering and Management Research Pune India India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi Delhi India R.M.K Engineering College Department of Computer Science and Business Systems Thiruvallur India

ISBN: (纸本)9798331508685

Blockchain, initially developed as the underlying technology for Bitcoin, has garnered significant attention for its applications beyond cryptocurrency, particularly in complex non-monetary domains. Utilizing cryptographic methods like hashing and asymmetric encryption, combined with a distributed consensus model, Blockchain-based ledgers achieve high levels of security and immutability, effectively removing the need for third-party intermediaries. Meanwhile, the rapid growth in Internet of Things (IoT) devices being connected to networks raises substantial concerns around security and privacy. Addressing these security challenges is essential for the expanding IoT landscape. This paper explores the blockchain solution by integrating cryptocurrency with IoT for enhanced security, reviewing recent studies and applications to evaluate Blockchain's role in IoT security, pinpoint challenges, and propose Blockchain-driven solutions to improve security in the IoT ecosystem. © 2025 IEEE.

关键词： Blockchain Cryptocurrency Internet of Things privacy Security

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