In this paper we present an intrusion detection engine comprised of two main elements; firstly, a neural network for the actual detection task and secondly watermarking techniques for protecting the related information that must be exchanged between nodes. In particular, we exploit information visualization and machine learning techniques in order to achieve efficient and effective intrusion detection. In order to avoid possible modification or alteration of the maps produced by the intrusion detection engine, we focus on safeguarding and authenticating them using a novel embedded watermarking method. Previously, we had shown promising results in the intrusion detection task using this system. This paper focuses on the watermarking technique and gives a detailed exposition that includes an experimental evaluation of its quality.