Character property method with biometric multifactor authentication for arabic text steganography

Text steganography is an ancient means of secret communication that uses the text hiding process to conceal a message and, when combined with cryptography, enhances its level of security. However, it is limited in its ability to optimize embedded data capacity with a high perceptual transparency level that will also not raise suspicion when written. Besides that, other concerns are active attacks by intruders which are a crucial security issue in the transmission of the shared secret key that enables the receiver to extract the secret information. Also, such attacks can be infected through a fake identity that allows the receiver to modify the secret information thus degrading its integrity. To overcome these drawbacks, we propose the Character Property method, which uses the basic properties of the Arabic Text such as dots, calligraphy typographical proportions, and sharp-edges to hide the secret message using a table index mapping technique to optimize data capacity with high perceptual transparency to avert suspicion. We apply biometric multi factor authentication to enhance the security of the transmitted shared secret key used to extract the stego-text. The designed biometric multi factor authentication has a liveness detection feature to spot a receiver’s fake identity. The biometric multi factor authentication is implemented through a custom Arduino smart watch with a fingerprint and heartbeat sensor as a proof of concept device which increases capacity in hiding the secret message by up to 23.5% compared to the previous methods. Since the designed method does not affect the stego-text appearance, its 1.0 Jaro Similarity score as compared to the other methods proves the high transparency of the stegotext. The biometric device evaluation results in a false rejection rate of only 4% while the false acceptance rate is 0%. The results are significant for the liveness detection with 0% results for both false acceptance of fake inputs (FerrFake) and false rejection of live subject (FerrLive) compared with a fingerprint-only biometric authentication approach which has a high percentage of up to 13% of false acceptance of fake inputs (FerrFake). To conclude, the Character Property method with biometric multi factor authentication provides an optimum embedded data capacity and a high level of perceptual transparency in hiding secret information together with a high level of user authorization that offers the liveness detection of users. This method with biometric multifactor authentication offers a new perspective on Arabic text steganography to cover both passive and active attack issues.

Text FSKTM 2020 29 - IR.1.pdf Download (1MB)

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