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12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Ikuesan, Richard Iqbal, Farkhund Hayawi, Abdul Kadhim College of Technological Innovation Zayed University Computing and Applied Technology Abu Dhabi United Arab Emirates College of Interdisciplinary Studies Zayed University Computational Systems Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350330366

Utilizing and deploying behavioral biometric modalities (BBM), specifically mouse dynamics for user attribution in a digital investigation, has seen a rapid upsurge. However, as asserted in a recent study, the current reliability threshold of BBM falls short of the required standard for forensic attributes. This poor reliability can be attributed, in part, to the low signal-to-noise ratio in a typical behavioral dataset. This study proposed a context-free signature identification and extraction technique for BBM to extract a unique mouse dynamics signature suitable for a forensic process. A Re-Pair Grammar induction approach, which identifies and extracts unique Grammar sequences, was used to achieve this proposition. The grammar generation leverages symbolic aggregate approximation techniques to generate behavioral string subsequences from the mouse dataset. The Re-Pair approach was then used to develop a user attribution mechanism, which can be deployed for digital forensic analysis. The outcome of the implementation of the proposition, however, shows a poor performance relative to existing studies, hence its infeasibility as a benchmark for forensic science. However, it shows promising potential to reveal the inherent noise in mouse dynamics data, which can provide further insight into digital forensic science. This result further extends the literature on establishing digital forensic science, a significant requirement for any forensic discipline. © 2024 IEEE.

关键词： Digital forensics

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NLP-Based Sentiment Analysis using Deep Learning Methods 1

NLP-Based Sentiment Analysis using Deep Learning Methods

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1st IEEE International Conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Kumar, Dheeraj Bhatia, Sandeep Singh Dhillon, Hardeep Goel, Amit Kumar Galgotias University School of Computing Science and Engineering Greater Noida India Department of Applied Sciences Panjab Mohali140307 India Apeejay Stya University Sohna Gurugram School of Engineering and Technology India

ISBN: (纸本)9798350356816

Opinion mining systems rely heavily on sentiment analysis because to the vast amount of data and opinions that are generated, exchanged, and sent on a regular basis through the internet and other media. This study presents a deep learning network-based sentiment analysis categorization that was created and compares the results across multiple deep learning networks. Using the Multilayer Perceptron, a benchmark for other networks' performance was established (MLP). Built and implemented on the 50K movie review file IMDB dataset were a hybrid model of long short-term memory (LSTM) and convolutional neural network (CNN), as well as an LSTM recurrent neural network. Reviews for the dataset were 50% positive and 50% negative. After Word2Vec performed its initial pre-processing on the data, word embedding was applied. The hybrid CNN_LSTM model outperformed the MLP and the separate CNN and LSTM networks, as seen by the findings. While CNN reported an accuracy of 88.9%, MLP and LSTM reported accuracy of 87.78% and 87.68, respectively. 89.4% accuracy was reported by CNN_LSTM. Results further show that the proposed deep learning models have performed better than SVM, Naïve Bayes, and RNTN models based on English datasets presented in previous works. © 2024 IEEE.

关键词： Contrastive Learning

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The Smart Assistive technology in Education for Students with Disabilities in Oman

The Smart Assistive Technology in Education for Students wit...

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computing and Data Analytics (ICCDA), International Conference on

作者： Junath Naseer Ahamed Laryam Nasser Albalushi Hind Maktoom Almamari Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

The research in Oman assessed smart assistive technology's impact on students with disabilities, focusing on academic improvement and user satisfaction. Using a mixedmethods approach, it found significant gains in student engagement and academic outcomes. Recommendations include expanding assistive tools and training educators. Limitations were a small sample size and uneven tech access. The study concluded that such technology greatly enhances inclusive education in Oman.

关键词： Training Data analysis Focusing Assistive technologies

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A Study on the Importance of Cybersecurity and its Significance in Omani Society

A Study on the Importance of Cybersecurity and its Significa...

