2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)最新文献_第3页

Adopting Machine Learning to Support the Detection of Malicious Domain Names 采用机器学习支持恶意域名检测

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340159

Fernanda Magalhães, J. Magalhães

{"title":"Adopting Machine Learning to Support the Detection of Malicious Domain Names","authors":"Fernanda Magalhães, J. Magalhães","doi":"10.1109/IOTSMS52051.2020.9340159","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340159","url":null,"abstract":"Nowadays there are many Domain Name System (DNS) firewall solutions to prevent users to access malicious domains. These can provide real time protection and block illegitimate communications. Most of these solutions are based on known malicious domain names lists (blocklists) that are being constantly updated. However, this way, it is only possible to block malicious communications for known malicious domains, leaving out many others that are malicious but have not yet been updated in the blocklists. In this paper we present a study on the usefulness of adopting machine learning to detect malicious domain names. From a large set of domain names classified in-advance as malicious or benign an enriched dataset with multiple features was created and analyzed. The exploratory analysis and the data preparation tasks were carried out and the results achieved by different machine learning classification algorithms. Depending on the classification algorithm, the accuracy results varied between 75% and 92% and the classification time ranged between 2.77 seconds and 5320 seconds. These results are interesting in that they make it possible to classify a new domain as malicious or not in a short time and with good hit rate.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123952798","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

Applications of Blockchain in Healthcare, Industry 4, and Cyber-Physical Systems 区块链在医疗保健、工业4.0和网络物理系统中的应用

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340215

Sai Mounika Tadaka, L. Tawalbeh

引用次数: 1

IOTSMS 2020 Message from the General Chairs 2020年IOTSMS大会主席致辞

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/iotsms52051.2020.9340220

引用次数: 0

Sensor Data Visualization on Google Maps using AWS, and IoT Discovery Board 使用AWS和物联网发现板在谷歌地图上实现传感器数据可视化

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340202

Vishakha Subhash Supekar, A. Ahmadinia

{"title":"Sensor Data Visualization on Google Maps using AWS, and IoT Discovery Board","authors":"Vishakha Subhash Supekar, A. Ahmadinia","doi":"10.1109/IOTSMS52051.2020.9340202","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340202","url":null,"abstract":"The changing environment plays a vital role in the health of humans as well as animals. Due to the grave impacts of pollution and increased temperature on human health, it is of utmost importance to monitor the environment parameters at every step. With the recent developments in the Internet of Things (IoT), monitoring these parameters in real-time has become possible and cost-effective. In this paper, we have designed and implemented a web application to demonstrate an intelligent temperature and humidity reporting system using IoT and cloud. This application aims to provide a visual map for the users to analyze the temperature and humidity in different areas to make an informed decision. The proposed system provides a new solution by utilizing the sensor activity on various applications using Amazon Web Services that can be used as a prototype in strengthening real-time localized temperature and humidity data monitoring in many applications such as Nest, activating farm sprinklers based on weather data, and helping patients sensitive to high temperature and high humidity to take prompt action upon real-time notification on change in temperature or humidity.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126759241","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

IOTSMS 2020 Table of Contents IOTSMS 2020目录

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/iotsms52051.2020.9340193

引用次数: 0

A Novel Gateway Selection Protocol for Three-layers Integrated Wireless Networks 一种新的三层集成无线网络网关选择协议

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340161

Raghad Al-Syouf, M. Shurman, A. Alma'aitah, Sharhabeel H. Alnabelsi

引用次数: 1

Network Formation in 6TiSCH Industrial Internet of Things under Misbehaved Nodes 不良节点下6TiSCH工业物联网网络的形成

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340200

Yassine Boufenneche, Rafik Zitouni, L. George, Nawel Gharbi

{"title":"Network Formation in 6TiSCH Industrial Internet of Things under Misbehaved Nodes","authors":"Yassine Boufenneche, Rafik Zitouni, L. George, Nawel Gharbi","doi":"10.1109/IOTSMS52051.2020.9340200","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340200","url":null,"abstract":"Time Slotted Channel Hopping (TSCH) is a new Medium Access Control (MAC) protocol proposed by the IEEE 802.15.4e standard. It is designed to meet the requirements of industrial networks, such as high Packet Delivery Ratio (PDR) and bounded delays, along with low energy consumption. TSCH is now the basis of a full stack for Industrial Internet of Things (IIoT) proposed by the International Engineering Task Force (IETF), known as 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e). Since 6TiSCH networks are expected to offer high performance and fast bootstrapping, the network formation time could be impacted by the network size and the rate of control packets. In this paper, we demonstrate that non cooperative nodes, which can be malicious, could also drastically increase the network joining time. First, we propose the attack model and its implementation on the 6TiSCH simulator. Then, we carry out a set of experiments for different network sizes. Finally, we show through simulation results the impact of the proposed attack on the joining time.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122299842","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

Resilient IoT-based Monitoring System for Crude Oil Pipelines 基于物联网的原油管道弹性监测系统

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340197

Safuriyawu Ahmed, Frédéric Le Mouël, N. Stouls

引用次数: 5

Quantifying Security and Performance of Physical Unclonable Functions 物理不可克隆功能的安全性和性能量化

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340212

Fahem Zerrouki, Samir Ouchani, Hafida Bouarfa

引用次数: 1

Indoor Temperature Characterization and its Implication on Power Consumption in a Campus Building 校园建筑室内温度特征及其对能耗的影响

2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) Pub Date : 2020-12-14 DOI: 10.1109/IOTSMS52051.2020.9340229

Ali Safari Khatouni, M. Bauer, H. Lutfiyya

{"title":"Indoor Temperature Characterization and its Implication on Power Consumption in a Campus Building","authors":"Ali Safari Khatouni, M. Bauer, H. Lutfiyya","doi":"10.1109/IOTSMS52051.2020.9340229","DOIUrl":"https://doi.org/10.1109/IOTSMS52051.2020.9340229","url":null,"abstract":"Building monitoring and management are some of the important components of smart cities. It provides valuable information to the city manager and power supplier to better optimize their resources. With a steady rise in electricity prices in recent years, the importance of efficient use of the Heating, Ventilating, and Air-Conditioning (HVAC) systems becomes vital since they contribute to more than 10% of building power consumption. Given the growth on the Internet of Things (IoT) more HVAC equipment is being deployed with sensors. These sensors can produce large amounts of data that can be transformed into knowledge about the operation of a building. In this paper, we examine a large amount of sensor data from a building with more than 200 rooms. We analyze the power consumption of the building and compare different algorithms to predict the power consumption of the building using indoor and outdoor temperatures. We compare 8 different Machine Learning (ML) algorithms in order to examine their effectiveness. We then cluster rooms based on the temperature settings. Our evaluation results illustrate reasonable prediction accuracy and pinpoint several clusters with an inefficient temperature setting. The results can help the university to better utilize its resources and reduce the power consumption costs.","PeriodicalId":147136,"journal":{"name":"2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131484093","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