Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk
The introduction of the Internet of Things (IoT), i.e., the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like clo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/19/4107 |
| _version_ | 1811185202520653824 |
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| author | Sharad Agarwal Pascal Oser Stefan Lueders |
| author_facet | Sharad Agarwal Pascal Oser Stefan Lueders |
| author_sort | Sharad Agarwal |
| collection | DOAJ |
| description | The introduction of the Internet of Things (IoT), i.e., the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like closed circuit television (CCTV) cameras, internet protocol (IP) phones, and oscilloscopes, is overwhelming for end users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world. |
| first_indexed | 2024-04-11T13:25:24Z |
| format | Article |
| id | doaj.art-2b03dd7daf1348deaf588d3e29e3f709 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:25:24Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2b03dd7daf1348deaf588d3e29e3f7092022-12-22T04:22:05ZengMDPI AGSensors1424-82202019-09-011919410710.3390/s19194107s19194107Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security RiskSharad Agarwal0Pascal Oser1Stefan Lueders2CMS Experiment, European Organization for Nuclear Research (CERN), 1211 Geneva, SwitzerlandCERN Computer Security Team, European Organization for Nuclear Research (CERN), 1211 Geneva, SwitzerlandCERN Computer Security Team, European Organization for Nuclear Research (CERN), 1211 Geneva, SwitzerlandThe introduction of the Internet of Things (IoT), i.e., the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like closed circuit television (CCTV) cameras, internet protocol (IP) phones, and oscilloscopes, is overwhelming for end users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.https://www.mdpi.com/1424-8220/19/19/4107Internet of Thingssecurityvulnerabilities and protective measurescontrol network securityoperation in multi-user environmentsrisk assessment |
| spellingShingle | Sharad Agarwal Pascal Oser Stefan Lueders Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk Sensors Internet of Things security vulnerabilities and protective measures control network security operation in multi-user environments risk assessment |
| title | Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk |
| title_full | Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk |
| title_fullStr | Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk |
| title_full_unstemmed | Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk |
| title_short | Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk |
| title_sort | detecting iot devices and how they put large heterogeneous networks at security risk |
| topic | Internet of Things security vulnerabilities and protective measures control network security operation in multi-user environments risk assessment |
| url | https://www.mdpi.com/1424-8220/19/19/4107 |
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