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Journal articles on the topic 'Audio steganography'

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Published: 4 June 2021

Last updated: 15 June 2025

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Alieksieiev, Artem, and Igor Svatovskiy. "ANALYSIS OF COMMON AUDIO STEGANOGRAPHY METHODS." Grail of Science, no. 34 (December 16, 2023): 117–18. http://dx.doi.org/10.36074/grail-of-science.08.12.2023.24.

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In the face of modern challenges, the protection of vital interests of a person and a citizen is fundamental to the issue of national security. In this context, the ability to freely transfer confidential information is very important. One of the possible solutions is the use of steganographic methods. Digital audio steganography has advantages over other types of steganography. This makes it important to analyze the most common audio steganography methods.

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Noor Azam, Muhammad Harith, Farida Ridzuan, M. Norazizi Sham Mohd Sayuti, A. H. Azni, Sakinah Ali Pitchay, and Najwa Hayaati Mohd Alwi. "A Method of Cover Audio Selection for Embedding Based on Various Criteria." ITM Web of Conferences 63 (2024): 01001. http://dx.doi.org/10.1051/itmconf/20246301001.

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The main goal of an audio steganography method is to improve the capacity, im-perceptibility, and robustness. Several methods of audio steganography have been proposed to enhance its capabilities. To further optimize the efficiency of the audio steganography method, this paper proposes to select the appropriate audio cover for concealing the message. The selection of an appropriate cover can significantly improve the quality of the output and facilitate the development of innovative audio steganography techniques. This paper proposed a new audio cover selection method, which can further enhance the characteristics of the resulting output. This method ranked each cover according to the qualities that need to be boosted using various measurements. These measurements are the Maximum Available Space (MAS), Peak Signal to Noise Ratio (PSNR) and Bit Error Rate (BER) for capacity, imperceptibility, and robustness respectively. Based on the experiment conducted using five cover audios stored in the self-created database, each audio is ranked differently based on the measurement used to determine its characteristic level. In conclusion, the proposed cover selection method can be used to select the most proper cover, hence improving the characteristics of audio steganography.

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Buchyk, Serhii, Oksana Khomenko, and Yuriy Serpinsky. "Steganographic system for hiding text information in audio files." Information systems and technologies security, no. 1 (6) (2023): 13–20. http://dx.doi.org/10.17721/ists.2023.1.13-20.

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Audio file steganography can be used as an effective and efficient method to hide messages, but it is a complex process because the human auditory system is sensitive to small changes in audio data. In this article an improved approach for hiding secret text message in audio is presented, combining steganography and cryptography. The Least Significant Bits (LSB) technique, one of the most common and basic methods of steganography, is used as an algorithm for steganographic transformation. The described point of this method is to replace the least significant bits of the audio container with message bits that contain not very useful information, so filling them with additional information has little effect on the quality of perception. Such a significant disadvantage as the low level of reliability is improved by the introduction of a cryptographic layer, the feasibility of which is justified in the article. Cryptographic protection has been added in the form of one of the modern symmetric encryption algorithms – the AES algorithm in the CBC mode. Pseudo-random numbers are used to create a stable cryptokey. The cryptoalgorithm is used to protect the message, which after cryptographic conversion is hidden in the audio file using the steganographic LSB method. The main characteristics of the stegosystem are analyzed. In this paper, the application system of steganographic protection of information in audio files using a cryptographic algorithm is implemented using the environment of Microsoft Visual Studio 2019 and cryptographic libraries, the programming language is C ++. A WAV audio file was used as the digital container. NIST tests were used to assess resistance to stegoanalysis, which according to the results is better using an improved method compared to the classical LSB approach. In addition, the steganographic algorithm is evaluated by visual analysis by comparing the original audio file and the stegofile with the hidden message. The results of the analysis indicate the absence of traces of steganography. Based on the obtained results, it can be argued about the reliability and efficiency of the proposed approach, so the use of LSB-AES technique can be proposed to ensure secure data transmission.

