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检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

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TrustMesh: A Blockchain-Enabled Trusted Distributed computing Framework for Open Heterogeneous IoT Environments 22

TrustMesh: A Blockchain-Enabled Trusted Distributed Computin...

引用

22nd IEEE international conference on Software Architecture, ICSA 2025

作者： Rangwala, Murtaza Buyya, Rajkumar Laboratory School of Computing and Information Systems Australia

ISBN: (纸本)9798331520908

The rapid evolution of Internet of Things (IoT) environments has created an urgent need for secure and trust-worthy distributed computing systems, particularly when dealing with heterogeneous devices and applications where centralized trust cannot be assumed. This paper proposes TrustMesh, a novel blockchain-enabled framework that addresses these challenges through a unique three-layer architecture combining permissioned blockchain technology with a novel multi-phase Practical Byzantine Fault Tolerance (PBFT) consensus protocol. The key innovation lies in TrustMesh's ability to support non-deterministic scheduling algorithms while maintaining Byzantine fault tolerance, features traditionally considered mutually exclusive in blockchain systems. The framework supports a sophisticated resource management approach that enables flexible scheduling decisions while preserving the security guarantees of blockchain-based verification. Our experimental evaluation using a real-world cold chain monitoring scenario demonstrates that TrustMesh successfully maintains Byzantine fault tolerance with fault detection latencies under 150 milliseconds, while maintaining consistent framework overhead across varying computational workloads even with network scaling. These results establish TrustMesh's effectiveness in balancing security, performance, and flexibility requirements in trustless IoT environments, advancing the state-of-the-art in secure distributed computing frameworks. © 2025 IEEE.

关键词： Edge computing

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Optimizing VPN Security in Financial Services: Implementing 256-Bit Encryption and Tunneling Protocols for Secure Data Transmission 19

Optimizing VPN Security in Financial Services: Implementing ...

引用

19th international conference on Ubiquitous information Management and Communication, IMCOM 2025

作者： Ilias, Irma Syarlina Che Sameon, Sera Syarmila Zulkifli, Muhammad Zaqwan Ezzad Salleh, Mohammad Zahir Mat Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia College of Computing and Informatics Universiti Tenaga Nasional Selangor Malaysia CyberSecurity RawSec Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

This study examines the essential importance of security in contemporary network settings, emphasizing the increasing dependence on Virtual Private Networks (VPNs) for safe data transfer. The emphasis is on assessing the security attributes of VPNs to enhance existing network systems. This study specifically contrasts the performance and efficacy of two tunneling protocols—Layer 2 Tunneling Protocol version 3 with IPsec (L2TPv3/IPsec) and Generic Routing Encapsulation (GRE) utilizing IPsec—in a site-to-site connection. The study offers an economical solution by leveraging current infrastructure, minimizing the requirement for extra gear like antennas and rented space. Moreover, the study follows the National Institute of Standards and technology (NIST) security protocols, specifically designed for the financial services sector, guaranteeing a secure and cost-effective approach for data transfer. Initial findings indicate that the best arrangement of VPN tunnels improves security in financial services networks, providing an effective method for protecting direct connections. © 2025 IEEE.

关键词： Cost effectiveness

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Emerging Horizons in Renal Cell Carcinoma Therapy: Impact of Cuproptosis-Related miRNAs on RCC 16th

Emerging Horizons in Renal Cell Carcinoma Therapy: Impact of...

