An information system is composed of two types of entities, subjects like users and objects like databases from the security viewpoint. A subject issues an operation to an object to manipulate data in the object. An object is protected from malicious accesses of unauthorized subjects in the AC (Access Control) models. Nevertheless, if data in an object \(o_j\) is stored in another object \(o_k\) , a subject \(s_i\) which is allowed to read \(o_k\) can read the data of \(o_j\) in \(o_k\) even if \(s_i\) is not granted an access right of \(o_j\) , i.e. illegal information flow from \(o_j\) to \(s_i\) occurs. In our previous studies, the O-IFC (Object-based Information Flow Control) is proposed where operations occurring illegal information flow are prohibited. Here, a unit of data exchanged among entities is an object. Even if some operations do not occur illegal information flow, the operations are prohibited in the O-IFC. In order to reduce the operations unnecessarily prohibited, a novel C-IFC (Content-based IFC) is proposed where a finer unit of data than an object is considered to be exchanged among entities. In this article, an object is composed of natural language sentences. It is critical to decide whether or not a sentence \(st_j\) in \(o_j\) is the same as another sentence \(st_k\) in \(o_k\) . In this article, the sentence classifier is used which is generated by using the large language model based on the neural networks. If \(st_j\) and \(st_k\) are decided to be the same by the sentence classifier, the sentences are referred to as paraphrases. In the evaluation, the operations unnecessarily prohibited in the C-IFC are fewer than the O-IFC.
