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2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)最新文献

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An Enhanced Method for Detecting Attack in Collaborative Recommender System 协同推荐系统中一种改进的攻击检测方法
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085506
Reda A. Zayed, H. Hefny, L. F. Ibrahim, H. A. Salman
{"title":"An Enhanced Method for Detecting Attack in Collaborative Recommender System","authors":"Reda A. Zayed, H. Hefny, L. F. Ibrahim, H. A. Salman","doi":"10.1109/ICAISC56366.2023.10085506","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085506","url":null,"abstract":"In recent decades, the advent of digital information services by YouTube, Amazon, Netflix, and many other web services of this kind have made recommendation systems more and more ubiquitous in our lives. rice field. The system suggests and recommends articles to the user that may interest the user in online advertising (recommending and suggesting appropriate content to the user that matches the user’s tastes and activities). Recommendation systems have become an integral part of our daily online journeys. The quality of predictions is degraded by the attackers by injection of fake profiles. therefore, the shilling attacks detection are necessary. thus, various shilling attacks detection techniques proposed. In this paper, we introduce an enhanced technique for detecting shilling attacks in collaborative recommender system using supervised learning techniques. The proposed method results show that getting better accuracy when we employee ensemble learning algorithm.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124087337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Novel Cybersecurity Issues in Smart Energy Communities 智能能源社区中的新型网络安全问题
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085312
G. Gaggero, Diego Pisera’, P. Girdinio, F. Silvestro, Mario Marchese
{"title":"Novel Cybersecurity Issues in Smart Energy Communities","authors":"G. Gaggero, Diego Pisera’, P. Girdinio, F. Silvestro, Mario Marchese","doi":"10.1109/ICAISC56366.2023.10085312","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085312","url":null,"abstract":"The Renewable Energy Directive (2018/2001/EU) of the European Union proposes a legal framework for the development of renewable energy sources and citizen participation in the energy transition through two new instruments: collective self-consumption schemes (CSCs) and renewable energy communities (RECs). Energy Communities are rapidly evolving, increasingly employing information and communication technologies to properly monitor and control distributed energy resources. In this scenario, it is fundamental to evaluate cybersecurity risks from the beginning, to allow researchers to develop “secure-by-design” systems and platforms. This work analyzed common architectures and protocols commonly used to build Smart Energy Communities, evaluating the attack surfaces and possible vulnerabilities. This work also discusses some solutions which can be employed to mitigate the risk, and highlights current gaps in the state of the art.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122585508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Breast Cancer Diagnosis Using a Machine Learning Model and Swarm Intelligence Approach 使用机器学习模型和群体智能方法进行乳腺癌诊断
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085393
Ibrahim Gad, M. Elmezain, Majed M. Alwateer, Malik Almaliki, Ghada Elmarhomy, E. Atlam
{"title":"Breast Cancer Diagnosis Using a Machine Learning Model and Swarm Intelligence Approach","authors":"Ibrahim Gad, M. Elmezain, Majed M. Alwateer, Malik Almaliki, Ghada Elmarhomy, E. Atlam","doi":"10.1109/ICAISC56366.2023.10085393","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085393","url":null,"abstract":"The features selection for machine learning models requires careful consideration. A good selection of features can enable machine learning models to better identify patterns in data and make more accurate predictions. Also, relevant features in the data have an impact on the accuracy of the model and lengthen the training process. In this study, the suggested feature selection strategy is implemented using pigeon inspired optimizer (PIO). The PIO is a continuous swarm intelligent algorithm. The machine learning models were trained and tested using the proposed PIO optimizer in the context of medical data. Both the training and testing steps use the Wisconsin breast cancer dataset. The best results are generated by the Random Forest model, which has accuracy, F-score, recall, and precision values of 97.2%, 97.3%, 97.3%, and 97.3%, respectively. It was concluded that the selected features perform better for classification than the original high-dimensional features, both in terms of accuracy and the F-score. As a consequence of this, the proposed approach can be utilized to better categorize breast cancer data.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122019792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Heart disease Prediction using Machine Learning 利用机器学习预测心脏病
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085522
Sarah Ibrahim, Nazih Salhab, A. Falou
{"title":"Heart disease Prediction using Machine Learning","authors":"Sarah Ibrahim, Nazih Salhab, A. Falou","doi":"10.1109/ICAISC56366.2023.10085522","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085522","url":null,"abstract":"Heart disease is among the main causes of fatalities worldwide, in our days. However, early detection of cardiac problems and timely care by health practitioners can reduce the mortality rate. Therefore, a reliable system for assessing such pathologies is of utmost importance to be able to process an adequate treatment. In this paper, we investigate various classification techniques to timely diagnose persons registered to receive medical treatment who are suffering from heart malfunctions. Accordingly, we can proactively identify issues based on collected clinical data. We analyze different machine learning approaches in order to recommend an optimal model by discussing the achieved performance in terms of multiple performance metrics. Finally, we provide our recommendations and share our lessons-learned.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127985758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sustainable Secure Internet of Things (SS-IoT) 可持续安全物联网(SS-IoT)
