Content authentication and tampering detection of Arabic text: an approach based on zero-watermarking and natural language processing

Due to the rapid increase in exchange of text information via internet network, the security and the reliability of the digital content has become a major research issue. The main challenges faced by researchers are content authentication, integrity verification and tampering detection of digital contents. In this paper, these issues are addressed with great emphasis on text information, which is natural language dependent. Hence, a novel intelligent zero-watermarking approach is proposed for content authentication and tampering detection of Arabic text contents. In the proposed approach, both the embedding and extracting of the watermark are logically implemented, which causes no change on the digital text. This is achieved by using fourth-level-order and alphanumeric mechanism of Markov model as a soft computing technique for the analysis of Arabic text to obtain the features of the given text which is considered as the digital watermark. This digital watermark is later used for the detection of any tampering attack on the received Arabic text. An extensive set of experiments using four datasets of varying lengths proves the effectiveness of the proposed approach in terms of robustness, effectiveness and applicability under multiple random locations of insertion, reorder and deletion attacks. Compared with baseline approaches, the proposed approach has improved performance regarding watermark robustness and tampering detection accuracy.