Spoof Detection in a Zigbee Network Using Forge-Resistant Network Characteristics (RSSI and LQI)
| العنوان: | Spoof Detection in a Zigbee Network Using Forge-Resistant Network Characteristics (RSSI and LQI) |
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| المؤلفون: | Muhammed Bashir Mu’azu, Christopher Bahago Martins, Ime Umoh Jarlath, Emmanuel Adedokun Adewale |
| المصدر: | Communications in Computer and Information Science ISBN: 9783030691424 ICTA |
| بيانات النشر: | Springer International Publishing, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Dynamic time warping, Spoofing attack, business.industry, Computer science, Node (networking), ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, 020208 electrical & electronic engineering, Testbed, 020206 networking & telecommunications, 02 engineering and technology, Smart grid, Application areas, 0202 electrical engineering, electronic engineering, information engineering, Wireless, ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS, business, Wireless sensor network, Computer network |
| الوصف: | The development of a spoof detection framework in a ZigBee network using forge-resistant network characteristics is presented. ZigBee has become ubiquitous in application areas such as Wireless Sensor Networks (WSNs), Home Area Networks (HANs), Smart Metering, Smart Grid, Internet of Things (IoT) and smart devices. Its pervasiveness and suitability for vast applications makes it a tempting target for attackers. Due to the open nature of the wireless medium, ZigBee networks are susceptible to spoofing attacks; where an illegitimate/Sybil node impersonates or disguises as one or multiple legitimate nodes with malicious intentions. A testbed consisting of two ZU10 ZigBee modules was setup to create a real ZigBee network environment. Received Signal Strength Indicator (RSSI) and the corresponding Link Quality Indicator (LQI) data were collected. The Dynamic Time Warping (DTW) algorithm was used for time series classification and similarity measurement of these dataset over variable physical distances. The framework was able to differentiate ZigBee signals that are at least 1 m apart. |
| ردمك: | 978-3-030-69142-4 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::13f5720b4805a4500ddf251efd3f1e0c https://doi.org/10.1007/978-3-030-69143-1_26 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........13f5720b4805a4500ddf251efd3f1e0c |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783030691424 |
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