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Al Hadad, Zeina, and Ibtisam Hassoun Ali. "Survey in Image and Audio Steganography by using the Deep Learning Methods." Journal of Kufa for Mathematics and Computer 10, no. 2 (2023): 132–39. http://dx.doi.org/10.31642/jokmc/2018/100222.

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Steganography is the practise of secretly encoding information into another medium (called a cover media) such that its existence cannot be identified. Steganography is the method that is utilised to successfully do this task. Through the use of digital image steganography, one is able to achieve the capacity of secure communication, which is vital in the bulk of the applications that are now being created. The use of steganography is applicable in a wide variety of advantageous settings. Its ascent to the forefront of current security systems may be attributed to a confluence of factors, including a phenomenal rise in processing power and a heightened awareness among individuals of the need of safeguarding their personal information. When it comes to the creation of a steganographic method, the most significant challenge that must be surmounted is finding the optimal balance between quality and quantity. The method is distinguished from linked systems like encryption and watermarking by its ability to embed information, as well as by the fact that it cannot be seen by the human eye. This article presents a thorough examination and analysis of some contemporary steganographic methods that are regarded as state-of-the-art approaches. In addition, we have included an in-depth discussion of the most important steganographic technologies now available. Recent steganographic techniques that are based on deep learning have been enhanced, which has enabled the resolution of issues that were previously present

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Dengre, Amit, and A. D. Gawande. "Audio Encryption and Digital Image Watermarking in an Uncompress Video." International Journal of Advances in Applied Sciences 4, no. 2 (2015): 66. http://dx.doi.org/10.11591/ijaas.v4.i2.pp66-72.

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The growth of high speed computer networks and that of the Internet, in particular, has increased the ease of Information Communication. Ironically, the cause for the development is also of the apprehension - use of digital formatted data. In comparison with Analog media, Digital media offers several distinct advantages such as high quality, easy editing, high fidelity copying, compression etc. But this type advancement in the field of data communication in other sense has hiked the fear of getting the data snooped at the time of sending it from the sender to the receiver. So, Information Security is becoming an inseparable part of Data Communication. In order to address this Information Security, Steganography plays an important role. Steganography is the art and science of writing hidden messages in such a way that no one apart from the sender and intended recipient even realizes there is a hidden message. In the current internet community, secure data transfer is limited due to its attack made on data communication. So more robust methods are chosen so that they ensure secured data transfer. One of the solutions which came to the rescue is the audio Steganography. But existing audio steganographic systems have poor interface, very low level implementation, difficult to understand and valid only for certain audio formats with restricted message size. Enhanced Audio Steganography (EAS) is one proposed system which is based on audio Steganography and cryptography &amp; watermarking, ensures secure data transfer between the source and destination.

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Ghane, Mohamed C., Maider D. Uribarri, Ramzi Djemai, Dipo Dunsin, and Istteffanny I. Araujo. "A Novel Hybrid Method for Effective Identification and Extraction of Digital Evidence Masked by Steganographic Techniques in WAV and MP3 Files." Journal of Information Security and Cybercrimes Research 6, no. 2 (2023): 89–104. http://dx.doi.org/10.26735/izbk9372.

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Anti-forensics techniques, particularly steganography and cryptography, have become increasingly pressing issues affecting current digital forensics practices. This paper advances the automation of hidden evidence extraction in audio files by proposing a novel multi-approach method. This method facilitates the correlation between unprocessed artefacts, indexed and live forensics analysis, and traditional steganographic and cryptographic detection techniques. In this work, we opted for experimental research methodology in the form of a quantitative analysis of the efficiency of the proposed automation in detecting and extracting hidden artefacts in WAV and MP3 audio files. This comparison is made against standard industry systems. This work advances the current automation in extracting evidence hidden by cryptographic and steganographic techniques during forensic investigations. The proposed multi-approach demonstrates a clear enhancement in terms of coverage and accuracy, notably on large audio files (MP3 and WAV), where manual forensic analysis is complex, time-consuming and requires significant expertise. Nonetheless, the proposed multi-approach automation may occasionally produce false positives (detecting steganography where none exists) or false negatives (failing to detect steganography that is present). However, it strikes a good balance between efficiently and effectively detecting hidden evidence, minimising false negatives and validating its reliability.

