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Informatica (Slovenia) 2025年第11期49卷 165-176页

作者： Ilias, Shaik Mohammad Sharmila, V. Ceronmani Durga, V. Sathya Dept. of Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India Department of Information Technology Hindustan Institute of Technology and Science Chennai India Department of Computer Science&Engineering Hindustan Institute of Technology and Science Chennai India

If adversaries were to obtain quantum computers in the future, their massive computing power would likely break existing security schemes. Since security is a continuous process, more substantial security schemes must be developed. Current PQC schemes primarily focus on data security or key exchange, and further improvement towards enhanced PQC primitives is required. Our proposal in this research is an innovative paradigm for PQC-focused cloud data security. The proposed HEDT approach achieves encryption and decryption with significantly lower latency (20% improvement) and higher reliability than AES, DES, and RSA, as demonstrated through experimental results. Furthermore, ECSIDH, a hybrid key exchange mechanism combining SIDH and ECDH, improves security strength by 50% while maintaining computational costs within 1.13x of SIDH. Compared to individual key exchange schemes like SIDH, ECSIDH offers superior security as a PQC candidate. These results confirm the robustness and efficiency of the proposed framework in ensuring secure data outsourcing and key exchange in cloud environments. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Quantum computers

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Role of IoT in Smart Cities: A Review, Applications, Open Challenges and Solutions 3

Role of IoT in Smart Cities: A Review, Applications, Open Ch...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Vivek, Kolla Swetha, Gurrala Kumar M, V. T. Ram Pavan Veni, Anusuri Krishna Praveen, Neti Kale, Masthan Rao Dept. of Cse Andhra Pradesh Ongole India Dept. of Cse Telangana India Kakaraparti Bhavanarayana College Dept. of Computer Science Andhra Pradesh Vijayawada India Madanapalle Institute of Technology & Science Dept. of Computer Science & Engineering - Data Science Andhra Pradesh Madanapalle517325 India Srkr Engineering College Dept. of Computer Science and Design Andhra Pradesh Bhimavaram India Dept. of Cse Andhra Pradesh Ongole India

ISBN: (纸本)9798331509675

Smart cities have emerged as a response to the fast expansion of metropolitan areas;these places strive to improve the lives of their residents while simultaneously promoting environmentally responsible growth. To maximize urban services, the Internet of Things (IoT) is an essential technology that allows for the seamless integration of sensors, devices, and systems. This allows smart cities to become a reality. With an emphasis on smart transportation, energy management, healthcare, environmental monitoring, and public safety, this paper explores the critical role of IoT in smart cities. data security, privacy, scalability, and interoperability are some of the problems that arise when smart cities use IoT, despite the revolutionary potential it has. These obstacles are thoroughly examined in this work, along with possible solutions to these problems. This study gives a thorough overview of the IoT and its impact on smart city development, innovation, and urban resilience by focusing on the present situation, applications, and unanswered questions. © 2025 IEEE.

关键词： Digital Technology Drainage Monitoring Fire detection Smart City Waste Management

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Enhancing Software Effort Estimation with Ant Colony Optimization Algorithm and Fuzzy-Neural Networks 3

Enhancing Software Effort Estimation with Ant Colony Optimiz...

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3rd International Conference on Distributed Computing and High Performance Computing, DCHPC 2024

作者： Afshari, Mahnaz Gandomani, Taghi Javdani Shahrekord University Data Science Research Group Shahrekord Iran Shahrekord University Dept. Computer Science Shahrekord Iran

ISBN: (纸本)9798350381580

Software effort estimation remains a persistent challenge and requires serious attention in the early stages of software project management. Inherent uncertainties arising from incomplete and inaccurate requirements pose a significant barrier to reliable estimations. Despite numerous efforts and various techniques proposed for cost estimation, the pursuit of improving estimation accuracy remains essential. In response to this challenge, this study introduces a novel model that integrates an Adaptive Neuro-Fuzzy Inference System with the Ant Colony Optimization algorithm. The model is further compared with well-known evolutionary algorithms such as Differential Evolution, Genetic Algorithm, Artificial Neural Network, and Particle Swarm Optimization. Applying the proposed model to popular software effort estimation datasets, including Albrecht, Desharnais, and Kemerer, demonstrates its superiority over the mentioned algorithms. The improved estimation provided by this model can assist software project managers in better project cost estimation. © 2024 IEEE.