引用

16th international conference on Genetic and Evolutionary computing, ICGEC 2024

作者： Abraham Gnanadass, Subeka Viswanathan, Pragasam 412-B Renal Research Laboratory Pearl Research Park School of Bio-Sciences and Technology Vellore Institute of Technology Tamil Nadu Vellore632014 India

ISBN: (纸本)9789819615308

Renal Cell Carcinoma (RCC) is a common type of genitourinary cancer. Despite progress in treatment, challenges such as drug resistance and disease recurrence remain, emphasizing the need for ongoing research to improve outcomes for RCC patients. Copper is essential for various biological processes, including iron intake, antioxidant/detoxification, and mitochondrial respiration. Cuproptosis, a type of cell death induced by copper and proteotoxicity, is closely linked to the TCA cycle and mitochondrial respiration and appears to play a significant role in cancer characteristics. There is also a strong connection between non-coding RNAs, cuproptosis, and cancer. The regulatory role of cuproptosis-related miRNAs in RCC prognosis is still not fully understood. In our current work, we have identified cuproptosis-related miRNAs and visualized them using CancerMIRNome. Potential miRNAs were determined through regression analysis, and gene enrichment analyses were conducted to understand their regulatory role in RCC development. Therefore, creating signatures of cuproptosis-related miRNAs may offer significant advantages and play a crucial role in the treatment and therapeutics of RCC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Disease control

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Design of a Smart Home Door Security System with Face Detection and Smart Bell using ESP32-CAM 6

Design of a Smart Home Door Security System with Face Detect...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Salsabila, Nurhusna Siswanto, Apri Bayuaji, Luhur Informatics Department Faculty of Engineering Universitas Islam Riau Pekanbaru Indonesia Fac. Data Science and Information Technology INTI International University Malaysia

ISBN: (纸本)9798331522667

This research introduces the design and implementation of an advanced IoT-based home security system aimed at improving both convenience and safety for homeowners. The system integrates a smart doorbell with a mobile application, enabling real-time alerts for guest arrivals. Key features include facial recognition for automated door unlocking and notification of unrecognized visitors. When an unknown face is detected, the system sends an image along with a notification to the homeowner via a Telegram bot. The architecture incorporates the ESP32-CAM microcontroller for face detection, a solenoid lock for automatic door access, and an ultrasonic sensor to detect visitor presence. Extensive testing under various environmental conditions was conducted to assess the system's performance, particularly in terms of face recognition accuracy and notification delivery. The results indicate that the system significantly enhances home security by ensuring timely notifications and automating door access for verified individuals. While the system performs reliably in well-lit environments, challenges remain in low-light conditions. Software testing confirmed the robustness of the underlying logic. This innovative IoT solution overcomes the limitations of traditional security systems, offering a more secure, user-friendly, and efficient alternative for modern home security. © 2025 IEEE.

关键词： Ultrasonic sensors

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Real-Time Sign Language to Speech Converter Using OpenCV and MediaPipe 5

Real-Time Sign Language to Speech Converter Using OpenCV and...

引用

5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Pathak, Anvisha Patil, Niraj Padhy, Prashant Jadhav, Adarsh Rukhande, Smita Gadhikar, Lakshmi Fr. Conceicao Rodrigues Institute of Technology Dept. of Information Technology Navi Mumbai India Fr. Conceicao Rodrigues Institute of Technology Dept. of Computer Engineering Navi Mumbai India

ISBN: (纸本)9798331522100

Communication barriers between deaf individuals and hearing people can lead to several significant problems such as social integration, reduced access to information and reduced opportunities thereby affecting quality of life of deaf individuals. Use of sign language for communication serves as the primary means to address these challenges. However, understanding of the sign language is very difficult for hearing individuals. To address this issue, we present a Real-Time Sign Language to text and Speech Converter to facilitate effective communication between deaf and hearing individuals. This paper presents a novel approach to sign language recognition using OpenCV and MediaPipe. The main aim of the paper is to develop real time computer vision that can translate sign language gestures into text in real-time. We use image processing techniques to segment and analyze sign gestures, OpenCV to record and process these gestures, MediaPipe for hand tracking and gesture prediction and a text-to-speech engine to translate the text into speech for auditory communication. Thus, this study offers a comprehensive sign language to speech converter system that has the potential to significantly improve communication between the deaf community and the hearing people. © 2025 IEEE.

关键词： Gesture recognition

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Secure Smart Contracts: Enhancing Vulnerability Detection With Graph and Tokenization Analysis

Secure Smart Contracts: Enhancing Vulnerability Detection Wi...