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Hajer, Muatamed, and Mohammed Anbar. "Identifying optimal message embedding location in audio steganography using generative adversarial networks." Eastern-European Journal of Enterprise Technologies 4, no. 9(118) (2022): 59–68. http://dx.doi.org/10.15587/1729-4061.2022.263695.

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Audio steganography (AS) uses the auditory redundancy of the human ear to conceal the hidden message inside the audio track. In recent studies, deep learning-based steganalysis has swiftly revealed AS by extracting high-dimensional stego acoustic features for categorization. There is still an opportunity for improvement in the current audio steganography required for managing communication confidentiality, access control and data protection. The main objective of this research is to improving the data protection by identifying the data embedding location in the audio. Generative Adversarial Network-based Audio Steganography Framework (GAN-ASF) is presented in this study, and it can automatically learn to provide better cover audio for message embedding. The suggested framework's training architecture comprises a generator, a discriminator, and a steganalyzer learned using deep learning. The Least Significant Bit Matching (LSBM) message embedding technique encrypts the secret message into the steganographic cover audio, which is then forwarded to a trained steganalyzer for misinterpretation as cover audio. After performing the training, stenographic cover audio has been generated for encoding the secret message. Here, Markov model of co-frequency sub images to generate the best cover frequency sub-image to locate an image's hidden payload. Steganographic cover audio created by GAN-ASF has been tested and found to be of excellent quality for embedding messages. The suggested method's detection accuracy is lower than that of the most current state-of-the-art deep learning-based steganalysis. This payload placement approach has considerably increased stego locations' accuracy in low frequencies. The test results GAN-ASF achieves a performance ratio of 94.5 %, accuracy ratio of 96.2 %, an error rate of 15.7 %, SNR 24.3 %, and an efficiency ratio of 94.8 % compared to other methods.

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Maricar, M. Chaeril, and Seng Hansun. "Implementasi Audio Steganografi menggunakan 4th LSB dan Advanced Encryption Standard pada Windows Phone." Jurnal ULTIMA Computing 7, no. 1 (2016): 1–4. http://dx.doi.org/10.31937/sk.v7i1.442.

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Securing data during transmission become one of the problem in technology, those data can be intercepted and read by others. One preventive action to overcome this is by using steganography. This thesis implements an audio steganography using Windows Phone. Combination of Advanced Encryption Standard to secure data and Audio Wave Steganography which embedded data inside 4th LSB layer, resulting in increased safety and robustness against noise addition compared to 1st LSB. Index Terms—Advanced Encryption Standard, Audio Steganography, Audio Wave Steganography, Least Significant Bit, Windows Phone.

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Maurya, Indu, and S. K Gupta. "Understandable Steganography." International Journal of Engineering & Technology 7, no. 3 (2018): 1024. http://dx.doi.org/10.14419/ijet.v7i3.8940.

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For hiding information in a digitalized object Steganography is an important technique. It is a special kind of scientific technique which involves the secret information communication inside suitable cover objects of multimedia like image files, audio or videos. The embedded data and its existence are hidden with the help of Steganography. It is a method of hiding data which has enormously improved the security level of confidential data with the help of special hiding mechanism and is considered as remarkable achievement in the computational power. The main aims of Steganography are; capacity of concealed data along with its robustness, lack of detection etc. These are some of the additional features which make it distinguishing from other older techniques like watermarking as well as cryptography. In this research paper, we have surveyed Steganography of digital images and cover the basic and key concepts. In spatial representation the development of image Steganographic methodology in the format of JPEG, along with that we will also debate on the modern developments as far as Steganography is concerned.For increasing Steganographic security, specifically used approaches are shortlisted and the developments made after investigations are also presented in this paper.

