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The Comparison of Password Composition Policies Among US, German, and Thailand Samples 20

The Comparison of Password Composition Policies Among US, Ge...

引用

20th International Joint Conference on computer science and Software Engineering, JCSSE 2023

作者： Lomchan, Jenjira Wiangsripanawan, Rungrat Shahandashti, Siamak F. School of Science King Mongkut's Institute of Technology Ladkrabang Dept. of Computer Science Bangkok Thailand University of York Dept. of Computer Science York United Kingdom

ISBN: (纸本)9798350300505

The study by Mayer, Kirchner, and Volkamer published at SOUPS 2017 showed that the password composition policy (PCP) strength of both the US and German websites was not influenced by the security but by the usability features of the websites. Surprisingly, the PCP strength of the banking website category was the lowest, whereas the government website was the highest. Our aim in conducting the first study is to find whether 78 Thai frequently used websites in 2018 would yield the same surprising results. Our finding showed an opposite perspective, the highest PCP strength was from the banking websites, followed by university and government websites, respectively. Two more security features were added to our study: 2FA and HTTPS. Although some German websites employing 2FA allowed lower PCPs for better usability, Thai websites with 2FA did not loosen the password requirements. Also, employing HTTPS did not impact the PCP strength. The study with Thai websites was reinvestigated in 2021, two years after the Personal data Protection Act (PDPA) was announced. The result showed that the median PCP strength of all Thailand samples had grown from 26.6 in 2018 to 31.0 in 2021. The banking websites still retained the highest PCP strength. A significant change appeared on the government websites, increasing from 29.9 to 40.4. In summary, the security features such as the size of services, and values of assets which play no part in both the US and German PCPs were heavily concerned by Thai websites. Government and university websites in Germany and USA gave much higher PCP strength than those in Thailand. The Thai government's PCP strength sharply increased in 2021 due to the privacy law. Nevertheless, it was still lower than the results in Germany and USA in 2016. Therefore, the criteria influencing PCP vary depending on the country. © 2023 IEEE.

关键词： Websites

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Voice AI-Intelligence Based Voice Assistant 3

Voice AI-Intelligence Based Voice Assistant

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Garai, Pooja Nikam, Aditya Kerkar, Suyash Deshmukh, Samruddhi Mane, Atharva Bhise, Suvarna Vasantdada Patil College Of Engineering & Visual Arts Dept. of Artificial Intelligence & Data Science Mumbai India

ISBN: (纸本)9798331515911

Voice assistant applications have become integral parts of modern technology ecosystems, offering users convenient and efficient ways to interact with their devices. This paper introduces Voice Ai, a versatile voice assistant application developed using Android Studio and Google's Machine Learning Kit Machine learning(MLKit) for Optical Character Recognition (OCR) functionalities. The app includes features like setting alarms, making calls, opening applications, and conducting question-answer sessions powered by G4F. A comparative analysis between G4F and Google's backend is performed, assessing their performance and user satisfaction during question-answer interactions. Voice Ai simplifies daily tasks and boosts productivity, providing insights for developers, researchers, and end-users interested in AI-based voice assistant applications. © 2025 IEEE.

关键词： Adversarial machine learning

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Bibliometric Analysis of IoT Application Research: Unveiling Trends and Future Directions for Terahertz Communication in Wireless Systems 4

Bibliometric Analysis of IoT Application Research: Unveiling...

引用

4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Hajoary, Deepak Basumatary, Rinku Narzary, Raju Dept. of Management Studies Assam Kokrajhar India Dept. of Computer Science and Technology Assam Kokrajhar India

ISBN: (纸本)9798350387490

This abstract presents a bibliometric analysis of IoT application research, focusing on unveiling trends and future directions in the field of terahertz communication for wireless systems. The study employs bibliometric techniques to analyze and assess the existing literature on IoT applications, with a specific emphasis on terahertz communication. By examining the publication trends, citation patterns, and collaboration networks, this research provides valuable insights into the current state of terahertz communication in the context of IoT. The findings highlight the emerging applications, key research areas, and potential challenges in terahertz communication for wireless systems. This bibliometric analysis serves as a roadmap for researchers and industry professionals interested in further advancing the field, shaping the future of IoT applications with terahertz communication technologles. © 2024 IEEE.

关键词： 5G mobile communication systems

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Uncovering Linguistic Patterns: Exploring Ensemble Learning and Low-Level Features for Identifying Spoken Arabic, English, Spanish, and German 5

Uncovering Linguistic Patterns: Exploring Ensemble Learning ...