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computing and Data Analytics (ICCDA), International Conference on

作者： Junath Naseer Ahamed Aisha Abdullah Mohammed Hamda Khamis Al Ghaithi Rawya Khamis Al Salty Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

This study investigates the critical role of cybersecurity in Omani society, analyzing its significance in safeguarding digital assets and maintaining societal well-being. By examining the current cybersecurity landscape in Oman, including challenges and vulnerabilities, the study highlights the pressing need for robust cybersecurity measures. Additionally, it explores the implications of cyber threats on various sectors, such as government, finance, healthcare, and education, underscoring the far-reaching consequences of inadequate cybersecurity practices. Furthermore, the study assesses existing cybersecurity initiatives and policies in Oman and identifies areas for improvement to enhance overall cyber resilience. Through empirical research and data analysis, this study contributes valuable insights into the importance of cybersecurity in protecting national interests, promoting economic growth, and preserving social stability in Oman.

关键词： Privacy Data analysis Pressing Passwords Stability analysis Loss measurement Computer security Computer crime Protection Resilience

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Availability and Demand of Jobs from the Perception of Automated Recruitment in Oman 7

Availability and Demand of Jobs from the Perception of Autom...

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Karim Sadiq, Mohamed Abdul Al-Fannah, Nasser Mohammed Shanmugam, Thirumurugan Kausar, Firdous Oman Ministry of Transport Communications and Information Technology Muscat Oman College of Computing and Information Science Utas Suhar Oman College of Computing and Information Science University of Technology and Applied Sciences Suhar Oman Fisk University Department of Mathematics and Computer Science NashvilleTN United States

ISBN: (纸本)9798350342154

Natural Language Processing has been applied for automation of the recruitment process globally with the increase in volumes of profiles and jobs. This paper discusses certain challenges in the use of cutting-edge technologies for documents in the Arabic language. We analyze the availability and demand of jobs in Oman with reference to that in UAE. As a result, hurdles can be minimized in the job-resume matching process between the employers and prospective candidates. © 2023 IEEE.

关键词： Deep learning

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A Security Analysis Model for IoT-ecosystem Using Machine Learning-(ML) Approach

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Recent Advances in Computer Science and Communications 2024年第6期17卷 39-47页

作者： Pradeep Kumar, N.S. Kantipudi, M. V. V. Prasad Praveen, N. Suresh, S. Aluvalu, Rajanikanth Jagtap, Jayant Dept.of ECE S.E.A College of Engineering and Technology Bangalore India Pune412115 India Dept. Of Electrical Engineering University of Technology and Applied Sciences Ibra Oman Dept.of CSE Balaji Institute of Technology & Science Warangal India Dept.of IT Chaitanya Bharathi Institute of Technology Hyderabad500075 India Dept.of AIML NIMS Institute of Computing Artificial Intelligence and Machine Learning NIMS University Rajasthan Jaipur India

Introduction: The attacks on IoT systems are increasing as the devices and communication networks are progressively integrated. If no attacks are found in IoT for a long time, it will affect the availability of services that can result in data leaks and can create a significant impact on the associated costs and quality of services. Therefore, the attacks and security vulnerability in the IoT ecosystem must be detected to provide robust security and defensive mechanisms for real-time applications. Method: This paper proposes an analytical design of an intelligent attack detection framework using multiple machine learning techniques to provide cost-effective and efficient security analysis services in the IoT ecosystem. Result: The performance validation of the proposed framework is carried out by multiple performance indicators. Conclusion: The simulation outcome exhibits the effectiveness of the proposed system in terms of accuracy and F1-score for the detection of various types of attacking scenarios. © 2024 Bentham Science Publishers.

关键词： Ecosystems

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A Study for Smart Technologies for Autism Spectrum Disorders Children in Oman to Facilitate Interactive Communication

A Study for Smart Technologies for Autism Spectrum Disorders...

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computing and Data Analytics (ICCDA), International Conference on

作者： Junath Naseer Ahamed Manal AlGhafri Shima Al-Zeid Misoon Al Mamari Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

The study investigates the use of smart technologies in Oman to improve communication skills and social interactions among children with autism spectrum disorders (ASD). The Sultanate of Oman is focusing on fostering an inclusive environment through technological innovation and inclusive education. The study concludes that smart technology interventions can significantly improve communication abilities and social interactions, promoting a more inclusive society for ASD children.

