2023 IEEE International Conference on Electro Information Technology (eIT)最新文献_第7页

Utilizing Computer Vision Algorithms to Detect and Classify Cyberattacks in IoT Environments in Real-Time 利用计算机视觉算法实时检测和分类物联网环境中的网络攻击

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187263

M. Gromov, David Arnold, J. Saniie

引用次数: 0

Protein Corona Formation Prediction on Engineered Nanomaterials 工程纳米材料中蛋白质电晕形成的预测

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187259

Nicholas Ferry, Kishwar Ahmed, S. Tasnim

引用次数: 0

ChatGPT: A Threat Against the CIA Triad of Cyber Security ChatGPT:对CIA网络安全三合会的威胁

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187355

M. Chowdhury, Nafiz Rifat, M. Ahsan, Shadman Latif, Rahul Gomes, Md Saifur Rahman

引用次数: 0

Drowning Recognition for Ocean Surveillance using Computer Vision and Drone Control 基于计算机视觉和无人机控制的海洋监视溺水识别

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187281

M. Rakotondraibé, Tianyang Fang, J. Saniie

引用次数: 0

ACapsule Q-Learning Based Reinforcement Model for Intrusion Detection System on Smart Grid 基于accapsule Q-Learning的智能电网入侵检测系统强化模型

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187374

T. T. Khoei, N. Kaabouch

{"title":"ACapsule Q-Learning Based Reinforcement Model for Intrusion Detection System on Smart Grid","authors":"T. T. Khoei, N. Kaabouch","doi":"10.1109/eIT57321.2023.10187374","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187374","url":null,"abstract":"Smart grid is an innovative technology that offers efficiency, low carbon emissions, and high energy storage. However, this promising technology has several shortcomings, including limited security. In this network, Intrusion Detection System (IDS) is one of the likely targeted systems that has limited security and is prone to several cyber vulnerabilities. To address a such challenge, several studies have been proposed to detect, classify, and mitigate these attacks using Artificial Intelligence (AI) techniques, although the proposed techniques in the literature suffer from high misdetection and false alarm rates. Additionally, limited data availability motivated the researchers to use another type of AI method, namely reinforcement learning to detect and classify attacks. In this paper, we propose a deep reinforcement learning-based technique, namely Q learning and capsule network as a deep learning model to detect attacks for IDS on smart grid networks. The benchmark of CICDDOs 2019 is selected to evaluate the model in terms of accuracy, detection, misdetection, false alarm rates, training time, and prediction time. We also investigate the performance of the proposed model based on discount values of 0.001 and 0.9. The experiments demonstrate that the proposed model has acceptable results, and the model with the lower discount values provides better results.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130606181","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

Link Multiple Courses to Enhance Students' Hands-on Practice on Microprocessor Systems 连结多个课程，加强学生对微处理器系统的实践

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187309

Jack Li

引用次数: 0

A Smartphone App for Real-time Heart Rate Computation from Streaming ECG/EKG data 从流心电/心电图数据实时计算心率的智能手机应用程序

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187337

Ucchwas Talukder Utsha, B. Morshed

{"title":"A Smartphone App for Real-time Heart Rate Computation from Streaming ECG/EKG data","authors":"Ucchwas Talukder Utsha, B. Morshed","doi":"10.1109/eIT57321.2023.10187337","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187337","url":null,"abstract":"Cardiac disease, also known as cardiovascular disease, refers to a group of conditions that affect the heart and blood vessels. Diagnosis of cardiac disease typically involves a combination of medical history, physical examination, and various tests, such as electrocardiograms (ECG/EKG), echocardiograms, and stress tests. To address this concern, we introduce a mobile application called Smart-Health application, which can continuously monitor electrocardiogram signals and display Average Heart Rate (HR) along with the instantaneous HR. The aim of this project is to discover cardiac diseases so that doctors can monitor the accurate heart rate and take further actions based on the results. Smart-Health application typically works by collecting data from wrists or chest by electrodes. This data is then processed and analyzed to provide the user with insights into their health. We collected data from 10 participants and compared it with KardiaMobile (AliveCor®, Mountain View, CA, USA) commercial application. The error rate of the proposed algorithm depends on several factors, including the accuracy of the sensors used to capture the ECG signal, the algorithms used to process the signal, and the quality of the hardware and software components used to build the application. Experimental results show an accuracy of up to 95-99%. This Smart-Health application has the potential to improve health outcomes and reduce healthcare costs, making it a valuable tool for both individuals and healthcare providers.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124778586","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