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Jusoh, Suhaibah, Aida Mustapha, Azizan Ismail, and Roshidi Din. "A review of arabic text steganography: past and present." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 2 (2020): 1040. http://dx.doi.org/10.11591/ijeecs.v17.i2.pp1040-1046.

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<span>Steganography is a strategy for hiding secret information in a cover document in order to avoid attacker from predict about hidden information. Steganography exploit cover message, for instance text, audio, picture and video to hide the secret message. Before this, linguistic text steganographic techniques are implemented just for the English language. But nowadays different languages are used to hide the data like Arabic language. This language is still new in the steganography and still need practices for empowerment. This paper will present the text steganographic method for Arabic language, scholar paper within 5 year will be analyze and compared. The main objective of this paper is to give the comparative analysis in the Arabic steganography method that has been applied by previous researchers. Finally, the disadvantage and advantage of the method also will be presented in this paper.</span>

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G.mohammed, Sajaa. "A survey on Rijndael based LSB Audio Steganography techniques." Wasit Journal for Pure sciences 2, no. 4 (2023): 80–87. http://dx.doi.org/10.31185/wjps.245.

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The need to protect multimedia data security—including audio, video, and text—and the data it contains has persisted, whether in physical or digital form. This is due to the fact that the fabrication and fake of Multimedia data is widespread throughout the world, causing serious costs to people, societies, and the industrial sectors in addition to compromising national security. People are therefore concerned about safeguarding their employment and avoiding these illegal behaviors. To safeguard sensitive data, a variety of strategies including steganography, cryptography, and coding have been used. Steganography is a suitable technique that allows the user to hide a message inside of another message (cover media). The majority of steganography research makes use of cover material, like videos, images, and sounds. Notably, because to the challenges involved in locating embedded bits in an audio recording, audio steganography is typically not prioritized. By altering the least significant bits (LSBs) of audio samples, a technique known as audio steganography (LSB) can be used to conceal information in an audio stream. The least significant bits (LSBs) in a number's binary representation are the least weighted bits and are typically undetectable to the human ear. The audio signal can have a hidden message inserted in it without significantly affecting its perceptual quality by changing or manipulating the LSBs of the audio samples. To incorporate information into an audio, However, because to the slight audio difference, an assailant or other outsider might be able to hear this. To solve this problem, it is important to alter the audio in a way that it cannot be heard by the human ear but may still be understood by other means. This document is a summary of the available research in the field. We start by outlining the fundamentals of audio steganography and how it works. Then, three categories of audio steganography—statistical and random generation; and linguistics—are described. Each class's tactics are examined, with a focus on how a special method is offered for concealing sensitive information. In addition, we survey the existing works in the advancement of strategies and algorithms relevant to audio steganography; our survey, which covers work published from 2016 to 2023, is not exhaustive. This study gathers the present approaches, difficulties, and future directions in this topic with the goal of assisting other researchers .In addition, we survey the existing works in the advancement of strategies and algorithms relevant to audio steganography.

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Setiaji, Hartoko Carolus Ferdy, Suhartono Tjondronegoro, and Bambang Hidayat. "Audio Steganography using Modified Enhanced Least Significant Bit in 802.11n." Journal of Measurements, Electronics, Communications, and Systems 1, no. 1 (2015): 7. http://dx.doi.org/10.25124/jmecs.v1i1.1479.

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Steganography is a technique to improve the security of data, which is by inserting messages or confidential information using a medium called the host or carrier or cover. A wide variety of digital media can be used as a host, among others audio, image, video, text, header, IP datagram, and so forth. For audio steganography, the embedded audio is called stego-audio. Steganography can be cracked by using steganalysis. By exploiting the weaknesses of each steganography method. Many steganography method has been developed to increase its performance. This work proposed audio steganography scheme called Modified Enhanced Least Significant Bit (MELSB) which is modified version of Enhanced Least Significant Bit (ELSB). This method using Modified Bit Selection Rule to increase SNR and robustness of stego-audio. SNR result after applying MELSB scheme is increased. MELSB scheme also increase robustness of stego-audio. MELSB still work fine until amplification level 1.07. MELSB also work fine against noise addition better than ELSB and LSB. It give BER and CER with value 0 at SNR 33 dB. MELSB work fine in real-time condition on 802.11n WLAN if there is no transcoding and noise addition between senderâ€™s and recipientâ€™s computer.

