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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Abdulfattah E. Ba Alawi Ferhat Bozkurt Mete Yağanoğlu Computer Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Software Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Based on the time of writing, Arabic poems are divided into eras or periods. Each era has its poetic properties that characterize its poems. The classification of poems and literary texts into eras using conventional Natural Language Processing (NLP) techniques and computerized methods is a challenging task. To overcome this problem, this paper uses a modified version of the Bidirectional Encoder Representations from Transformers (BERT) model to classify Arabic poems. The proposed model was modified to better comprehend and classify the rich grammatical and stylistic features of Arabic poetry. We modified the Multilingual Arabic variants of BERT (MARBERT) by adding pooling, dropout, and classification layers and training it on a large corpus of Arabic poetry from different genres. Additionally, linguistic and rhyme features were employed to enhance the performance. The objective of this method is to offer the model a sophisticated comprehension of the theme and poetry phrases in Arabic poems. The suggested model performs more effectively in categorizing Arabic poetry with an accuracy of 86.82%. The findings illustrated that Arabic literary text analysis and classification can be automated and emphasized the significance of language-specific optimization for transformer-based models designed to tackle challenging categorization of textual data.

关键词： Training Text analysis Computational modeling Bidirectional control Writing Transformers Natural language processing

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Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

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computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul Haq Muhammad Asif Shehzad Ashraf Chaudhry Taeshik Shon Graduate School of Engineering Science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer Science Lahore Garrison UniversityLahore54920Pakistan Department of Computer Science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC

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SPUFChain: Permissioned Blockchain Lightweight Authentication Scheme for Supply Chain Management Using PUF of IoT

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IEEE Access 2025年 13卷 88662-88682页

作者： Assaqty, Mohammad Iqbal Saryuddin Gao, Ying Alqarni, Abeer D. Khan, Siraj Chakraborty, Mohuya Nur Siddiqi, Hafied Ahmad, Sadique South China University of Technology School of Computer Science and Engineering Guangzhou510006 China Universitas Nahdlatul Ulama Indonesia Faculty of Engineering and Computer Science Jakarta10320 Indonesia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Technology P.O. Box 84428 Riyadh11671 Saudi Arabia Research Institute for Future Media Computing College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China University of Engineering and Management Cybersecurity Centre of Excellence Kolkata700160 India Riyadh12435 Saudi Arabia

The complexity of the entire process of supply chain management (SCM) is quite cumbersome and traditional way of handling it is devoid of proper authentication and security and very often suffers from human errors in dealing with flaws in quality control process of SCM. While it may have started with shipment tracking, the outcome of using IoT on supply chains has spread to every link in the chain. For instance, manufacturers are employing Internet-enabled sensors in production to find product faults, resulting in higher-quality production runs. Physical Unclonable Function (PUF) is a defense countermeasure that exploits the exclusive, unrepeatable features of hardware components to generate distinct cryptographic keys or identifiers, typically for a semiconductor device like an Internet of Things (IoT) device. The distinctive proof of identity of IoT devices in the supply chain is employed by means of PUFs as inviolable IDs. Blockchain, the distributed, immutable ledger, on the other hand is the disruptive technology that provides higher security as compared to traditional centralized systems. The integration of PUF and blockchain proves to be quite interesting while handling the above issues of authentication. A smart contract on the blockchain is a software code that executes spontaneously as and when the conditions of the contract or agreement are satisfied. Hence after authentication process the results are fed to blockchain smart contract for the final validation. This paper presents a novel permissioned blockchain smart contract-based lightweight authentication scheme for SCM using PUF of IoT known as SPUFChain. Informal and formal security analysis (using AVISPA and BAN logic) of the proposed framework show its efficiency to resist several threat scenarios like man-in-the middle, non-repudiation, impersonation, replay attacks and many other security features as compared to other related schemes. The processing time (~13.8ms) is better than existing lightweig

关键词： Supply chain management

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Research and development of an information system for speech recognition based on neural network algorithms metrics 4

Research and development of an information system for speech...