关键词： Fuzzy neural networks

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IIoT-based Realtime Environmental Monitoring System for an Underground Coal Mines 15

IIoT-based Realtime Environmental Monitoring System for an U...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Thirumal, G. Gautam, Vivek Kumar Kumar, Chiranjeev Seth, Himanshu Ranjan Bodra, Shaily Priyanka Dept. Computer Science and Engg. Jharkhand Dhanbad India Data Science Oyo Vacation Homes Lucknow India

ISBN: (纸本)9798350370249

Underground coal mines are harsh in the working environment, which leads to more causality. Therefore, modern mines are using sensor networks to monitor the mines regularly to minimize mine accidents. Hence, very limited real-time monitoring systems are developed using a Real-time operating system (RTOS). Contiki-NG is a popular embedded application development framework for Wireless sensor networks and the internet of things (IoT). This paper provides a detailed roadmap to design a real-time monitoring system for underground coal using Contiki-NG. The System design comprises designing sensor node with modified RPL protocol and border router using TI CC2650 launchpad and raspberry pi 3. The Node-RED middleware collects data from the application environment using a sensor node. Store the data into the MongoDB database and visualizes sensed data in a web browser in the monitoring center. © 2024 IEEE.

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An Architecture for Dynamic Load Balancing in Cloud Environment 2

An Architecture for Dynamic Load Balancing in Cloud Environm...

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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Lokesh, Gudivada Baseer, K.K. Dept. of Computer Science and Engineering Tirupati India Department of Data Science Tirupati India

ISBN: (纸本)9798350347579

Clouds are highly customizable infrastructures that offer a platform as a service and let customers subscribe on a pay-as-you-go basis to their requirements. The straightforward service-oriented cloud computing model is gaining popularity around the world. The number of people using the Cloud is constantly growing. Clouds use modern data centers to manage a massive number of users. The reliability of the Cloud depends on load balancing. Balancing virtual machine loads lowers energy consumption and task rejections by optimizing resource utilization. One can increase performance while using fewer resources using load balancing, resource management, quality of service, etc. The difficulty of overloading and underloading virtual machines in cloud computing can be lessened by load balancing in the *** research study thoroughly examined the load-balancing algorithms found in the literature. First, the traditional approaches are analyzed before moving on to more recent work on load balancing with heterogeneous techniques. Along with the tools available for the current investigation, various metrics are used to evaluate the load-balancing algorithms. The proposed article will primarily serve to assist in the development of new algorithms in the future. © 2023 IEEE.

关键词： Energy utilization

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Enhancing Application Placement in Cloud-Fog Environment Based on Multicriteria Decision Making 3

Enhancing Application Placement in Cloud-Fog Environment Bas...

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3rd International Conference on Advanced Electrical Engineering, ICAEE 2024

作者： Arichi, Bochra Amraoui, Asma Dept. Computer science Tlemcen13000 Algeria Dept. Computer science Tlemcen13000 Algeria

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349351

Fog computing (FC) is a distributed infrastructure computing that extends cloud computing (CC) capabilities to the edge of the network, closer to where data is generated and consumed. This approach responds to the challenges caused by Internet of Things (IoT) applications, which generate massive amounts of data that are costly and time-consuming to send to the cloud for processing. By leveraging fog computing, the cloud's limitations were successfully addressed, such as unpredictable latency. However, this shift introduced a new challenge. One of these challenges is finding the best placement of applications on distributed fog devices. This paper outlines a study aimed at addressing this challenge by utilizing multi-criteria decision-making (MCDM) techniques, including the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This study aims to choose the most appropriate fog nodes for positioning and processing application modules. The simulation was carried out on the iFogSim simulator, and the findings indicate that the suggested technique provides significant improvements in placement time and latency in a fog computing environment. © 2024 IEEE.

关键词： Fog computing

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SRGB REAL NOISE MODELING VIA NOISE-AWARE SAMPLING WITH NORMALIZING FLOWS 12

SRGB REAL NOISE MODELING VIA NOISE-AWARE SAMPLING WITH NORMA...

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12th International Conference on Learning Representations, ICLR 2024

作者： Kim, Dongjin Jung, Donggoo Baik, Sungyong Kim, Tae Hyun Dept. of Computer Science Hanyang University Korea Republic of Dept. of Artificial Intelligence Hanyang University Korea Republic of Dept. of Data Science Hanyang University Korea Republic of

Noise poses a widespread challenge in signal processing, particularly when it comes to denoising images. Although convolutional neural networks (CNNs) have exhibited remarkable success in this field, they are predicated upon the belief that noise follows established distributions, which restricts their practicality when dealing with real-world noise. To overcome this limitation, several efforts have been taken to collect noisy image datasets from the real world. Generative methods, employing techniques such as generative adversarial networks (GANs) and normalizing flows (NFs), have emerged as a solution for generating realistic noisy images. Recent works model noise using camera metadata, however requiring metadata even for sampling phase. In contrast, in this work, we aim to estimate the underlying camera settings, enabling us to improve noise modeling and generate diverse noise distributions. To this end, we introduce a new NF framework that allows us to both classify noise based on camera settings and generate various noisy images. Through experimental results, our model demonstrates exceptional noise quality and leads in denoising performance on benchmark datasets. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Generative adversarial networks

