The goal of steganalysis is to identify suspected files (images, text, etc.) and to determine whether or not they have a payload encoded into them, and, if possible, recover the payload. Many different hypotheses may be chosen for modeling a steganography/ steganalysis problem. Our work focused on the case in which Eve, the steganalyst, has partial or erroneous knowledge of the cover distribution. More precisely we suppose that Eve knows the algorithms and the payload size that has been used by Alice, the steganographer, but she ignores the images distribution. In this source-cover mismatch scenario, we demonstrate that an Ensemble Classiffier with Features Selection (EC-FS) allows the steganalyst to obtain the best state-of-the-art performances, while requiring 100 times smaller training database compared to the previous state-of-the art approach. Moreover, we propose the islet approach in order to increase the classification performances [ART.9, CACT.61]. This first work raised the issue of 3-D object security. Indeed, it as been increasingly brought to the attention of the public by the expansion of new multimedia technologies such as the 3-D printing. In the development of cryptosecurity systems of 3-D objects, we can identify two major directions represented by the cryptography and digital watermarking. A good security system has to be format compliant, has to preserve the original bit rate and, whenever possible, it should be reversible. Watermarking methodology has the advantage of ensuring that the embedded hidden message can be verified at any processing stage such as the transmission, storage and when visualizing the embedding media. We performed a review of the previous work in 3-D security and analyzed the crypto-security of a 3-D watermarking method which embeds information by mesh surface distortion minimization. Then, we discuss future avenues of research by presenting emerging applications [ART.24, CACT.37]. We also proposed a new retrieval approach for 3D non-rigid objects. The proposed method consists in using the Reeb graph representation as local shape descriptor. The generated Reeb graph, based on the heat diffusion properties, is segmented into Reeb charts having a controlled topology. Each Reeb chart is associated with a couple of geometrical signatures, based on the area and angle distortions. The matching procedure is carried out on each pair of Reeb charts, according to the minimum dis-tance between the corresponding signatures. A global similarity measure quantifies the degree of correspondence between all the matched Reeb charts. Experimental results, conducted on SHREC 2011 dataset, have shown that our retrieval approach provides an overall retrieval efficiency gain compared to three state-of-the-art methods[ ART.11.