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4th IEEE International Conference on Smart Information Systems and Technologies, SIST 2024

作者： Kanashev, Maksat Mukasheva, Assel Yedilkhan, Didar Rakhmetulaeva, Sabina Gnatyuk, Sergiy Nazym, Mirambayeva Almaty University of Power Engineering and Telecommunications Almaty Kazakhstan The School of Information Technology and Engineering Kazakh-British Technical University Almaty Kazakhstan The Department of Computer Engineering Astana IT University Astana Kazakhstan The Department of Information Systems International University of Information Technologies Almaty Kazakhstan The Faculty of Cybersecurity Computer and Software Engineering National Aviation University National Aviation University Kyiv Ukraine

ISBN: (纸本)9798350374865

This article examines the parameters of speech recognition in audio recordings containing a variety of phrases uttered by different people with different accents and intonations. The aim of the study is to evaluate the recognition speed, the accuracy of audio-to-text conversion and resource consumption when using SpeechRecognition and Levenshtein libraries. During the analysis, the above libraries were used to record and recognize audio files, as well as to calculate the distance between two lines and determine the recognition accuracy. The findings of this study can be useful for improving speech recognition systems and creating more adaptive and efficient solutions for audio data processing. The results of comparing the accuracy of speech recognition models are recorded in JSON format, after which, using the matplotlib library, they are visualized as graphs, comparing the speed and accuracy of recognition. Visualization of data in this way contributes to their improvement and more effective integration into educational systems. In conclusion, the authors emphasize the prospects for further development of speech recognition technologies in different fields. © 2024 IEEE.

关键词： Audio recordings

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Towards a Conceptual Model for Assessing User Satisfaction in Metaverse-Based Learning 11

Towards a Conceptual Model for Assessing User Satisfaction i...

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11th International Conference on Information Technology, ICIT 2023

作者： Alhalaybeh, Awf Althunibat, Ahmad Al-Mahadeen, Bassam M. Habashneh, Khaldoun Khalil Daradkeh, Ali Mohammad Software Engineering Al-Zaytoonah University of Jordan Madaba Jordan Software Engineering Al-Zaytoonah University of Jordan Amman Jordan Mu'Tah University Department of Computer Science Alkarak Jordan Faculty of Arts Amman Jordan Amman Jordan

ISBN: (纸本)9798350320060

this paper proposes a conceptual model for assessing user satisfaction in metaverse-based learning, a novel field that utilizes virtual reality technology to create an immersive and interactive learning experience. Despite the growing popularity of metaverse-based learning, there is a lack of research on how to evaluate user satisfaction in this type of learning environment. The proposed model includes four factors: Perceived Trialability, Perceived Observability, User Compatibility, and Perceived Complexity, each of which can be measured using statistical methods. The study aims to address the research gap in evaluating user satisfaction in metaverse-based learning and provides a model for educators and researchers to assess and improve user satisfaction in this innovative learning environment. The findings of this study contribute to the growing body of literature on metaverse-based learning and provide insights into the unique challenges associated with implementing this technology in educational settings. © 2023 IEEE.

关键词： Learning systems

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Key protected deputy signature scheme against the deputy signing key exposure

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International Journal of Circuits, Systems and Signal Processing 2021年 15卷 800-808页

作者： Chen, Jianhong Yu, Kun Wang, Wenhao Faculty of Computer and Software Engineering Huaiyin Institute of Technology Jiangsu Huaian223003 China

Key exposure is very harmful to a cryptographic system. To decrease the loss from the deputy signing key vulnerability in identity-based proxy signature systems, we propose the method of key protected deputy signature (IBKPDS) using the method of parallel key insulation. The proposed IBKPDS is based on identities and is shown to be secure with the cryptographic proof. In the proof, there is no random oracle. In an IBKPPS crypto-system, a user stores his short-lived deputy signing key by himself and saves two long-lived keys in two heavily guarded boxes respectively. The derived IBKPDS cryptographic system is heavily key-separated. A thief who wants to obtain crucial information can not corrupt the IBKPDS when he get only one long-lived key. In addition, the user can change the short-lived deputy signing keys frequently at low risk. © 2021, North Atlantic University Union NAUN. All rights reserved.

