2020 IEEE 23rd International Multitopic Conference (INMIC)最新文献_第10页

IoT DoS and DDoS Attack Detection using ResNet 物联网DoS和DDoS攻击检测使用ResNet

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318216

Faisal Bashir Hussain, Syed Ghazanfar Abbas, M. Husnain, U. U. Fayyaz, F. Shahzad, G. Shah

{"title":"IoT DoS and DDoS Attack Detection using ResNet","authors":"Faisal Bashir Hussain, Syed Ghazanfar Abbas, M. Husnain, U. U. Fayyaz, F. Shahzad, G. Shah","doi":"10.1109/INMIC50486.2020.9318216","DOIUrl":"https://doi.org/10.1109/INMIC50486.2020.9318216","url":null,"abstract":"The network attacks are increasing both in frequency and intensity with the rapid growth of internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of service (DDoS) attacks are reported as the most frequent attacks in IoT networks. The traditional security solutions like firewalls, intrusion detection systems, etc., are unable to detect the complex DoS and DDoS attacks since most of them filter the normal and attack traffic based upon the static predefined rules. However, these solutions can become reliable and effective when integrated with artificial intelligence (AI) based techniques. During the last few years, deep learning models especially convolutional neural networks achieved high significance due to their outstanding performance in the image processing field. The potential of these convolutional neural network (CNN) models can be used to efficiently detect the complex DoS and DDoS by converting the network traffic dataset into images. Therefore, in this work, we proposed a methodology to convert the network traffic data into image form and trained a state-of-the-art CNN model, i.e., ResNet over the converted data. The proposed methodology accomplished 99.99% accuracy for detecting the DoS and DDoS in case of binary classification. Furthermore, the proposed methodology achieved 87% average precision for recognizing eleven types of DoS and DDoS attack patterns which is 9% higher as compared to the state-of-the-art.","PeriodicalId":137217,"journal":{"name":"2020 IEEE 23rd International Multitopic Conference (INMIC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128346411","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: 66

Alphabetical Gesture Recognition of American Sign Language using E-Voice Smart Glove 基于E-Voice智能手套的美国手语字母手势识别

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318185

Muhammad Saad Amin, Muhammad Talha Amin, Muhammad Yasir Latif, Ali Asghar Jathol, N. Ahmed, M. I. N. Tarar

引用次数: 9

Automated Robotic System for Assistance of Isolated Patients of Coronavirus (COVID-19) 新型冠状病毒(COVID-19)隔离患者自动救助机器人系统

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318124

Iram Haider, Khan Bahadar Khan, Muhammad Arslan Haider, Arshad Saeed, K. Nisar

{"title":"Automated Robotic System for Assistance of Isolated Patients of Coronavirus (COVID-19)","authors":"Iram Haider, Khan Bahadar Khan, Muhammad Arslan Haider, Arshad Saeed, K. Nisar","doi":"10.1109/INMIC50486.2020.9318124","DOIUrl":"https://doi.org/10.1109/INMIC50486.2020.9318124","url":null,"abstract":"The end of 2019 and the start of 2020 remained the time of the world's largest medical emergency due to Coronavirus disease known as COVID-19, outbreak in all over the world. We designed an automated robotic assistance system for the patients who are kept in quarantine. In the proposed system, doctors can remotely monitor the medical condition of a patients by maintaining social distance. A robotic cart will provide food and medicine to the patient. The proposed system also contains an emergency system where the doctor and paramedical staff can be called through the LCD panel installed aside the patient's bed or through the mobile application. The article portrays the three levels of the development of the model: the equipment level, which contains the sensors, actuators and robot execution. The design level, which defines the distinctive practical services; and the application level which illustrate the administrations offered by the system. The setup will enable the medical staff to deal with the maximum patients at less time. Also, it will enable them to make social distancing to pay more attention to severely affected patients.","PeriodicalId":137217,"journal":{"name":"2020 IEEE 23rd International Multitopic Conference (INMIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126288449","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: 10