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Li, Jing, Kaixi Wang, and Xiaozhu Jia. "A Coverless Audio Steganography Based on Generative Adversarial Networks." Electronics 12, no. 5 (2023): 1253. http://dx.doi.org/10.3390/electronics12051253.

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Traditional audio steganography by cover modification causes changes to the cover features during the embedding of a secret, which is easy to detect with emerging neural-network steganalysis tools. To address the problem, this paper proposes a coverless audio-steganography model to conceal a secret audio. In this method, the stego-audio is directly synthesized by our model, which is based on the WaveGAN framework. An extractor is meticulously designed to reconstruct the secret audio, and it contains resolution blocks to learn the different resolution features. The method does not perform any modification to an existing or generated cover, and as far as we know, this is the first directly generated stego-audio. The experimental results also show that it is difficult for the current steganalysis methods to detect the existence of a secret in the stego-audio generated by our method because there is no cover audio. The MOS metric indicates that the generated stego-audio has high audio quality. The steganography capacity can be measured from two perspectives, one is that it can reach 50% of the stego-audio from the simple size perspective, the other is that 22–37 bits can be hidden in a two-second stego-audio from the semantic. In addition, we prove using spectrum diagrams in different forms that the extractor can reconstruct the secret audio successfully on hearing, which guarantees complete semantic transmission. Finally, the experiment of noise impacts on the stego-audio transmission shows that the extractor can still completely reconstruct the semantics of the secret audios, which indicates that the proposed method has good robustness.

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Jain, Nikhil. "Wavelet Transform based Steganography." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 1398–402. http://dx.doi.org/10.22214/ijraset.2021.35105.

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Steganography is a technique which is used to hide audio signal behind an image in the transform domain using wavelet transform. The audio signal can be of any type, any format like MP3 or WAV or any other type is encrypted and hide behind an image without disclosing even the existence of audio signal to anyone. It gives the best way to send an audio signal by hiding the secret data.

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Alexander, Anu Sara, and L. C. Manikandan. "A Study on Steganography Concealing Data." European Journal of Engineering Research and Science 4, no. 5 (2019): 115–18. http://dx.doi.org/10.24018/ejers.2019.4.5.1337.

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Steganography is a process of hiding or concealing confidential information from unauthorized access. Steganography used in various fields such as military, aerospace and industrial applications. Steganography techniques are used for secure transmission of data from sender to receiver. The computer programmers, begins applying steganography techniques to video as well as audio files. This time multimedia data like image, audio, video are used as a cover media by steganography systems because public often send digital pictures in email and other Internet communication. The purpose of this review is to bring the idea of Steganography for young researchers.

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Alexander, Anu Sara, and L. C. Manikandan. "Study on Steganography Concealing Data." European Journal of Engineering and Technology Research 4, no. 5 (2019): 115–18. http://dx.doi.org/10.24018/ejeng.2019.4.5.1337.

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Phipps, Anthony, Karim Ouazzane, and Vassil Vassilev. "Securing Voice Communications Using Audio Steganography." International Journal of Computer Network and Information Security 14, no. 3 (2022): 1–18. http://dx.doi.org/10.5815/ijcnis.2022.03.01.

