A Novel Localization Method of Wireless Covert Communication Entity for Post-Steganalysis

Abstract

Recently, some criminals have begun to use multimedia steganography to conduct covert communication, such as transmitting stolen trade secrets. After using steganalysis to find covert communication entities, obtaining their locations can effectively help criminal forensics. This paper proposes a novel localization method of wireless covert communication entity for post-steganalysis. The method is based on hybrid particle swarm optimization and gray wolf optimization to improve localization precision (ILP-PSOGWO). In this method, firstly, the relationship model between received signal strength (RSS) and distance is constructed for the indoor environment where the target node exists. Secondly, dichotomy is used to narrow the region where the target node is located. Then, the weighted distance strategy is used to select the reference point locations with strong and stable RSS. Finally, the intersection region of the reference points is taken as the region where the target node is located, and the hybrid PSOGWO is used to locate and optimize the target node location. Experimental results demonstrate that ILP-PSOGWO can maintain high stability, and 90% of the localization errors are lower than 0.9012 m. In addition, compared with the existing methods of PSO, GWO and extended weighted centroid localization (EWCL), the average localization error of ILP-PSOGWO is also reduced by 28.2–49.0%.