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2025 international conference on computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Arun Kumar, B.R. Lakshmi, B.N. Prasad, Mahadeshwara Sangolli, Dharshan B. Gowda, Akshith Likhith, Y.V. Bms Institute of Technology & Management Department of Information Science Bengaluru India Bms Institute of Technology & Management Department of Computer Science Bengaluru India

ISBN: (纸本)9798331538538

Blockchain smart contracts can be easily integrated into any DApp because they function automatically and cannot be altered. But the existence of important weaknesses, like reentrancy attacks, integer overflow, underflows, and access control problems, puts these contracts at a considerable risk in terms of reliability and security. To effectively detect the vulnerabilities, smart contract's code needs to be preprocessed into a strong representation that will be properly analyzed by the deep learning models. In this study, we offer a hybrid deep learning model combining the use of Graph Neural Networks (GNNs) and CodeBERT that can effectively be ensured through a dedicated preprocessing pipeline. Our model involves: (1) First, smart contract code is graphically converted by employing Recursive Depth First Traversal (RDFT) and Iterative Depth First Traversal (IDFT) algorithms to allow code structure along with relationships to be preserved;(2) The WordPiece tokenizer is used in smart contracts to comprehend semantics better;and (3) The Slither static analysis tool is incorporated to facilitate the marking of weaknesses. Finally, we examine different graph construction algorithms focusing on accuracy and computational ability while concluding that IDFT is most helpful in completing this task. The proposed preprocessing pipeline enables precise identifi- cation of vulnerable functions, variables, and line numbers while preparing the data for hybrid model training. This work lays a foundation for advancing automated vulnerability detection, contributing to a more secure blockchain ecosystem. © 2025 IEEE.

关键词： Graph neural networks

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Pronunciation Correction for Hearing Impairment by Web Connection with Volunteers 12th

Pronunciation Correction for Hearing Impairment by Web Conne...

引用

12th international conference on Frontiers of Intelligent computing: Theory and Applications, FICTA 2024

作者： Park, JungHyun Chadwick International School Incheon Korea Republic of

ISBN: (纸本)9789819601462

Pronunciation plays a crucial role in shaping first impressions during initial conversations, and unclear pronunciation is often misconstrued to be closely linked to intelligence. Consequently, individuals with hearing impairments who struggle with pronunciation are susceptible to such misunderstandings. This paper aims to address this issue by describing a prototype web service that provides remote assistance for pronunciation correction among individuals with hearing impairments. The service allows individuals with hearing impairments to upload recorded audio files, which are then reviewed by non-hearing-impaired volunteers. Subsequently, feedback is provided by comparing the submitted pronunciation with standard pronunciation. Prior research has explored various methods to address similar issues, including mimicking mouth movements and automatic recognition using AI. This study analyzed these programs, considering the characteristics of the Korean language, and applied the most suitable platform and technology to create a service tailored for individuals with hearing impairments. The web service emphasizes accessibility, enabling individuals to receive pronunciation correction assistance without constraints related to time, resources, or location. The development process involved utilizing Figma for web design and coding, forming the primary technologies for the web user interface. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Web Design

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Latency optimization for task offloading in Space-Terrestrial collaborative networks based on deep reinforcement learning

Latency optimization for task offloading in Space-Terrestria...

引用

2024 international conference on Smart Transportation and City Engineering, STCE 2024

作者： Song, Chuanlong Zhao, Yuxuan He, Jian School of Communication and Information Engineering Shanghai University Shanghai China Shanghai Aerospace Electronic Technology Institute Key Laboratory of Intelligent Computing for Spatial Heterogeneous Network Shanghai China

