Geo-Tagged Spoofing Detection using Jaccard Similarity

Abstract

In recent years, position evaluation of mobile devices has developed as an essential part of social movement. Meantime, the criminals may interfere with the information of geographical position (geo-position), and they can adjust the geo-position for their convenience. Therefore, it is important to identify the authenticity of geo-position. In this paper, an instant messaging platform-based geo-tagged spoof image detection system is created using Jaccard similarity. With the help of a Fuzzy filter, the input, as well as spoofing images, are subjected to camera footprint extraction, and their corresponding outputs are fused by Dice Coefficient. Moreover, the input as well as spoofed images is subjected to geotagged process, and their corresponding geotagged input, and geotagged spoofed images are fused by Tanimoto similarity. At last, the fused images from Dice Coefficient, and Tanimoto similarity are employed for the spoof detection process, where the Jaccard similarity compares the two images using Dicerete Cosine Transform (DCT). Consequently, the spoofed images are detected, and their effectiveness is measured in terms of accuracy, False Positive Rate (FPR), and True Positive Rate (TPR), as well as the corresponding values are attained like 0.099, 0.892, and 0.896 respectively.