New Technique to Rank Without Off Page Search Engine Optimization 没有页面搜索引擎优化排名的新技术

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318166

Asad Nadeem, Musa Hussain, Ahsan Iftikhar

引用次数: 2

Optimization of PV Modules through Tilt Angle in Different Cities Of Punjab, Pakistan 巴基斯坦旁遮普不同城市通过倾斜角度优化光伏组件

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318120

Muhammad Waqas Ashraf, Sheikh Muhammad Aaqib, H. Manzoor, M. Asharaf, Tareq Manzor, Muzammal Hussain Sethi

引用次数: 2

A Two Fold Approach for Object Recognition with Bag of Visual Words using Artificial Neural Network 基于人工神经网络的视觉词袋目标识别的双重方法

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318197

Muhammad Ahmed Raza, Qasim Hussain, Saira Mustafa, Mughees Ahmed Bhatti, Mafaz Ahmad

{"title":"A Two Fold Approach for Object Recognition with Bag of Visual Words using Artificial Neural Network","authors":"Muhammad Ahmed Raza, Qasim Hussain, Saira Mustafa, Mughees Ahmed Bhatti, Mafaz Ahmad","doi":"10.1109/INMIC50486.2020.9318197","DOIUrl":"https://doi.org/10.1109/INMIC50486.2020.9318197","url":null,"abstract":"Advancements in Computer vision techniques have assisted the Artificial intelligence and Autonomous robotics community. Its applications involve driverless cars, Visual Odometry, Object detection and localization and 3D Reconstruction. Object recognition and localization have also been a hot topic for researchers in recent years. Object detection is a very important part in driverless cars too, i.e., it detects objects such as humans and other vehicles. Proposed is a technique to recognize and localize the object in the image effectively. This Proposed technique first reduces the problem from multi-class, multi-label classification to a single label, multi-class problem by only taking a bag of visual word (BoVW) model of a single bounding box at a time. Moreover, this also generates ‘none’ class edge boxes and suppresses these ‘none’ objects based on its BoVW model. PASCAL VOC 2012 and 2007 datasets were used for training and testing purposes. Both qualitative and quantitative analysis was carried out. It is established that the proposed approach gives appreciable results while reducing the complexity of the problem.","PeriodicalId":137217,"journal":{"name":"2020 IEEE 23rd International Multitopic Conference (INMIC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132496083","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

Detection of Anomaly in Videos Using Convolutional Autoencoder and Generative Adversarial Network model 基于卷积自编码器和生成对抗网络模型的视频异常检测

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318140

M. Aqeel, Khan Bahadar Khan, M. A. Azam, Muhammad Hamza Ghouri, Hammad-ur-Rehman Khalid, Fawwad Hassan Jaskani

{"title":"Detection of Anomaly in Videos Using Convolutional Autoencoder and Generative Adversarial Network model","authors":"M. Aqeel, Khan Bahadar Khan, M. A. Azam, Muhammad Hamza Ghouri, Hammad-ur-Rehman Khalid, Fawwad Hassan Jaskani","doi":"10.1109/INMIC50486.2020.9318140","DOIUrl":"https://doi.org/10.1109/INMIC50486.2020.9318140","url":null,"abstract":"Anomaly in the crowds can create a threat to public security. Manual detection of abnormal crowd behavior in CCTV footage by human operators is a very difficult and time-consuming task. There is a need for automated detection of abnormal events in a video. The proposed automated method is based on the Convolutional Autoencoder and Generative Adversarial Network (GAN) model which are used to extract the features and motion patterns of the videos. The selected features are then classified by using different classifiers such as Support Vector Machine (SVM), Naïve Bayes, Decision Tree, and Linear Regression, for differentiation of various types of abnormalities in videos. The proposed method is validated on the UCF crime video dataset. Accuracy, sensitivity, specificity and loss function are the performance parameters used for the evaluation of the proposed methodology. The visual and parametric results of the proposed method showed promising results in the form of accuracy as compared with the existing techniques.","PeriodicalId":137217,"journal":{"name":"2020 IEEE 23rd International Multitopic Conference (INMIC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131345668","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: 2