关键词： Autism Technological innovation Data analysis Education Focusing

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A Study on the Development and Evaluation of Smart Home System Using IoT and AI Technologies in Oman

A Study on the Development and Evaluation of Smart Home Syst...

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computing and Data Analytics (ICCDA), International Conference on

作者： Junath Naseer Ahamed Mohammed Ashraf Ahmed Juma Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

Smart homes, leveraging Internet of Things (IoT) and Artificial Intelligence (AI) technologies, are gaining popularity worldwide. However, their implementation in specific regions, such as Oman, remains underexplored. This research addresses this gap by investigating the development and evaluation of a smart home system tailored to Oman's unique context. Our study aims to enhance home automation, energy efficiency, and overall quality of life for Omani residents. We propose hypotheses related to the impact of IoT and AI integration, economic prospects, and localized design strategies. The study's significance lies in its potential to inform decisionmakers, urban planners, and technology suppliers regarding the adoption and use of smart home technologies in Oman.

关键词： Data analysis Prototypes Smart homes Energy efficiency Internet of Things Cultural differences Artificial intelligence Socioeconomics Meteorology

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Exploring the Influence of Social Media on Omani Culture, Identity and its Impact on Youth Behavior

Exploring the Influence of Social Media on Omani Culture, Id...

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computing and Data Analytics (ICCDA), International Conference on

作者： Junath Naseer Ahamed Hawa Zaid Al Shiadi Abir Nasser Al Mamari Shatha Mohammed Al Farsi Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

The purpose of this study was to comprehend how social media affects Omani youth and what that means for maintaining their nationality and identity. Expanding school curricula to highlight the importance of Omani culture, finding strategies for parents to support their children in preserving Omani identity and culture, and increasing public awareness of the risks connected with social media platforms were the objectives. The study employed a survey research methodology, gathering data via the administration of questionnaires. A representative sample of young Omani people was chosen using voluntary response samples and convenience sampling. Social network analysis and content analysis are examples of data analysis. A number of ethical factors were taken into account, including security, privacy, secrecy, data integrity, and informed permission. The results indicated that there were no statistically significant differences between the means of the data sets, indicating that the central tendency of the data sets was statistically similar. The research concluded that social media plays an important role in shaping cultural perceptions, identity formation, and behavioral patterns among Omani youth, and strategies should be developed to harness its positive aspects while mitigating its negative effects. The result tendency of the data sets was statistically similar, according to the results, which showed that there were no statistically significant discrepancies between the means of the data sets. According to the study's findings, social media has a significant impact on how Omani young perceives culture, construct identities, and behave. As a result, measures for maximizing social media's beneficial benefits while reducing its negative ones should be devised.

关键词： Surveys Ethics Data privacy Data analysis Social networking (online) Data integrity Information age Cultural differences Stakeholders Security

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Explore Enhanced Communication and Decision Making between Government and Citizens of Oman Using Digital Technologies

Explore Enhanced Communication and Decision Making between G...

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computing and Data Analytics (ICCDA), International Conference on

作者： Junath Naseer Ahamed Naira Hassan Anwar Muneera Saif Al naabi Mashaal Atiyaq Al-Badi Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

This study explores how digital technology can enhance communication and decision-making between the Omani government and its citizens. In our digital age, effective communication and collaboration are crucial. The research examines how tools like mobile apps, social media, and e-government services can improve information sharing and decision-making. The paper begins by highlighting the importance of citizen participation and transparency in Oman's Vision 2040. It then presents the hypothesis: digital technology positively impacts citizen engagement, communication quality, transparency, trust, and decision-making. The study reviews the relevance, scope, and limitations, emphasizing the need for digital tools to enhance communication in Oman. It aims to evaluate how well these technologies bridge communication gaps and overcome challenges. The methodology combines qualitative and quantitative approaches, gathering data from government officials, citizens, and experts. The findings and recommendations aim to guide policymakers in developing effective digital initiatives to boost governance and public involvement in Oman.

关键词： Bridges Data analysis Social networking (online) Decision making Information sharing Collaboration Information age Mobile applications Electronic government Systematic literature review

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