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Although authentication of users of digital voice-based systems has been addressed by much research and many commercially available products, there are very few that perform well in terms of both usability and security in the audio domain. In addition, the use of voice biometrics has been shown to have limitations and relatively poor performance when compared to other authentication methods. We propose using audio steganography as a method of placing authentication key material into sound, such that an authentication factor can be achieved within an audio channel to supplement other methods, thus providing a multi factor authentication opportunity that retains the usability associated with voice channels. In this research we outline the challenges and threats to audio and voice-based systems in the form of an original threat model focusing on audio and voice-based systems, we outline a novel architectural model that utilises audio steganography to mitigate the threats in various authentication scenarios and finally, we conduct experimentation into hiding authentication materials into an audible sound. The experimentation focused on creating and testing a new steganographic technique which is robust to noise, resilient to steganalysis and has sufficient capacity to hold cryptographic material such as a 2048 bit RSA key in a short audio music clip of just a few seconds achieving a signal to noise ratio of over 70 dB in some scenarios. The method developed was seen to be very robust using digital transmission which has applications beyond this research. With acoustic transmission, despite the progress demonstrated in this research some challenges remain to ensure the approach achieves its full potential in noisy real-world applications and therefore the future research direction required is outlined and discussed.

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Alhassan, Salamudeen, Mohammed Ibrahim Daabo, and Gabriel Kofi Armah. "Twin K-Shuffle Based Audio Steganography." Asian Journal of Engineering and Applied Technology 11, no. 1 (2022): 1–4. http://dx.doi.org/10.51983/ajeat-2022.11.1.3200.

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Secure communication is most effective when it is covert. In the realm of covert communication, steganography conceals secret message within a cover medium. This ensures that adversaries who have access to this carrier medium are unaware of the existence of the secret message. This paper proposes a novel twin K-Shuffling and embedding technique that scrambles and hides secret message inside audio samples. The scrambling phase of the proposed technique consists of bit and character shuffling. The bit-shuffling scrambles the bit-string of each character in the secret message into cipher-text via K-Shuffle. The characters of the resulting cipher-text are then shuffled by another K-Shuffle technique to yield chaotic cipher-text. At the embedding phase, the scrambled cipher-text is randomly planted into the carrier audio samples. The novelty in this proposed technique is the provision of a three-layer protection for secret messages; bit, character, and encoding layers. Results and analyses show that this technique satisfied both embedding and encryption requirements of steganographic systems.

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Aruna, Ms T. N., L. R. Nandika, C. I. Sneha, imothy Jerald Xavier, and Treesa Mary George. "Text, Image and Audio Steganography." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 4435–39. http://dx.doi.org/10.22214/ijraset.2023.51091.

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Abstract: Steganography refers to the concealment of confidential data within a common medium, like a text, image, or audio file, without altering its original appearance, to evade detection. This method is used for several purposes, including protecting data privacy, preventing unauthorized access to data, and ensuring safe information transmission over insecure networks. While steganography can be used for legitimate purposes such as by military, law enforcement, and journalism, it can also be employed for malicious activities like cybercrime and terrorism. The least significant bit (LSB) of each letter in text & audio and the LSB of each pixel in images are altered in steganography to make the alterations invisible. Advanced steganography algorithms like Masking & Filtering and Encrypt & Scatter have improved security against steganalysis assaults while producing higher-quality stego images. The method’s capability for concealing text with an unlimited hidden text size in text, audio, and images will be employed in the outcome.

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Gupta Banik, Barnali, and Samir Kumar Bandyopadhyay. "Blind Key Based Attack Resistant Audio Steganography Using Cocktail Party Effect." Security and Communication Networks 2018 (2018): 1–21. http://dx.doi.org/10.1155/2018/1781384.

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Steganography is a popular technique of digital data security. Among all digital steganography methods, audio steganography is very delicate as human auditory system is highly sensitive to noise; hence small modification in audio can make significant audible impact. In this paper, a key based blind audio steganography method has been proposed which is built on discrete wavelet transform (DWT) as well as discrete cosine transform (DCT) and adheres to Kerckhoff’s principle. Here image has been used as secret message which is preprocessed using Arnold’s Transform. To make the system more robust and undetectable, a well-known problem of audio analysis has been explored here, known as Cocktail Party Problem, for wrapping stego audio. The robustness of the proposed method has been tested against Steganalysis attacks like noise addition, random cropping, resampling, requantization, pitch shifting, and mp3 compression. The quality of resultant stego audio and retrieved secret image has been measured by various metrics, namely, “peak signal-to-noise ratio”; “correlation coefficient”; “perceptual evaluation of audio quality”; “bit error rate”; and “structural similarity index.” The embedding capacity has also been evaluated and, as seen from the comparison result, the proposed method has outperformed other existing DCT-DWT based technique.

