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Secure blockchain bidding auction protocol against malicious adversaries

High-Confidence Computing 2024年第3期4卷 58-63页

作者： Xiaobing Dai Jiajing Liu Xin Liu Xiaofen Tu Ruexue Wang Department of Computer and Information Engineering Baotou Vocational&Technical CollegeBaotou 014010China Department of Computer Tianjin Ren’ai CollegeTianjin 301636China School of Information Engineering Inner Mongolia University of Science and TechnologyBaotou 014010China

In recent years,with the development of blockchain,electronic bidding auction has received more and more *** at the possible problems of privacy leakage in the current electronic bidding and auction,this paper proposes an electronic bidding auction system based on blockchain against malicious adversaries,which uses the secure multi-party computation to realize secure bidding auction protocol without any trusted third *** protocol proposed in this paper is an electronic bidding auction scheme based on the threshold elliptic curve *** can be implemented without any third party to complete the bidding auction for some malicious behaviors of the participants,which can solve the problem of resisting malicious adversary *** security of the protocol is proved by the real/ideal model paradigm,and the efficiency of the protocol is *** efficiency of the protocol is verified by simulating experiments,and the protocol has practical value.

关键词： Blockchain Secure multi-party computation Electronic bidding auction Malicious model Real/ideal model paradigm

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IDedupNet: A MobileNetV3-Based Deep Learning Framework for Efficient Image Deduplication in Cloud Computing Environments

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第13期49卷 143-162页

作者： Mohiuddin, Mohd Hasan Tamilselvan, Latha Department of Computer Science and Engineering B.S. Abdur Rahman Crescent Institute of Science &Technology Vandalur Chennai600048 India Department of Information & Technology B.S. Abdur Rahman Crescent Institute of Science &Technology Vandalur Chennai600048 India

Image deduplication is becoming increasingly important for cloud storage infrastructures to handle the increasing amount of multimedia material. Through increased storage efficiency, effective picture deduplication may optimize resources and save expenses. It also improves performance by facilitating quicker access, utilizing less bandwidth, and enhancing data integrity. Although heuristic-based classical deduplication techniques work well in various storage infrastructures, they cannot keep up with the dynamic nature of cloud storage resources. This study presents IDedupNet, a revolutionary DL-based framework that improves infrastructure performance in cloud computing by efficiently detecting duplicate and near-duplicate photos. Our approach leverages MobileNetV3 for feature extraction and CNN-based encodings for image deduplication, enabling it to manage duplicate photos in highly dynamic contexts efficiently. Additionally, we provide a Learning-Based Image Deduplication (LBID) approach that improves deduplication performance by extending the use of the IDedupNet model. Experimental evaluation demonstrates a high accuracy of 98.68% on benchmark datasets, consistently outperforming existing models. The underlying technique and deep learning framework may be easily integrated into real-time cloud storage systems to increase customer satisfaction and infrastructure efficiency. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Cloud storage

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Cluster Based Concurrent Data Collection with Fault Tolerance for Shared IoT Applications 16

Cluster Based Concurrent Data Collection with Fault Toleranc...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Kumar, Arvind Matam, Rakesh Swain, Srinibas Mukherjee, Mithun Indian Institute of Information Technology Guwahati Department of Computer Science and Engineering India Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9798350383119

Sharing IoT device infrastructure by multiple entities or applications for their respective sensing and monitoring needs is an effective way to reduce the upfront setup cost, ownership costs, and also to prevent over provisioning. Concurrent data collection in such a shared environment is a major challenge, given the number of devices and multiple processes relying on that data. Most of the existing works in this direction typically consider network scenarios where devices can reach the base station(s) directly. As this assumption is not always valid, few other works focused on concurrent data collection over multiple-hops. In such a shared multi-hop environment, the chances of device failures are high, especially considering the power constraints of devices. To address the issue of reliability in data collection, this paper presents a cluster-based fault tolerant network structure for concurrent data collection. The proposed work aims to minimize the delay and handles the topology changes in case of faults, and also lowers the transmission count. The validity of the proposed work is shown via analytical and simulation results. © 2024 IEEE.