关键词： Cryptography

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A Security Enhanced Chaotic-Map-Based Authentication Protocol for Internet of Drones

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IEEE Internet of Things Journal 2024年第12期11卷 22301-22309页

作者： Mahmood, Khalid Ghaffar, Zahid Farooq, Muhammad Yahya, Khalid Das, Ashok Kumar Chaudhry, Shehzad Ashraf National Yunlin University Of Science And Technology Graduate School Of Intelligent Data Science Douliu64002 Taiwan National Yunlin University Of Science And Technology Graduate School Of Engineering Science And Technology Douliu64002 Taiwan Abu Dhabi University Department Of Mathematics And Statistics College Of Arts And Sciences Abu Dhabi United Arab Emirates Istanbul Gelisim University Department Of Electrical And Electronics Engineering Istanbul34310 Turkey Sabratah University Department Of Electrical Engineering Faculty Of Engineering Regdalen Libya Center For Security Theory And Algorithmic Research Hyderabad500 032 India Abu Dhabi University Department Of Computer Science And Information Technology College Of Engineering Abu Dhabi United Arab Emirates Nisantasi University Faculty Of Engineering And Architecture Department Of Software Engineering Istanbul34398 Turkey

The Internet of Drones (IoD) extends the capabilities of unmanned aerial vehicles, enabling them to participate in a connected network. In IoD infrastructure, drones communicate not only among themselves but also with users and a control center. This interconnected communication framework holds promise for various applications, from collaborative decision-making to real-time data exchange. However, the expansion of communication in IoD also introduces new challenges, particularly in terms of security, privacy and authentication. Unfortunately, the current authentication protocols are inadequate in offering robust security features against various attacks in the IoD environment. To address these security issues and limitations, we proposed a secure protocol for the IoD environment using chaotic maps and hash functions. In addition, we also employed a physically unclonable function in the development of the proposed protocol. We assess the security of the protocol through both informal and formal security analysis. The formal security analysis is conducted through a widely used random or real (RoR) model. The informal analysis shows the rigorous security features against various attacks, such as masquerading, anonymity violation, and physical cloning attacks. Moreover, we compare the performance of the devised protocol with similar existing protocols across important performance parameters, such as communication overhead, computation overhead, and security features. The devised protocol provides a 67.86% and 17.80% reduction in computation and communication overheads, respectively, as compared to related protocols. The analysis demonstrates the proposed protocol's capacity to support secure communication in the IoD environment and satisfy desirable security attributes. © 2014 IEEE.

关键词： Drones

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Smartphone-Based Artificial Intelligence System for Real-Time Exercise Rep Counting

SSRN

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SSRN 2024年

作者： Sinclair, Adam Kautai, Kayla Shahamiri, Seyed Reza Department of Electrical Computer and Software Engineering Faculty of Engineering The University of Auckland Auckland New Zealand

Automated exercise repetition counting has applications across the physical fitness realm, from personal health to rehabilitation. Motivated by the ubiquity of mobile phones and the benefits of tracking physical activity, this study explored the feasibility of counting exercise repetitions in real time, using only on-device artificial intelligence inference. In this work, after providing an extensive overview of the state-of-the-art automatic exercise repetition counting methods, we introduce a deep learning based exercise repetition counting system for smartphones consisting of five components: (1) Pose Estimation, (2) Thresholding, (3) Optical flow, (4) State machine, and (5) Counter. The system is then implemented via a cross-platform mobile application that uses only the smartphone camera to track repetitions in real time for three standard exercises: Squats, Push-ups, and Pull-ups. The proposed system was evaluated via a dataset of pre-recorded videos of individuals exercising and tested by subjects exercising in real time. Evaluation results indicated that the system achieved 92.78% mean accuracy in real-world tests and 86.04% absolute accuracy when evaluated via the pre-recorded dataset. This makes it an effective, low-cost, and convenient alternative to existing solutions since the proposed system has minimal hardware requirements without requiring any wearable or specific sensors or network connectivity. © 2024, The Authors. All rights reserved.

