2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)最新文献_第8页

An Approach to Reduce Uncertainty Problem in Network Intrusion Detection Systems 一种减少网络入侵检测系统不确定性问题的方法

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342634

G. Kadam, Sahil Parekh, Priyanka Agnihotri, D. Ambawade, P. Bhavathankar

{"title":"An Approach to Reduce Uncertainty Problem in Network Intrusion Detection Systems","authors":"G. Kadam, Sahil Parekh, Priyanka Agnihotri, D. Ambawade, P. Bhavathankar","doi":"10.1109/ICIIS51140.2020.9342634","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342634","url":null,"abstract":"In the current scenario pertaining to cyberattacks, Denial of Service attacks are the most common type. Denial of Service (DoS) has now become an attack category that has different types of attacks such as Back, Neptune, Smurf, Teardrop, etc. As common as these attacks are, they are one of the most troublesome to deal with and have become an annoyance in the industry. Along with those, attacks like User-to-Root (U2R), Remote-to-Local (R2L) and Probe are used to gain access to the system and hence form the cycle of an attack. A network intrusion detection system is proposed which is tailored to detect these attacks. The main objective is to classify the aforementioned types of attacks with minimum uncertainty and reduce the number of false positives for more reliable detection. With data mining coupled with machine learning and deep learning algorithms, a feature selection and a classification model is built by primarily training it on the KDDCup99 dataset and the ISTS Dataset, then tweaking the models by testing it on real-time data gathered from tcpdump. Real-time data collected using the ISTS dataset is firstly labelled using unsupervised machine learning methods and also by matching the data with the KDDCup99 dataset records. A model with the most optimum algorithms used for feature selection and classification procedure is developed. Also, different algorithms used on various parameters are compared.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124660815","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

Identification of Brand Logos from Video Feed 识别品牌标志从视频馈送

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342654

Pranshu Garg, Anmol Tripathi, A. Sahani

引用次数: 0

Significance of Controller in Software Defined Networks 控制器在软件定义网络中的意义

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342710

Deepjyot Kaur Ryait, Manmohan Sharma

{"title":"Significance of Controller in Software Defined Networks","authors":"Deepjyot Kaur Ryait, Manmohan Sharma","doi":"10.1109/ICIIS51140.2020.9342710","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342710","url":null,"abstract":"The Software Defined Networks (SDN) provides an innovative paradigm for networking, which improve the programmability and flexibility of the network. Due to the separation between the control and data plane, all the control logic transfer to the controller. Thus, the controller provides a centralized logical view of the entire network. Therefore, all manipulation and implementation in the network are control by a single controller in the SDN, which increases the maximum chance of a central point of failure in the network. As a consequence, it collapses the entire network. Therefore, a fault tolerance mechanism is required which reduces SPOF in the network by using multiple controllers. As a significance, the multiple controllers increase the scalability, reliability, and high availability of services in the network. The various roles of multiple controllers are Equal, Master and Slave exist in the Software Defined Networks. During the simulation to analyse, when a SPOF is happening in SDN then the value of the packet loss parameter is increasing gradually till the controller becomes again in the working condition. Thus, to resolve this problem by using multiple controllers in the networks.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126063989","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

Loss functions for optimizing Kappa as the evaluation measure for classifying diabetic retinopathy and prostate cancer images 用于优化Kappa作为糖尿病视网膜病变和前列腺癌图像分类评价指标的损失函数

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342711

Rajendran Nirthika, Siyamalan Manivannan, A. Ramanan

{"title":"Loss functions for optimizing Kappa as the evaluation measure for classifying diabetic retinopathy and prostate cancer images","authors":"Rajendran Nirthika, Siyamalan Manivannan, A. Ramanan","doi":"10.1109/ICIIS51140.2020.9342711","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342711","url":null,"abstract":"Quadratic Weighted Kappa (QWK) is a statistic to measure the agreement between two annotators. QWK has been widely used as the evaluation measure for various medical imaging problems, where, the class labels have a natural ordering, e.g., no Diabetic Retinopathy (DR), mild DR, and severe DR. The easiest way to treat the classification problem with these ordinal labels is to consider the problem as a multiclass classification problem and apply the Cross Entropy (CE) loss. However, when applying CE loss the order of the classes becomes meaningless, i.e., the loss will be same if a healthy image is classified into mild DR or severe DR. At the same time, the QWK score will be severely affected if a healthy image is classified into severe DR than mild DR. The most appropriate way to get a better classification score is to optimize the evaluation measure itself. i.e., directly optimize the QWK statistics. However, this optimization may hinder the learning, and may lead to sub-optimal solutions, and therefore, may give lower performance than expected. On the other hand, Ordinal Regression (OR) based approaches also can be used for such problems. The main focus of this work is to investigate which loss function (CE loss, QWK loss or OR loss) is the most appropriate one to the Convolutional Neural Network-based ordinal classification problems, where, QWK is used as the evaluation measure. Experiments on two public datasets, Diabetic Retinopathy and Prostate Cancer, with two different network architectures suggest that directly optimizing QWK is the better choice when small networks are used. On the other hand, we found that for large networks OR based loss function gives better performance.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132729593","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: 5