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Vejare, Ritvij, Abhishek Vaish, Kapish Singh, and Mrunali Desai. "Removal of Image Steganography using Generative Adversarial Network." Indian Journal of Artificial Intelligence and Neural Networking 2, no. 4 (2022): 6–10. http://dx.doi.org/10.54105/ijainn.d1054.062422.

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Secret messages can be concealed in ordinary media like audio, video and images. This is called as Steganography. Steganography is used by cyber attackers to send malicious content that could harm victims. Digital steganography, or steganography in photographs, is exceedingly difficult to detect. The detection of steganography in images, has been investigated in thoroughly by a variety of parties. The use of steganographic techniques to send more malware to a compromised host in order to undertake different post-exploitation operations that affect the exploited system. Many steganalysis algorithms, on the other hand, are limited to working with a subset of all potential photos in the wild or have a high false positive rate. As a result, barring any suspected image becomes an arbitrary policy. Filtering questionable photos before they are received by the host machine is a more practical policy. In this paper, a Generative Adversarial Network based model is proposed that may be optimized to delete steganographic content while maintaining the original image's perceptual quality. For removing steganography from photos while keeping the maximum visual image quality, a model is built utilizing a combination of Generative Adversarial Network (GAN) and Image Processing. In the future, utilizing a generator to synthesize a picture will become more popular, and detection of steganography in images will become very difficult. In comparison to other models that have been addressed further, the proposed model is able to give a mean square error of 5.4204 between the generated image and the cover image, as well as better outcomes based on several metrics. As a result, a GAN-based steganography eradication method will aid in this endeavor.

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Srivastava, Mayank, and Mohd Qasim Rafiq. "A Novel Approach to Secure Communication Using Audio Steganography." Advanced Materials Research 403-408 (November 2011): 963–69. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.963.

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The digital information revolution has brought important changes in our society and life. Nowadays, large amount of data is transmitted over the network and if the data that is being transmitted is important, one should use secure technique like steganography to transmit it. Steganography is a method of hiding a secret message in a cover media such as text, image, audio etc. in a way that hides the existence of the secret data. This paper introduces new method for audio steganography. The proposed method works on the basis of low bit blind encoding scheme which is used to embed secret data into non-silent samples of wav audio file. Robustness and performance of the proposed scheme is investigated by performing experiments on different audio signals.

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Acharjee, T., A. Choudhury, and P. Kumar. "A Hybrid Audio Steganography Method." International Journal of Computer Sciences and Engineering 6, no. 12 (2018): 558–62. http://dx.doi.org/10.26438/ijcse/v6i12.558562.

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Rana, Manisha, and Rohit Tanwar. "Genetic Algorithm in Audio Steganography." International Journal of Engineering Trends and Technology 13, no. 1 (2014): 29–34. http://dx.doi.org/10.14445/22315381/ijett-v13p206.

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Tharmia, Akshay, Niketan Kudtarkar, Nishant Mishra, Sarthak Bhingarde, and Rohini Patil. "Genetic Algorithm Based Audio Steganography." International Journal of Engineering Trends and Technology 46, no. 3 (2017): 174–77. http://dx.doi.org/10.14445/22315381/ijett-v46p230.

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Jian, Chua Teck, Chuah Chai Wen, Nurul Hidayah Binti Ab. Rahman, and Isredza Rahmi Binti A. Hamid. "Audio Steganography with Embedded Text." IOP Conference Series: Materials Science and Engineering 226 (August 2017): 012084. http://dx.doi.org/10.1088/1757-899x/226/1/012084.

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Puranik, Prof, S. W. "Video Steganography." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 11 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26643.