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Understanding the Impact of News Articles on the Movement of Market Index: A Case on Nifty 50

Understanding the Impact of News Articles on the Movement of...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Dasgupta, Subhasis Satpati, Pratik Choudhary, Ishika Sen, Jaydip Praxis Business School Dept. of Data Science Kolkata India Praxis Tech School Dept. of Data Science Kolkata India

ISBN: (纸本)9798331540821

In the recent past, there were several works on the prediction of stock prices using different methods. Sentiment analysis of news and tweets and relating them to the movement of stock prices have already been explored. But, when we talk about the news, there can be several topics such as politics, markets, sports etc. It was observed that most of the prior analyses dealt with news or comments associated with particular stock prices only or the researchers dealt with the overall sentiment scores only. However, it is quite possible that different topics have different levels of impact on the movement of the stock price or an index. The current study focused on bridging this gap by analysing the movement of Nifty 50 index with respect to the sentiments associated with news items related to various different topic such as sports, politics, markets etc. The study established that sentiment scores of news items of different other topics also have a significant impact on the movement of the index. © 2024 IEEE.

关键词： Marketplaces

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Leveraging XAI and Breakthrough Machine Learning Techniques for Trigeminal Neuralgia Severity Classification

Leveraging XAI and Breakthrough Machine Learning Techniques ...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Abhijna, M.B. Akul, P. Kodipalli, Ashwini Global Academy of Technology Dept. of Information Science and Engineering India Global Academy of Technology Dept. of Computer Science and Engineering India Global Academy of Technology Dept. of Artificial Intelligence and Data Science India

ISBN: (纸本)9798350364866

Trigeminal Neuralgia (TN) is a debilitating chronic pain disorder that significantly diminishes overall well-being, making diagnosis and therapy more challenging. The quick and precise categorization of TN severity is critical to therapy effectiveness. To assess the severity of TN, this study makes use of advanced machine learning techniques and explainable AI (XAI) approaches. We use a range of bagging and boosting strategies, including AdaBoost, Random Forest, Decision Tree, K-Nearest Neighbours (KNN), Gradient Boosting, and Logistic Regression. Random Forest was 95.2% accurate, whereas AdaBoost and Gradient Boosting were 92% and 97.2% in terms of their accuracy. The Decision Tree classifier obtained an accuracy of 84.62%, while K-Nearest Neighbours and Logistic Regression also achieved 92.31% accuracy. F1- score, precision, and recall metrics were used to assess performance on a dataset that included patient demographics and medical histories. XAI techniques, such as LIME and SHAP values, were used to improve the models' readability and transparency, which helped to progress the creation of cutting-edge diagnostic tools and increase clinician and researcher confidence. © 2024 IEEE.

关键词： Logistic regression

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A Number of Conceptual Scalable Node-Organizing Multi-Tiered Blockchain Architectures for IoT 17

A Number of Conceptual Scalable Node-Organizing Multi-Tiered...

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IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart data, Smartdata 2024

作者： Elsaadany, Riham Bégin, Guy Computer Science Dept. Canada

ISBN: (纸本)9798350351637

The high volume and rapid pace of transactions generated by IoT devices pose challenges for current blockchain designs, which typically employ flat or two-tiered node organizations. These models often lack the scalability, throughput, and consensus efficiency required for the IoT environment. This study proposes a multi-tiered clustered design concept that enhances blockchain scalability and efficiency. We compare our approach with flat and two-tiered models to demonstrate its viability. Central to our design is a node lookup and message routing mechanism, coupled with a consensus-accelerating protocol. Transaction, block verification, and creation processes involve a logarithmically bounded number of nodes per tier, improving consensus time and scalability as tier levels increase. The design concept maintains a balance between consensus decentralization and node overhead capacity, ensuring scalability and security. This design concept can be implemented using various algorithmic approaches to produce multiple proposed architectures, all leveraging the consensus-accelerating protocol. Simulations performed on one of the architectures provide solid proof of concept, demonstrating improved performance over flat and two-tier models. The proposed mechanisms provide general-purpose scalability, load balancing, node lookup, and message routing solutions, and are application- and consensus-algorithm-agnostic. © 2024 IEEE.

关键词： Efficiency

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