A Survey Comparing Specialized Hardware And Evolution In TPUs For Neural Networks 神经网络专用硬件与tpu进化的比较研究

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318136

A. Shahid, Malaika Mushtaq

{"title":"A Survey Comparing Specialized Hardware And Evolution In TPUs For Neural Networks","authors":"A. Shahid, Malaika Mushtaq","doi":"10.1109/INMIC50486.2020.9318136","DOIUrl":"https://doi.org/10.1109/INMIC50486.2020.9318136","url":null,"abstract":"This survey paper is based on the evolution of TPUs from first generation TPUs to edge TPUs and their architectures. This paper compares CPUs, GPUs, FPGAs and TPUs, their hardware architectures, their similarities and differences will be discussed. Modern neural networks are immensely used these days but they require more time, computation and energy. Due to the greater demand and attractive options for architects to explore, companies are continuously working to reduce training and inference response time. Due to the demands and cost factors different kinds of ASICs (application specific integrated circuits) are developed and research is increased in this area. Many models of CPUs, GPUs and TPUs have been developed to support these networks and to improve training and inference phase. Intel developed CPUs for this purpose, NVIDIA developed GPUs and Google developed cloud TPUs. The hardware of CPUs and GPUs can be sold to businesses while Google offers TPU processing for everyone from the cloud. When the data is away from the computational source, it increases the overall cost and to reduce this cost companies implements memory management and caching techniques close to ALUs.","PeriodicalId":137217,"journal":{"name":"2020 IEEE 23rd International Multitopic Conference (INMIC)","volume":"19 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123553788","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: 9

Wind Energy Micorogrids for Smart Grid in Rural Sindh — Nooriabad 用于信德省农村智能电网的风能微电网

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318050

A. B. Ahmed, H. Zahid, Syed Ali Abbas Kazmi, U. Khan

引用次数: 0

A Flexible Highly Configurable System Architecture for Geographical Information System 一种灵活的、高度可配置的地理信息系统架构

2020 IEEE 23rd International Multitopic Conference (INMIC) Pub Date : 2020-11-05 DOI: 10.1109/INMIC50486.2020.9318108

M. S. Iqbal, Atif Ali, A. Naseem, Rizwan Majeed

{"title":"A Flexible Highly Configurable System Architecture for Geographical Information System","authors":"M. S. Iqbal, Atif Ali, A. Naseem, Rizwan Majeed","doi":"10.1109/INMIC50486.2020.9318108","DOIUrl":"https://doi.org/10.1109/INMIC50486.2020.9318108","url":null,"abstract":"In the current environment, the functionality and the usage of Geographic Information Systems (GIS) have grown steadily, resulting in many diversified and complex artifacts. Although there is a different GIS used for other regions with different goals, they have versatile features and requirements. So, for intensive software reuse, such as Highly Configurable System Engineering (HCSE), different techniques can be applied. Despite extensive research on Highly Configurable Systems Engineering in recent years, the same has not yet been defined in the field of GIS In this research work, we identified the requirements and capabilities for a standard product of Web-based GIS. We shared them jointly, which allowed us to regenerate many of the different objects and software variants, which will enable software engineers to configure his application. We then define the functionality and technical architecture of a highly configurable system that uses current technology to develop web-based applications. Lastly, we designed a tool to configure and assemble components to generate the desired products. Subsequently, the proposed platform is flexible to create its GIS product as per each customer's specific needs.","PeriodicalId":137217,"journal":{"name":"2020 IEEE 23rd International Multitopic Conference (INMIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128717921","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: 4