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5th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2023

作者： Hamdi, Skander Moussaoui, Abdelouahab Chabane, Mafaza Laouarem, Ayoub Berrimi, Mohamed Oussalah, Mourad University of Ferhat Abbes Setif 1 Dept. of Computer Science Setif Algeria University of Oulu Dept. of Computer Science Oulu Finland

ISBN: (纸本)9798350381450

This paper presents a novel approach to spoken language identification in Arabic, English, Spanish, and German languages using ensemble learning techniques. The study compares the performance of two well-known ensemble learning algorithms (Random Forest and XGBoost). Next, a Stacking Ensemble method with Logistic Regression is used as a meta-model, which combines the predictions of two configurations of Random Forest and two other configurations of XGBoost. We explore the utilization of the audio Low-Level Descriptors features, which have previously received limited attention in spoken language identification. Experimental results demonstrate the effectiveness of the ensemble learning algorithms, achieving high accuracy in accurately classifying spoken languages. Notably, the Stacking Ensemble method showcases its ability to reduce misclassification rate, emphasizing its potential for performance improvement. The stacking Ensemble method achieved the highest recorded classification rate of 97.22%, outperforming individual methods. © 2023 IEEE.

关键词： Learning systems

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Enhanced Multimodal Biometric Fusion with DWT, LSTM, and Attention Mechanism for Face and Iris Recognition

Enhanced Multimodal Biometric Fusion with DWT, LSTM, and Att...

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2024 IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2024

作者： Vannurswamy, K. Shekar, B.H. Pilar, Bharathi Karunakar Kotegar, A. Jiang, Frank Mangalore University Dept of Computer Science Mangalore India Mangalore University Dept of Computer Science Konaje Mangalore India University College Mangalore Dept of Computer Science Mangalore India Mahe Manipal Dept of Data Science Manipal India Deakin University School of Information Tech Melbourne Australia

ISBN: (纸本)9798350376876

This paper introduces a new multimodal biometric system integrating facial and iris recognition using discrete wavelet transform (DWT) and long short-term memory (LSTM) neural networks enhanced with an attention mechanism. DWT is effective in extracting global and local features, and these extracted traits are addressed as instances of serial data to enable LSTMs to pick temporal connections in and provide context-specific continuations with continual regularity;other than these factors, improvement of the features has a major impact because attention emphasizes exactly on where more contextual contribution would occur with these elements to allow further contextual insights during the output phase. Experimental results show commendable gains in performance as compared with conventional systems, and achieves identification of up to 9 9. 9 4 %. It can be utilized in security environment where accurate identification with biometrics and proper authentication is highly needed. Framework: Features acquired from the DWT are integrated inside an LSTM network. Thus, it provides guidelines for both the structured feeding schedule and the organizing of time data, thus better facilitating biometric recognition. Though some progress has been made in optimizing biometric identification for individuals with varied features, there is still much to be done. © 2024 IEEE.

关键词： Authentication

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AI Driven Brain Tumor Classification and Localization using Faster R-CNN 8

AI Driven Brain Tumor Classification and Localization using ...

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8th International Conference on Inventive Computation Technologies, ICICT 2025

作者： Gospelin Reena, E. Kavitha, T. Dept. of Computer Science and Engineering Karunya University coimbatore India Dept. of Computer Science and Engineering Karunya University coimbatore India

ISBN: (纸本)9798331512248

The increasing prevalence of brain tumors necessitates the development of accurate, automated methods for early diagnosis and localization. Traditional approaches, which rely on manual MRI interpretation by radiologists, are prone to errors due to varying expertise levels and limited resources. To overcome these limitations, this study proposes an AI-driven solution for brain tumor classification and localization using Faster R-CNN, a deep learning architecture known for its robust object detection capabilities. The proposed model utilizes public MRI datasets to train a Faster R-CNN model, which effectively identifies and locates brain tumors with high precision. The model's performance is evaluated using standard metrics such as accuracy, precision, recall, F1-score, and Intersection over Union (IoU), demonstrating superior results compared to conventional methods. A user-friendly web-based interface developed using Streamlit allows radiologists to upload MRI images and receive real-time diagnostic results, enhancing clinical workflows. Despite its high performance, the study acknowledges the need for improvements in image resolution and model interpretability. Future work will explore the integration of 3D MRI data and explainable AI techniques to further enhance the model's transparency and clinical applicability. © 2025 IEEE.

关键词： Artificial Intelligence Brain Tumor Detection Deep Learning Faster R-CNN Medical Imaging MRI Classification Region Proposal Network

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Navigator: A Decentralized Scheduler for Latency-Sensitive AI Workflows 8

Navigator: A Decentralized Scheduler for Latency-Sensitive A...