关键词： Concurrent Data collection in IoT Network topology Shared IoT device infrastructure

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Exploration of the Impact of 5G on Mobile Communication Systems

Exploration of the Impact of 5G on Mobile Communication Syst...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Singh, Akhilendra Pratap Seth, Jyoti Kamalraj, R. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

The fifth era (5G) of cell communication systems is a progressive jump forward in the evolution of wireless networks. It promises to deliver a brand new user enjoyment, characterized by using quicker speeds and greater capability, with improved energy efficiency. The increased speed and efficiency of 5G networks could have a big impact on a wide variety of packages, which includes stepped forward user revel, advanced great of provider, and green use of sources. This paper explores the ability impact of 5G on cellular communique systems by inspecting the important thing demanding situations and case studies that highlight specific advantages that may be realized. We evaluate the primary technological advances that will make contributions to the success of 5G structures, including millimeter waves, large MIMO and beamforming, and community cutting. The paper also considers the capability effect that 5G will have on modern-day network architectures, regulatory and policy frameworks, and new enterprise fashions in order to be taken into consideration. Through a variety of case research, we pick out the potential possibilities and challenges that 5G might also carry and provide concrete suggestions on how first-rate to ensure successful deployment. In the end, we present the concept that 5G can be the most effective engine of digital transformation, furnishing the right mixture of innovation, investment, and partnership. © 2024 IEEE.

关键词： Beamforming Communication Efficiency Enterprise Networks Partnership

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Investigating and Implementing the Efficiency of Image Restoration Techniques in Digital Image Processing

Investigating and Implementing the Efficiency of Image Resto...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Seth, Jyoti Ojha, Ananta Singh, Vaishali Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

photo restoration is restoring the advent and pleasantness of a picture that has been degraded in various manners. Photo healing strategies are extensively used in digital picture processing for recovering pics degraded due to noise, blur, and artifacts. These techniques are based on restoring the underlying records compromised by the degradation. Photo restoration intends to repair the image and make it look nice. This research investigates and implements the performance of photo restoration strategies in virtual picture processing. An assessment and contrast of various photograph restoration strategies consisting of Wiener filter, Tikhonov regularization, and overall variant regularization are performed with the usage of numerous criteria, which include top Signal-to-Noise Ratio (PSNR) and suggest rectangular mistakes (MSE). The results of photograph healing techniques are also evaluated in terms of the first-rate of the restored picture. A test is conducted on a selected photograph to illustrate the effectiveness of the numerous strategies. The outcomes of the experiments and critiques exhibit that photo recuperation techniques can effectively repair first-class degraded photos. The effectiveness of those techniques relies upon the type of degraded image and the noise present in it. Wiener filter out is powerful for pics corrupted by additive white Gaussian noise;simultaneously, Tikhonov regularization and total version regularization are most appropriate for images corrupted by impulsive noise. Consequently, this research provides a perception of the overall performance and efficiency of photo healing techniques to facilitate the choice of the best method for various picture recuperation programs. © 2024 IEEE.

关键词： degraded efficiency facilitate restoration technique

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The Claim-based Priority-Discriminated Channel Access (CPDCA) Method using the Registered Backoff Time Mechanism for IEEE 802.11ah

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Mobile Networks and Applications 2023年第3期28卷 1096-1115页

作者： Huang, Chung-Ming Cheng, Rung-Shiang Pan, Yan-Jia Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Department of Information Technology Overseas Chinese University Taichung Taiwan

IEEE 802.11ah is a protocol that adopts the CSMA/CA-based channel access way for Internet of Thing (IOT). This work proposed a newly devised Restricted Access Window (RAW) called the Claiming RAW to let those spontaneous stations having high priority’s uplinked data frames do claims of intending to uplink high priority’s data to reduce collisions. In addition, instead of generating the random backoff time after the collision happens, which the regular CSMA/CA-based 802.11* protocols adopt, this work adopted the registered backoff time mechanism, for which a station registers its next backoff time to IEEE 802.11ah AP when its current channel access is finished, i.e., a station generates the backoff time before the collision happens. Thus, IEEE 802.11ah AP is able to schedule stations’ channel accesses based on stations’ registered backoff time to avoid collisions more effectively. Through the use of the Claiming RAW and the registered backoff time mechanisms, IEEE 802.11ah AP can know which stations have high priority’s uplinked data frames and then schedule these stations to have the higher privilege to access the channel. The simulation results shown that. Comparing with the traditional IEEE 802.11ah, the simulation results shown that the proposed Claim-based Priority-Discriminated Channel Access (CPDCA)method has a lower collision rate and higher throughput in the network environment having the higher number of stations in each time slot;the transmission time of those stations with high priority’s uplinked data frames using the CPDCA mechanism is much lower than that of using the traditional IEEE 802.11ah. © 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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The Smart Attitude Analysis of Network Interference User using Recursive Neural Framework

