Detecting fingerprints of audio steganography software

Gong, Caili; Zhang, Jinghong; Yang, Yunzhao; Yi, Xiaowei; Zhao, Xianfeng; Ma, Yi

doi:10.1016/j.fsir.2020.100075

Cited by 7 publications

(6 citation statements)

References 12 publications

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“…On the other hand, attackers may try to detect Fig. 11 The quality of the stego file generated by Jung and Yoo [29], Ahmad and Fiqar [30], Andra et al [32], Bobeica et al [33], Ahmad et al [31], and the proposed technique with e = 3 , m = 1 , h = 0 and h = 4 the existence of hidden information in the stego audio [38,39]. Although it is out of the scope of this investigation, this possible attack should be anticipated.…”

Section: Discussionmentioning

confidence: 99%

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

Ahmad

Samudra

2020

J Big Data

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In this age, information technology has grown significantly. Computer networks, which connect a device to others, have made it easier for people to transfer data than before. Moreover, smart devices have the capability of supporting this data transmission, including those in the cloud that may contain massive data. However, the security factor can be a severe issue if sensitive big data, such as military and medical data, do not have enough protection. Furthermore, an attacker may be able to disclose such data. Some algorithms have been introduced to solve that problem, one of which is the data hiding method. Nevertheless, some factors are still challenging, concerning the capacity of the secret data and the quality of the generated data, which are represented by bit and Peak Signal-to-Noise Ratio (PSNR), respectively. Besides, some techniques are not reversible, which means that they cannot reconstruct the carrier (cover). In this research, we investigate those problems by taking audio as the carrier. It is done by sampling the audio file before being interpolated to present spaces for accommodating the secret. Meanwhile, the secret is segmented before the embedding. Later, the embedded audio is smoothed according to the required level. The experimental result is obtained by using a public data set containing various audio genres and instruments, and 11 secret sizes, from 1 to 100 kb. It shows that the proposed method outperforms the others. This higher PSNR value means that the proposed method can generate more similar stego data; it also implies that at a certain quality level, the number of bits that can be hidden in the audio cover is higher than that of others.

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Section: Discussionmentioning

confidence: 99%

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

Ahmad

Samudra

2020

J Big Data

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“…Steganography can be detected via various tools, taking into account their three components: the sender, received and the carrier [3]. Steganalysis is the practice of detecting the use of steganography [18] and research states that, currently, there are two different types of approach in stenography identification: the first is the targeted steganalysis which to detects a particular algorithm; the second, is capable of detecting steganalysis without knowing the steganographic algorithms [19]. The method used depends on the hiding technique [15].…”

Section: Detention Techniquesmentioning

confidence: 99%

“…Nevertheless, we need to keep in mind that with the increasing of steganographic software's, the steganalysis methods need to keep up with the demand [19].…”

Section: Detention Techniquesmentioning

confidence: 99%

Steganography and Computer Forensics - the art of hiding information: a systematic review

Fernandes

2022

ARIS2-Journal

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This paper focuses on the study of steganoprahy as an anti-forensic method. The purpose of steganography techniques is to hide information from individuals unrelated to its content. Through a systematic review, the objectives of this article are: (I) explore and investigate the importance of steganography in computer forensics; (II) understand and analyze the methodology used to hide information in a file and (III) understand and analyze the methodology used to extract the information. The results summarize the previous research on this topics and we conclude the article with a warning to develpop more studies regarding this thematic as well as and make the security forces aware of this type of digital evidence and, in the same way that the methodology is being developed, the stegananalysis must also seek, at least, to reach the same technological level

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“…The encryption, on the other hand, is a way of transforming the overall view of understood data into a disfigured one, so the encrypted message appears to contain important data that requires deciphering. The encryption would fail if the intruder were to be able to decrypt the cipher message, while Steganography fails to secure data when the attacker detects the presence of a secret data inside the cover file [4], [5]. Thus, for more ensuring data security, steganography and encryption are used together so that any observer would struggle to detect messages and, even upon retrieval, it would remain indecipherable and meaningless [6].…”

Section: Introductionmentioning

confidence: 99%

Audio steganography with enhanced LSB method for securing encrypted text with bit cycling

et al. 2022

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Data security pressing issue, particularly in terms of ensuring secure and reliable data transfer over a network. Encryption and seganography play a fundamental role in the task of securing data exchanging. In this article, both steganography and cryptography were combined to produce a powerful hybrid securing stego-system. Firstly, a text message is encrypted with a new method using a bits cycling operation to give a cipher text. In the second stage, an enhanced LSB method is used to hide the text bits randomly in an audio file of a wav format. This hybrid method can provide effectually secure data. Peak signal-to-noise ratio (PSNR), mean squared error (MSE) and structural similarity (SSIM) were employed to evaluate the performance of the proposed system. A PSNR was in range (60-65) dB with the enhanced least significant bit (LSB) and the SSIM had been invested to calculate the signal quality, which scored 0.999. The experimental results demonstrated that our algorithm is highly effective in securing data and the capacity size of the secured text. Furthermore, the time consumption was considerably low, at less than 0.3 seconds.

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Detecting fingerprints of audio steganography software

Cited by 7 publications

References 12 publications

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

Steganography and Computer Forensics - the art of hiding information: a systematic review

Audio steganography with enhanced LSB method for securing encrypted text with bit cycling

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