The security of transmitting data over the Internet is always of great concern. As a popular research topic, an efficient steganographic technique aims to hide a secret message for secure transmission over the Internet. In this paper, we propose a new information hiding method based on the difference value between the maximum and minimum pixels in an image block and using Modified Least Significant Bit (LSB) substitution strategy to conceal data. The difference value will be in one of three levels (lower, middle, and higher). Using Modified LSB substitution, the lower, middle, and higher levels correspond to 3-, 4-, and 5-bit embedded secret data, respectively. The experimental results demonstrate that the embedding capacity of the proposed method is greater than previous contributions and maintain a good image quality of stego images that are generated by the proposed method.

A novel watermarking scheme is proposed that could substantially improve current watermarking techniques. This scheme exploits the features of micro images of watermarks to build association rules and embeds the rules into a host image instead of the bit stream of the watermark, which is commonly used in digital watermarking. Next, similar micro images with the same rules are collected or even created from the host image to simulate an extracted watermark. This method, called the features classification forest, can achieve blind extraction and is adaptable to any watermarking scheme using a quantization-based mechanism. Furthermore, a larger size watermark can be accepted without an adverse effect on the imperceptibility of the host image. The experiments demonstrate the successful simulation of watermarks and the application to five different watermarking schemes. One of them is slightly adjusted from a reference to especially resist JPEG compression, and the others show native advantages to resist different image processing attacks.

The technologies of internetworking and databases have expedited the distributed database systems being implemented in the global information systems. But we cannot avoid the occurrence of random missing values in the process of gathering data. The research on association rules can effectively establish the relationship of attributes in databases containing missing values. While this technique is used to resolve the issues on replacing the missing values, the integrity of the methodology and the measurability of the quality can already be verified in related essays. However, the accuracy of replaced missing values in the database can only be satisfactory with specific criteria and a higher completion rate cannot yet be achieved. In other words, a given accuracy cannot be reached at the same time as resolving the database validity issues. Therefore, we propose a rule recycle technique, which reuses and composes the rules in order to retrieve more complete attribute value association rules. This will not only enable the database recovered to improve the accuracy and completion rate but also increase the validity of missing value completion.

Along with the development of networking technology, distributed databases exist in most companies. It is important to place data in the most appropriate locations so that the efficiency of data processing can be increased and the cost of data processing can be reduced. Most recent research programs study the data allocation problems of existing distributed databases by analyzing the system operation history, such as frequency of query and data affinity. For a new distributed database system construction, a requirements analysis method based on ontology is discussed and applied to data allocation in distributed databases.