引用

8th IEEE International Conference on Edge Computing and Communications, EDGE 2024

作者： Yang, Yuting Merlina, Andrea Song, Weijia Yuan, Tiancheng Birman, Ken Vitenberg, Roman Cornell University dept. Computer Science Ithaca United States University of Oslo dept. Informatics Norway

ISBN: (纸本)9798350368499

We consider AI inference and generative query processing in distributed systems: an increasingly popular edgecomputing use case. In such systems, coscheduling of GPU memory management and task placement represents a promising opportunity. We propose Navigator, a novel framework that unifies these functions to reduce job latency while using resources efficiently, placing tasks where data dependencies will be satisfied collocating tasks from the same job (when this will not overload the host or its GPU), and efficiently managing GPU memory Comparison with other state of the art schedulers shows a significant reduction in completion times while requiring the same amount or even fewer resources. In one case, just half the servers were needed for processing the same workload. © 2024 IEEE.

关键词： Memory management

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Theta-λ Optimization for Network Performance in Rician Fading and Multi-User Interference Scenarios 4

Theta-λ Optimization for Network Performance in Rician Fadi...

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4th International Conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Upadhyay, Deepak Sharma, Kunj Bihari Dhondiyal, Shiv Ashish Venu, Nookala Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (纸本)9798331530402

In this paper, an investigation into the application of Theta-λ optimization strategies to improve network performance is made in a challenging wireless communication systems environment subject both Rician fading and multi-user interference (MUI). This paper discusses the dynamic adjustments of Theta (angle-of-arrival) and λ parameters necessary to balance system resiliency against high throughput. We did some simulations to test the performance in terms of latency, throughput as well as accuracy using values such frequency stability and jitter. The results show strong enhancements after the optimization - latency: from a mean of 20 ms to stabilizing at 15ms, throughput: dramatically enhanced from existing baseline of around ~50 to 100 Mbps with enhancement between ~70-120Mbps while maintaining range and jitter reduction halved as average jitter is now less than two milliseconds compared previous Jitter at an optimal value. This had the added benefit of improvements in frequency stability: now, instead of hovering around 2.4 GHz like when we first tested it out-of-the-box, average was up to 2.5 GHz after optimization as well! The results of this study illustrate the potential for enhanced network reliability and availability through fading and interferer mitigation using Theta-λ optimization. This case study is representative of the relevance for real-time adaptive optimization techniques in current-day telecommunications given surging demands on resilient wireless connectivity. Further research directions include enhancement of the optimization algorithms depending on specific network conditions and integration with adaptive strategies for real-time delivery using QoE-oriented mechanisms. © 2025 IEEE.

关键词： Fading MUI Rician Theta-λ Wireless

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Device Identification using Network Traces in a Smart Home IoT Network 17

Device Identification using Network Traces in a Smart Home I...

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17th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Brahma, Jwngfu Matam, Rakesh Choudhury, Nikumani Indian Institute of Information Technology Dept. of Computer Science & Engineering Guwahati India Birla Institute of Technology & Science Dept. of Computer Science & Information Systems Hyderabad India

ISBN: (纸本)9798350307672

Device identification is a crucial aspect of securing networks, particularly in the context of the Internet of Things (IoT), where a vast variety of devices are interconnected. Recently, there has been significant research on developing techniques for identifying IoT devices based on their unique characteristics, called as device fingerprints. These techniques use machine learning algorithms, which can effectively learn and classify devices based on their features. However, device identification remains a challenging task due to the diversity of IoT devices and the constant evolution of their characteristics. This paper presents our attempt at device identification by analyzing distinct device characteristics observed during network communication and using different machine learning techniques. © 2023 IEEE.

关键词： Internet of things

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An Artificial Intelligence Approach in 5G New Radio Beam Enhancement 3

An Artificial Intelligence Approach in 5G New Radio Beam Enh...

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3rd International Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Upadhyay, Deepak Mittal, Saksham Jain, Ayushi Sharma, Ravi Bagla, Piyush Tripathi, Neha Tiwari, Pallavi Graphic Era Hill University Dept. of Computer Science & Engineering Uttarakhand Dehradun India National Institute of Technology Computer Science & Engineering Dept. Punjab Jalandhar India Dept. of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350300710

The paper presents a novel application of artificial neural networks in the context of 5G new radio beamforming. The research leverages the intricate mechanism of ANNs to demonstrate the efficacy of this approach in optimizing the beamforming process and improving the overall performance of the 5G new radio system. The utilization of ANNs allows for real-time adaptation and decision-making, thereby mitigating the limitations of conventional beamforming techniques. The results of the study are quite promising, indicating a substantial enhancement in the accuracy and efficiency of beamforming in 5G new radio. The proposed method is expected to have a significant impact on the development of advanced wireless communication systems. © 2023 IEEE.

关键词： Beamforming

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