In the past few years, we have witnessed a number of powerful steganalysis technique proposed in the literature. These technique could be categorized as either specific or universal. Each category of techniques has a set of advantages and disadvantages. A steganalysis technique specific to a steganographic embedding technique would perform well when tested only on that method and might fail on all others. On the other hand, universal steganalysis methods perform less accurately overall but provide acceptable performance in many cases. In practice, since the steganalyst will not be able to know what steganographic technique is used, it has to deploy a number of techniques on suspected stego objects. In such a setting the most important question that needs to be answered is: What should the steganalyst do when the decisions produced by different steganalysis techniques are in contradiction? In this work, we propose and investigate information fusion techniques, that combine a number of steganalysis techniques. We start by reviewing possible fusion techniques which are applicable to steganalysis. Then we illustrate, through a number of case studies, how one is able to obtain performance improvements as well as scalability by employing suitable fusion techniques.