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085280
Mahmoud Badawy
{"title":"Sustainable Secure Internet of Things (SS-IoT)","authors":"Mahmoud Badawy","doi":"10.1109/ICAISC56366.2023.10085280","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085280","url":null,"abstract":"The development of Internet of Things (IoT) technology has been and remains a primary focus of the academic investigation. Smart cities rely primarily on IoT networks, and one of the most important challenges facing the development of smart solutions for these cities is cyber-attacks. Future communications and end devices should be well-secured, economical, energy-efficient, and eco-friendly. Thus, IoT deployment must be supported with lightweight cryptography techniques. This paper sheds light on a novel research trend, the Sustainable Secure Internet of Things (SS-IoT) that discusses IoT challenges regarding sustainability and security. In addition, current SS-IoT-related projects are touched on and presented. This study helps researchers and developers interested in technology and environmental engineering.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128701102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Smart vegetable cutter for Smart Home 智能家居的智能切菜机
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085675
S. Singhal, Deepak Mangal, Rakesh Kumar, B. Sharma, I. Dhaou
{"title":"Smart vegetable cutter for Smart Home","authors":"S. Singhal, Deepak Mangal, Rakesh Kumar, B. Sharma, I. Dhaou","doi":"10.1109/ICAISC56366.2023.10085675","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085675","url":null,"abstract":"Modern society strives for simpler, more efficient, dependable, speedier, and more automated lifestyle. Existing vegetable cutters in the market have drawbacks such as high investment costs, additional manpower, and time consumption. Moreover, none of them provide the feature of cleaning, peeling, and cutting in a single machine. The veggies offered in the market have pesticides and chemicals, and many people, in their haste, do not wash them properly, endangering their health. To reduce human labor while also providing good health care, a solution to this problem is required. This paper offers a novel method for developing a vegetable cutter and chopper using an Android application and IoT devices. In addition, smart vegetable cutters clean, peel, and cut veggies all in one piece of equipment. This strategy will assist human society in reducing the amount of additional manpower needed and would save them time.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124347550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Detecting Available Parking Spaces in Smart Cities 探测智慧城市的可用停车位
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085386
Hassanin M. Al-Barhamtoshy, Khalid K. Abdullah, Muhammed K. Dauda, Tarik F. Himdi
{"title":"Detecting Available Parking Spaces in Smart Cities","authors":"Hassanin M. Al-Barhamtoshy, Khalid K. Abdullah, Muhammed K. Dauda, Tarik F. Himdi","doi":"10.1109/ICAISC56366.2023.10085386","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085386","url":null,"abstract":"The concept of smart cities is realizing between vehicles, road networks, smart parking, smart mobility, smart environment, living, and people coupled with human population growth and needs. Therefore, the smart city has evolved over time, and improved the quality of human life using technologies. This paper proposes a fine-tuned model based on Mask-RCNN to implement and test “available parking spaces in smart cities”. The fine-tuned model performed well in classification accuracy. It demonstrates good performance and practical value in smart cities. Smart city is fast motivating to making technological solution for achieving smart mobility (transportation systems) more intelligent. This motivation takes us to compile new trends of AI and deep learning on the different aspects of smart city. Therefore, this paper presents an effort that can be taken up as research work for smart parking. Our result shows that; the proposed work outperforms in the detection of smart parking.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121855694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
ViT-DeiT: An Ensemble Model for Breast Cancer Histopathological Images Classification viti - deit:一种用于乳腺癌组织病理图像分类的集成模型
2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2022-11-01 DOI: 10.1109/ICAISC56366.2023.10085467
A. Alotaibi, Tarik K. Alafif, Faris A Alkhilaiwi, Y. Alatawi, Hassan Althobaiti, A. Alrefaei, Y. Hawsawi, T. Nguyen
{"title":"ViT-DeiT: An Ensemble Model for Breast Cancer Histopathological Images Classification","authors":"A. Alotaibi, Tarik K. Alafif, Faris A Alkhilaiwi, Y. Alatawi, Hassan Althobaiti, A. Alrefaei, Y. Hawsawi, T. Nguyen","doi":"10.1109/ICAISC56366.2023.10085467","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085467","url":null,"abstract":"Breast cancer is the most common cancer in the world and the second most common type of cancer that causes death in women. The timely and accurate diagnosis of breast cancer using histopathological images is crucial for patient care and treatment. Pathologists can make more accurate diagnoses with the help of a novel approach based on computer vision techniques. This approach is an ensemble model of two pretrained vision transformer models, namely, Vision Transformer (ViT) and Data-Efficient Image Transformer (DeiT). The ViTDeiT ensemble model is a soft voting model that combines the ViT model and the DeiT model. The proposed ViT-DeiT model classifies breast cancer histopathology images into eight classes, four of which are categorized as benign, whereas the others are categorized as malignant. The BreakHis public dataset is used to evaluate the proposed model. The experimental results show 98.17% accuracy, 98.18% precision, 98.08% recall, and a 98.12% F1 score, which outperform existing classification models.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114513844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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