关键词： Smartphones

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Exploring Compositional Neural Networks for Real-Time Systems

Exploring Compositional Neural Networks for Real-Time System...

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ACM and IEEE International Conference on Formal Methods and Models for Co-Design (MEMOCODE)

作者： Sobhan Chatterjee Nathan Allen Nitish Patel Partha Roop Department of Electrical Computer and Software Engineering Faculty of Engineering University of Auckland Auckland New Zealand

ISBN: (数字)9798350378023

ISBN: (纸本)9798350378030

Real-time CPSs using Artificial Neural Networks (ANNs) are traditionally developed as monolithic black-boxes. This results in designs that are often difficult to formally verify against safety specifications and implement on hardware for formal timing analysis. Consequently, their implementation as a composition of smaller ANNs has received recent interest. These are easier to implement, parallelise and validate. Despite this, the question of how to produce hardware-implementable compositional designs from existing monolithic ones remains largely unanswered. This work develops a novel procedure to replace large ANN monolithic designs with smaller compositional designs and implement them on a Field Programmable Gate Array (FPGA) for timing analysis using synchronous compositional semantics. To illustrate our approach, we develop regression and classification ANN designs for multiple real-life datasets. Using various design and model architecture variations, we show that using a compositional design instead of a monolithic design can achieve an $\mathbf{8 5 \%}$ reduction in WCET, around a $\mathbf{53 \%}$ reduction in hardware resources and around a 40% reduction in computations and neuron connections for a minor reduction in performance.

关键词： Neurons Semantics Artificial neural networks Multilayer perceptrons Hardware Mathematical models Real-time systems Timing Safety Field programmable gate arrays

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EEiF: Efficient Isolated Forest with e Branches for Anomaly Detection 24

EEiF: Efficient Isolated Forest with e Branches for Anomaly ...

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24th IEEE International Conference on Data Mining, ICDM 2024

作者： Zhang, Yifan Xiang, Haolong Zhang, Xuyun Xu, Xiaolong Fan, Wei Zhang, Qin Qi, Lianyong School of Software Nanjing University of Information Science and Technology China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services China School of Computing Macquarie University Australia University of Oxford Uffield Department of Women's & Reproductive Health United Kingdom College of Computer Science and Software Engineering Shenzhen University China Faculty of Science and Engineering China

ISBN: (纸本)9798331506681

Anomaly detection is a popular research topic in Artificial Intelligence and has been widely applied in network security, financial fraud detection, and industrial equipment failure detection. Isolation forest based methods are the base algorithms to detect anomalies in these scenarios for their simplicity and efficiency, which has been further exploited with multi-folk trees and learning mechanisms to realize the optimal isolation forest for high detection accuracy. However, the optimal isolation forest is time-consuming with the learning mechanisms, resulting in the task failing of time-constrained applications. Moreover, the original optimal isolation forest fails to construct the optimal tree structure restricted by the time complexity. To address the above challenges, we propose an efficient anomaly detection method called EEIF, which realizes the real e-folk structure of the optimal isolation forest in our practical algorithm design. Specifically, we design a distribution that perfectly matches the e-branch theory to construct the optimal isolation forest. Then, we design an FR clustering scheme to achieve fast training of the isolation forest with learning to hash and provide related proofs of accuracy and efficiency. Besides, a parallel algorithm is integrated into our method to reduce prediction time. Finally, extensive experiments are conducted on a large amount of real-world datasets and the results demonstrate that our method significantly improves efficiency while ensuring effectiveness, compared with the state-of-the-art methods. © 2024 IEEE.

关键词： Anomaly Detection Efficient FR clustering Parallel Algorithm

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