2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS)最新文献_第6页

Low-cost BLE based intravenous monitoring and control infusion system 基于低成本BLE的静脉监控输注系统

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104683

Saad Abdullah, Kehkashan Kanwal, Abdelakram Hafid, Sabrina Difallah

引用次数: 0

Dealing with extremly Unbalanced Data and Detecting Insider Threats with Deep Neural Networks 用深度神经网络处理极度不平衡数据和检测内部威胁

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10105103

Samiha Besnaci, Mohamed Hafidi, Mahnane Lamia

{"title":"Dealing with extremly Unbalanced Data and Detecting Insider Threats with Deep Neural Networks","authors":"Samiha Besnaci, Mohamed Hafidi, Mahnane Lamia","doi":"10.1109/ICAECCS56710.2023.10105103","DOIUrl":"https://doi.org/10.1109/ICAECCS56710.2023.10105103","url":null,"abstract":"The internal and external security of a company is important. External security can be secured by setting up mechanisms to monitor any external flow, while internal security is the most complex, in this case how do we monitor internal workers who have full privileges to access the resources and data of the organization? All necessary measures must be in place to avoid internal damage, which has increased considerably in last years. Since the number of harmful behaviors is very low compared to normal events, the imbalance in class scores does not allow supervised learning algorithms to provide accurate results as their learning depends on balanced categories. Therefore, it is necessary to use a model capable of distinguishing clearly the harmful category. In previous work, ML techniques were used, although they are less effective if the data used are not balanced. In this document, we propose an S-LSTM model based on the integration of sampling approach, which is the generation of synthetic samples to balance the two classes of learning by SMOTE technique and LSTM algorithm for identify abnormal behavior. To build and evaluate the model, we used the Cert v4.2 dataset, and through the experimental evaluation, which gave a high prediction accuracy of 99%, we show that the proposed model provides a better solution. to detect the insider threat.","PeriodicalId":447668,"journal":{"name":"2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117008403","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

Blockchain for medical security data: a review and perspectives 医疗安全数据的区块链:回顾与展望

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104749

Hakima Rym Rahal, S. Slatnia, O. Kazar, E. Barka

引用次数: 0

Effect of FSS structures on Radiation Properties of a Monopole Antenna with Anisotropic Substrate FSS结构对各向异性衬底单极天线辐射特性的影响

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104774

F. Guidoum, M. L. Tounsi, M. Yagoub

引用次数: 0

Chaos-based Key Generator using Artificial Neural Networks Models 基于人工神经网络模型的混沌密钥生成器

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10105105

Amina Kadir, M. S. Azzaz, Redouane Kaibou

{"title":"Chaos-based Key Generator using Artificial Neural Networks Models","authors":"Amina Kadir, M. S. Azzaz, Redouane Kaibou","doi":"10.1109/ICAECCS56710.2023.10105105","DOIUrl":"https://doi.org/10.1109/ICAECCS56710.2023.10105105","url":null,"abstract":"Because of the growing number of attacks on existing systems, it is crucial to design new cryptographic techniques to ensure confidentiality. Although, the chaotic systems and deep learning methods have been proven to be effective in cryptography because of the nonlinearity and the high degree of randomness [1] and due to this, we combined them to produce cryptographic keys. This paper presents the chaotic time series forecasting models in order to produce encryption keys applied in cryptographic applications. Our artificial neural network (ANN) is trained by the Unified chaotic system samples using the optimal layers design. For comparative purposes, we have tested the performances of the Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) models in terms of chaotic time series patterns prediction. The Mean Squared Error (MSE) of the model achieves a value of 3.2x1$0^{-3}$ and we discover that, despite the small differences between the predicted samples of LSTM and GRU models, they produce nearly identical results for the task of chaotic time series prediction when compared to the MLP.","PeriodicalId":447668,"journal":{"name":"2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123658093","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

Low-Cost ECG Monitoring System with Classification Using Deep Learning 基于深度学习分类的低成本心电监测系统

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104707

H. Saadi, M. Ferroukhi, Y. L. Elghandja, F. Lahmari

引用次数: 1

Fuzzy Fast Terminal SMC for Underactuated Mechanical Systems 欠驱动机械系统的模糊快速终端SMC

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104963

A. Bendenidina, Kamel GUESMI, A. Rebai

引用次数: 0

Local Directional Patterns for Plant Leaf Disease Detection 植物叶片病害检测的局部定向模式

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104754

Amine Mezenner, H. Nemmour, Y. Chibani, A. Hafiane

引用次数: 0

An intelligent monitoring system of greenhouse: A Belief Functions Theory-Based Approach 基于信念函数理论的温室智能监控系统

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10104825

Karima Chemoun, Sarah Oubabas, Tassadit Sadoun, R. Aoudjit, Marc Gilg

引用次数: 0

Toward Building Another Arabic Voice Command Dataset for Multiple Speech Processing Tasks 为多个语音处理任务建立另一个阿拉伯语语音命令数据集

2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS) Pub Date : 2023-03-06 DOI: 10.1109/ICAECCS56710.2023.10105079

Mohamed Lichouri, Khaled Lounnas, Adil Bakri

{"title":"Toward Building Another Arabic Voice Command Dataset for Multiple Speech Processing Tasks","authors":"Mohamed Lichouri, Khaled Lounnas, Adil Bakri","doi":"10.1109/ICAECCS56710.2023.10105079","DOIUrl":"https://doi.org/10.1109/ICAECCS56710.2023.10105079","url":null,"abstract":"Expanding Internet connectivity has had tremendous influence on people’s everyday life, since they do everything on their phones and laptops [1]. Several items have been developed by various researchers in order to improve the lives of people, notably the elderly and disabled, while remaining technologically advanced. Voice-command-enabled technologies, such as SIRI and Google voice commands, are the most useful. These systems are based on the Speech recognition module, which is one of the most important module that can make human-machine communication easier. Automatic Speech Recognition (ASR) has made significant progress toward human-like performance by employing a data-driven method [2]. In this paper, we created an Arabic voice command dataset which include 10 commands spoken by 10 speaker and repeated 10 times. The obtained dataset, despite its size, was evaluated on four speech processing tasks and achieved an accuracy of 95.9% in ASR, and a macro F1score of 99.67%, 100%, 100%, and 97.98%, in speaker identification, gender recognition, accent recognition, and spoken language understanding, respectively.","PeriodicalId":447668,"journal":{"name":"2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126879177","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