Performance analysis on secured data method in natural language steganography

Abstract

The rapid amount of exchange information that causes the expansion of the internet during the last decade has motivated that a research in this field. Recently, steganography approaches have received an unexpected attention. Hence, the aim of this paper is to review different performance metric; covering the decoding, decrypting and extracting performance metric. The process of data decoding interprets the received hidden message into a code word. As such, data encryption is the best way to provide a secure communication. Decrypting take an encrypted text and converting it back into an original text. Data extracting is a process which is the reverse of the data embedding process. The effectiveness evaluation is mainly determined by the performance metric aspect. The intention of researchers is to improve performance metric characteristics. The evaluation success is mainly determined by the performance analysis aspect. The objective of this paper is to present a review on the study of steganography in natural language based on the criteria of the performance analysis. The findings review will clarify the preferred performance metric aspects used. This review is hoped to help future research in evaluating the performance analysis of natural language in general and the proposed secured data revealed on natural language steganography in specific.

Review on feature-based method performance in text steganography

“…Steganoraphy is the scientific knowledge information that hide the hidden message implementation in several media that are unrecognized by human vision [4]. The steganography impelementationis could be applied in private communication, security system protection and any confidential data that is commonly used by government, military, industry and etc [5]. From that history, steganography is introduced as information hiding field that hides the confidential information to avoid the message from the third party [6].…”