Simulation and Design of Modified SPWM and Single-Phase Five-Level Inverter 改进型SPWM及单相五电平逆变器的仿真与设计

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342677

V. Srinath, Manmohan Agarwal, D. Chaturvedi

引用次数: 1

Virtual Character Animation based on Data-driven Motion Capture using Deep Learning Technique 基于深度学习技术的数据驱动动作捕捉的虚拟角色动画

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342693

G. Rajendran, Ojus Thomas Lee

{"title":"Virtual Character Animation based on Data-driven Motion Capture using Deep Learning Technique","authors":"G. Rajendran, Ojus Thomas Lee","doi":"10.1109/ICIIS51140.2020.9342693","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342693","url":null,"abstract":"Perceptions in motion capture (mocap) technology are increasing every day as the variety of applications using it is doubling. By leveraging the resources offered by mocap technology, human activity characteristics are captured and can be used as the source for animation. The devices involved in the technology are therefore very costly and hence not practical for personal use. In this scenario, we implement a framework capable of producing mocap data from standard RGB video and use it to animate a character in 3D space, based on the action of person in the original video with the help of deep learning techniques. The Human Mesh Recovery (HMR) scheme is used to extract mocap data from the input video to determine where joints of the person in the input video are located in 3D space, using 2D pose estimation. The locations of 3D joints are used as mocap data and transferred to Blender with a simple 3D character using which the character can be animated. A subjective evaluation of our framework based on the metric called observation factor was performed and yielded an accuracy value of 73.5%.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132293533","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

Aircraft Engine Reliability Analysis using Machine Learning Algorithms 基于机器学习算法的飞机发动机可靠性分析

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342675

Deepankar Singh, Mithilesh Kumar, K. V. Arya, Sunil Kumar

{"title":"Aircraft Engine Reliability Analysis using Machine Learning Algorithms","authors":"Deepankar Singh, Mithilesh Kumar, K. V. Arya, Sunil Kumar","doi":"10.1109/ICIIS51140.2020.9342675","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342675","url":null,"abstract":"In the aviation industry, the reliability analysis of aircraft engines is essential for ensuring the smooth functioning of each component of an aircraft engine. The reliability analysis is also important to predict their scheduled maintenance event and the Remaining Useful Life (RUL) of engine parts. Existing approaches for engine reliability are based on numerical methods, which do not predict RUL accurately. Hence, a more accurate model is required for predicting maintenance events. The reliability of an aircraft engine can be measured using readings of different sensors. In this work, the performances of different machine learning algorithms are studied, and finally, a better algorithm is suggested for predicting RUL. Additionally, a classification approach is proposed to classify the health state of an engine. The experimental results show that the XGBoost gives the best prediction accuracy in terms of root mean square error. The proposed LightGBM-based classifier further enhances the maintenance prediction based on the health state of the aircraft engine. Thus, the proposed analysis shows that XGBoost and LightGBM is a better choice for predicting the RUL, and for classifying the health state of the aircraft engine.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123370739","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 Magnetic Resonance Coupling Based Touchless Pad for Human-Computer Interfacing 一种基于磁共振耦合的人机界面非触控板

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342687

V. K. Srivastava, Ashwani Sharma, Ananth Bharadwaj

引用次数: 2

A Review on Comprehensive analysis in curbing Diabetes Mellitus with the aid of Nanotools 纳米工具在糖尿病防治中的综合分析综述

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342707

Narayanam Srikanth, R. Nair, K. S. Siddharth

{"title":"A Review on Comprehensive analysis in curbing Diabetes Mellitus with the aid of Nanotools","authors":"Narayanam Srikanth, R. Nair, K. S. Siddharth","doi":"10.1109/ICIIS51140.2020.9342707","DOIUrl":"https://doi.org/10.1109/ICIIS51140.2020.9342707","url":null,"abstract":"Diabetes Mellitus is the third most common metabolic disorders observed among human population. In our research article, we have discussed the various methods for detection of blood glucose level and the process for administration of insulin using nanoparticles as a drug delivery medium. Development is seen in various disciplines such as material science, aerospace and robotics. Nanotechnology has the potential to improve life quality of diabetic patients using better treatment strategies. Novel strategies used to treat or manage diabetes mellitus are: use of polymeric, polysaccharides nanoparticles, inhaleable insulin or delivery via BioNEMS. There is also a focus in developing multifunctional polymeric substrates capable of simultaneous and continuous monitoring of blood glucose with closed loop delivery of insulin. Efficiency of these strategies, especially the multifunctional polymers, are still subject to clincal testing. However a lot of the diabetes relatively older delivery tactics using nanoparticles proved to be highly efficient, especially compared to current medical practices for managing this disease.","PeriodicalId":352858,"journal":{"name":"2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117178889","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

Modeling and Analysis of 3D IC Structures for Heat Mitigation by Thermal Through Silicon Vias 基于硅通孔散热的三维集成电路结构建模与分析

2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) Pub Date : 2020-11-26 DOI: 10.1109/ICIIS51140.2020.9342651

Debika Chaudhuri, Dalia Nandi Das, H. Rahaman, Tamal Ghosh

引用次数: 0