The Smart Attitude Analysis of Network Interference User usi...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Agarwal, Ankita Devrani, Rekha Kannagi, A. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

This paper proposes a Recursive Neural framework for the clever mindset evaluation of network interference customers. Our technique builds on previous work achieved in sentiment analysis using extracting a person's man or woman mindset from complicated and incomplete statistics streams. The framework, to begin with, gets the sentiment layers based on consumer interactions from the datasets, after which it integrates this fact with various Recursive Neural networks to seize the sentiment of a single user. The community extracts capabilities associated with the user and learns to distinguish between the behaviors of two users inside the community. Once the community is educated on the datasets, it may classify the sentiment of users based on various contextual cues. We evaluated our framework through crowd-sourced sentiment annotation datasets from a web forum, and it confirmed superior overall performance than different present approaches. We proposed a Recursive Neural framework that utilizes contextual schemas and sentiment to analyze user attitudes and behaviors for community interference scenarios. It can open up promising new opportunities for observing consumer mindset and behavior in online networks. This paper offers a recursive neural framework for competent mindset evaluation of network interference customers. Recursive Neural Networks, broadly carried out in natural language processing responsibilities with sentiment analysis, combine word embeddings with a recursive architecture to gain a perception of the syntactic shape of sentences. On this, look at the Recursive Neural Network (RNN) architecture tailored to research the sentiment mindset of community interference users. The information amassed from Twitter, Weibo, and different open-supply platforms had been pre-processed using the frequency inverted report frequency technique before constructing an RNN for its modeling. Checks at the built community proved that the proposed model furnished pleasant c

关键词： efficacy evaluation extracting practitioners recognize

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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 315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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Design of improved deer hunting optimization enabled multihop routing protocol for wireless sensor networks

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International Journal of Cognitive Computing in engineering 2023年第1期4卷 363-372页

作者： Balasubramanian, D. Lubin Govindasamy, V. Department of Computer Science and Engineering Manakula Vinayagar Institute of Technology Puducherry India Department of Information Technology Puducherry Technological University Puducherry India

A wireless sensor network (WSN) encompasses a huge set of sensor nodes employed to collect data and transmit it to a base station (BS). Due to its compact, inexpensive, and scalable nature of sensors, WSN finds its applicability in diverse real-time applications. The battery-operated sensor nodes necessitate the design of a multi-hop routing protocol for the effective utilization of available energy in the network. Routing can be considered an optimization problem and can be solved by the design of bioinspired algorithms. This study introduces an improved deer hunting optimization-enabled multihop routing (IDHO-MHR) protocol for WSN. The major intention of the IDHO-MHR approach is to optimally find the routes to the destination in WSN. The IDHO algorithm is initially derived by the incorporation of the Nelder Mead (NM) concept into the traditional DHO algorithm. In addition, the IDHO-MHR technique primarily derives a fitness function with the inclusion of two major variables, namely residual energy (RE) and distance. The nodes with higher RE and minimum distance have the probability of becoming optimal routes from the networks. The performance validation of the IDHO-MHR approach is performed, and the outcomes are inspected in various aspects. The experimental outcomes reported the supremacy of the IDHO-MHR protocol over the other recent approaches. © 2023 The Authors

关键词： Energy efficiency

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Analyzing the Role of Time Series Analysis in Early Detection of Merkel Cell Carcinoma

Analyzing the Role of Time Series Analysis in Early Detectio...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Singh, Akhilendra Pratap Seth, Jyoti Nachappa, M.N. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

this paper investigates the potential of using time collection evaluation to detect Merkel cellular Carcinoma (MCC) early. MCC is a competitive shape of pores and skin. Early detection is critical to the growing survival rate. Time collection evaluation is an adequate records mining technique used to degree diffused styles in facts. This look aims to discover the usage of time series analysis to stumble on early signs and symptoms of MCC and evaluate the results to present strategies that include Random forest and decision Tree classifiers. First, fixed healthcare information collected from patients with MCC became amassed, and the related time series was created. Next, different versions of time collection models consisting of ARIMA (car-Regressive included transferring common) and SARIMA (Seasonal ARIMA) become used to measure the extent of temporal trends inside the records. Subsequently, the models were compared in opposition to the present system learning classifiers and assessed in phrases of accuracy, precision, take into account, and F1-score. © 2024 IEEE.

关键词： adjustments discovering Regressive sickness stumble

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