Abstract
IP geolocation, which is important for the security of devices, heavily relies on the number of high-quality landmarks. As one kind of widely used Internet of Things (IoT) devices, Internet webcams are exposed to the Internet intentionally or unintentionally. While there are few researches on the methodology to extract landmarks for Internet webcams by now. In this paper, we proposed a framework GeoWAT to automatically generate landmarks from the watermarks of the webcams, which are accurate enough to improve some IP geolocation services. GeoWAT uses Optical Character Recognition (OCR) techniques to get text locations from the watermarks of public webcams on the Internet websites. Then GeoWAT queries the locations through online maps to get latitudes/longitudes of webcams as landmarks. We conducted experiments to evaluate the performance and effectiveness of GeoWAT in real world. Our results show that GeoWAT could automatically extract the locations of webcams with high precision and recall. Also, GeoWAT have got more accurate landmarks than other IP location services, such as IPIP, GeoLites2 and ipstack, on the webcams dataset we collected from the whole world.
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Ren, Y., Li, H., Zhu, H., Sun, L., Wang, W., Li, Y. (2020). The Mining of IP Landmarks for Internet Webcams. In: Hao, Z., Dang, X., Chen, H., Li, F. (eds) Wireless Sensor Networks. CWSN 2020. Communications in Computer and Information Science, vol 1321. Springer, Singapore. https://doi.org/10.1007/978-981-33-4214-9_19
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DOI: https://doi.org/10.1007/978-981-33-4214-9_19
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