Evaluation of Homomorphic Encryption for Privacy in Principal Component Analysis 主成分分析中的同态加密隐私评估

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187220

David Arnold, J. Saniie

{"title":"Evaluation of Homomorphic Encryption for Privacy in Principal Component Analysis","authors":"David Arnold, J. Saniie","doi":"10.1109/eIT57321.2023.10187220","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187220","url":null,"abstract":"Principal Component Analysis (PCA) is a versatile Unsupervised Learning (UL) technique for reducing the dimensionality of datasets. As a result, PCA is widely used in consumer and research applications as a preprocessing tool for identifying important features prior to further analysis. In instances where on-site personnel or developers do not have the expertise to apply UL techniques, third party processors are frequently retained. However, the release of client or proprietary data poses a substantial security risk. This risk increases the regulatory and contractual burden on analysts when interacting with sensitive or classified information. Homomorphic Encryption (HE) cryptosystems are a novel family of encryption algorithms that permit approximate addition and multiplication on encrypted data. When applied to UL models, such as PCA, experts may apply their expertise while maintaining data privacy. In order to evaluate the potential application of Homomorphic Encryption, we implemented Principal Component Analysis using the Microsoft SEAL HE libraries. The resulting implementation was applied to the MNIST Handwritten dataset for feature reduction and image reconstruction. Based on our results, HE considerably increased the time required to process the dataset. However, the HE algorithm is still viable for non-real-time applications as it had an average pixel error of near-zero for all image reconstructions.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126349251","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

A Novel Approach Towards Fusion of Steganography and Cryptography for Enhanced Data Security using RGB Image 一种基于RGB图像的隐写与加密融合增强数据安全性的新方法

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187231

Zeeshan Abbas, K. Chong

{"title":"A Novel Approach Towards Fusion of Steganography and Cryptography for Enhanced Data Security using RGB Image","authors":"Zeeshan Abbas, K. Chong","doi":"10.1109/eIT57321.2023.10187231","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187231","url":null,"abstract":"Security has now become an essential part of communication on both sender and receiver's side. It is challenging to deliver comprehensive security against invaders since a lot of algorithms are expounded and can effortlessly get significant data by performing different hacking methods. High security-based algorithms like AES are nowadays used in various systems, as they present a high performance and is quite faster than most of stream-based encryption algorithms. Regardless of how reliable the technique is, the cipher-text always creates a doubt in brain when someone notices it, which makes the data prone to interception. Here arises another method of security to eliminate that suspicion, hence, we incorporate the confidential information into another format, such as an image, sound, video, or text and then transmit through the network. A novel security system based on three steps of hybrid architecture has been proposed in this paper by combining steganography and cryptography with codebooks. Two different keys are used to encrypt and then hide that highly secured encrypted message into the cover image. The message is encrypted first with AES algorithm and then placed at random positions in the cover image using codebook and KSA algorithm. AES encrypted message is mapped onto values of predefined codebooks then hide those encrypted message bits in LSBs of the cover image. The selected parameters are then passed on to the decryption side to recover the original message. Based on the achieved experimental results, it has outperformed the previous methodologies and without having the secret keys it is unfeasible to extract the message in a readable format.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132950872","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

Verification of a Predictive Method for Obstacle Detection and Safe Operation of Autonomous Vehicles 自动驾驶汽车障碍物检测与安全运行预测方法的验证

2023 IEEE International Conference on Electro Information Technology (eIT) Pub Date : 2023-05-18 DOI: 10.1109/eIT57321.2023.10187222

Lila Areephanthu, B. Abegaz

引用次数: 0