Indexing techniques are essential for efficiently storing and retrieving big data. Traditional indexing methods may not be suitable for uncertain environments due to their reliance on complete and accurate data. In such cases, probabilistic indexing techniques can be employed. These techniques assign probabilities to different values or attributes of the data, allowing for efficient retrieval even in the presence of uncertainty. Examples of probabilistic indexing techniques include inverted indexes with probabilistic weights and Bayesian networks. Handling uncertainty is a critical aspect of indexing big data in an uncertain environment. Our main objective in this paper is to propose a new method of semantic indexing of data in an uncertain environment. Basically, our proposed method is composed of two main parts: (i) a first part consists in processing the uncertain data in a textual document and, (ii) the second part consists in determining a new model of uncertain semantic indexing.We developed a series of experiments to evaluate our proposed solution by comparing it to the approaches studied in the literature. The results found showed that our solution is more efficient.

In order to contribute to safe sharing of 3D mul-tiresolution meshes, a new approach of crypto-watermarking is proposed. This approach is based on the use of RSA algorithm and spherical harmonics transform. The aim being is to increase the integration rate while maintaining mesh quality on the one hand and extract correctly inserted image on the other hand. To embed data, host mesh is decomposed using spherical harmonics transform. Resulting coefficients are watermarked twice to insert the grayscale image already encrypted using RSA algorithm. Finally, watermarked mesh is reconstructed through the use on 10% of coefficients already calculated. Found results prove that our approach is able to insert a high amount of data without influencing the mesh quality. The application of the most popular attacks does not prevent a correct extraction of data already inserted. Our algorithm is,then,robust against these attacks.