ISBN: (纸本)9781510690585

Satellite networks, as a crucial component of space communication systems, effectively mitigate the limitations of terrestrial communication networks in edge computing, such as insufficient ground station coverage and susceptibility to natural disasters. Therefore, this paper introduces satellite networks into the context of terrestrial edge computing, constructing a space-terrestrial collaborative network edge computing framework and investigating the latency issues in task offloading. Due to factors such as long communication distances in space-terrestrial networks, limited onboard resources, and rapid relative positional changes between nodes, system latency may increase. This study models the problem as a Markov Decision Process (MDP) with the objective of minimizing system latency. A Deep Deterministic Policy Gradient (DDPG) reinforcement learning algorithm is proposed for the space-terrestrial collaborative network edge computing scenario. Experimental results demonstrate that, compared to local task processing and the Deep Q-Network (DQN) algorithm, the proposed algorithm reduces the overall system overhead by an average of 28.12% and 13.29%, respectively, while also exhibiting better stability and convergence. © 2025 SPIE.

关键词： Satellite communication systems

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Zero-correlation Linear Cryptanalysis on Full-round Shadow 24

Zero-correlation Linear Cryptanalysis on Full-round Shadow

引用

5th international conference on Computer Science and Management technology, ICCSMT 2024

作者： Hong, Haonan Li, Wenya Chen, Ziyu Zhang, Kai Information Engineering University Henan Zhengzhou China Laboratory for Advanced Computing and Intelligence Engineering Jiangsu WuXi China

ISBN: (纸本)9798400709999

The rapid development of the Internet of Things (IoT) has led to an increasing demand for symmetric ciphers in IoT devices. Shadow is a lightweight block cipher proposed in 2021. In previous research, the security evaluations on Shadow against differential attack, impossible differential cryptanalysis and linear cryptanalysis were proposed. However, the security level on Shadow for zero-correlation linear cryptanalysis is still missing. In this paper, we fill this gap and propose the security evaluation on Shadow against zero-correlation linear cryptanalysis. To make thorough security analysis, two different approaches are adopted to construct zero-correlation linear distinguishers on Shadow. Based on the method of traceable pattern, 128 6-round zero-correlation linear distinguishers are constructed for Shadow-32, and 256 8-round distinguishers for Shadow-64 are constructed with similar approach. Based on the detailed linear property of the round function, 56 and 240 full-round zero-correlation linear distinguishers are constructed for Shadow-32 and Shadow-64 respectively. To validate the correctness of our theoretical analysis, a series of experiments are conducted, which matches our results well. The result in this paper implies Shadow cannot meet the expected security level in terms of zero-correlation linear cryptanalysis. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Ciphertext

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Diabetes Detection Using Iris Image 3

Diabetes Detection Using Iris Image

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Bindu, S. Sarala, T. Prashanth, M.K. Mohan Kishore, D. Bnm Institute of Technology Visveswaraya Technological University Dept. of Electronics & Communication Engineering Bengaluru India Bnm Institute of Technology Visveswaraya Technological University Dept. of Chemistry Bengaluru India Svyasa Deemed to be University Karnataka India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

The diabetes detection utilizing iris images was an extensive investigation into the application of machine learning techniques for medical image analysis. The primary objective was to develop an effective system capable of distinguishing between diabetic and non-diabetic individuals based on iris images. The Proposed system comprised several phases, including image preprocessing, feature extraction using Histogram of Oriented Gradients (HOG), and classification using the AdaBoost algorithm. Iris images were preprocessed by converting them to grayscale, resizing them to a uniform size, and normalizing their pixel values. HOG was employed to extract meaningful features from the images, capturing the essential gradient and edge information necessary for classification. The AdaBoost classifier, with a decision tree as the base learner, was then trained to differentiate between diabetic and non-diabetic iris images. A comprehensive dataset of iris images was used, split into training and testing sets to ensure robust model validation. Cross-validation was performed to assess the model's generalization capability, resulting in a low cross-validated loss, indicative of the model's accuracy and reliability. For feature extraction and classification, the suggested solution successfully integrates Python's machine learning packages, including scikit-learn and scikit-image. A user-friendly interface for classifying test images was also included, demonstrating the proposed system's usefulness. © 2025 IEEE.

关键词： Adversarial machine learning

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