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Video Steganography is an extension of image steganography where any kind of file in any extension is hidden into the digital video. It is art of hiding secret data in a non-secret digital carrier called cover media. Data exchange occurs with a variety of purpose, ranging from sharing information or just basic communication between people. Data exchanges that occurs every day make data traffic busier. Data theft is made even easier by utilizing the large number of message sender and the busy data traffic. One popular method used to secure data is steganography method. In this research, End of File steganography method is successfully implemented in the various types of multimedia, namely image, audio, and video. this method provides the effect of increasing the size then it is advisable to use video because generally, video size is always larger than image size because it contains image and audio in one file at a time. Keywords- Data Exchange; Steganography; Multimedia; Security

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Reddy, Reddyvari Venkateswara. "Message Encapsulation in-Text, Image, Audio and Video." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 136–43. http://dx.doi.org/10.22214/ijraset.2024.59730.

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Abstract: Steganography entails concealing text-based mystery records within non-textual content documents together with picture, audio, or video documents, with the extraction of the hidden records taking area at its vacation spot. This avoids detection. Steganography is a flexible and effective method hired to hide sensitive statistics inside apparently harmless cover media. This task pursuits to discover the sector of steganography, check out its diverse methods, and increase a realistic stenographic utility for securing digital information.

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Noor Azam, Muhammad Harith, Farida Ridzuan, and M. Norazizi Sham Mohd Sayuti. "A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography." Pertanika Journal of Science and Technology 30, no. 1 (2022): 497–511. http://dx.doi.org/10.47836/pjst.30.1.27.

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Audio steganography is implemented based on three main features: capacity, robustness, and imperceptibility, but simultaneously implementing them is still a challenge. Embedding data at the Least Significant Bit (LSB) of the audio sample is one of the most implemented audio steganography methods because the method will give high capacity and imperceptibility. However, LSB has the lowest robustness among all common methods in audio steganography. To cater to this problem, researchers increased the depth of the embedding level from fourth to sixth and eighth LSB level to improve its robustness feature. However, consequently, the imperceptibility feature, which is commonly measured by Peak Signal to Noise Ratio (PSNR), is reduced due to the trade-off between imperceptibility and robustness. Currently, the lack of study on the estimation of the PSNR for audio steganography has caused the early assessment of the imperceptibility-robustness trade-off difficult. Therefore, a method to estimate PSNR, known as PSNR Estimator (PE), is introduced to enable early evaluation of imperceptibility feature for each stego-file produced by the audio steganography, which is important for the utilisation of embedding. The proposed PE estimates the PSNR based on the pattern collected from the embedment at different levels. From the evaluation, the proposed method has 99.9% of accuracy in estimating PSNR values at different levels. In comparison with the Mazdak Method, the proposed method performs better in all situations. In conclusion, the proposed PE can be used as a reference for embedding and further reducing the calculation complexity in finding the feasible value to minimise the trade-off between robustness and imperceptibility.

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Julianto, Yohanes, and Kristoforus Jawa Bendi. "SISTEM STEGANOGRAFI DENGAN METODE LEAST SIGNIFICANT BIT (LSB) TERACAK." Jurnal Ilmiah Flash 2, no. 2 (2016): 116. http://dx.doi.org/10.32511/jiflash.v2i2.32.

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Information security has become important today. Steganography is one of the ways tomake any information secure. It hides information by inserting it in a media or cover. LSB (LeastSignificant Bit)steganographic technique has become popular because of its simplicity. LSB(Least Significant Bit) is one algorithm from steganography. The weakness of LSB is bits ofembedded are inserted sequentially. It can be easily tracked. Our research using text as embeddedmessage and WAV audio format as cover-object. We combine LSB and LCG (Linear CongruetialGenerator) to determinant the random position of replacement bit. Outcome of this research is asoftware that was develop by waterfall model and coded in Visual Basic. The result shows thatembedded message can be encode dan decode

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Kumar, P. Mohan, and K. L. Hanmuganathan. "Developing a Secure Image Steganographic System Using TPVD Adaptive LSB Matching Revisited Algorithm for Maximizing the Embedding Rate." Journal of Telecommunications and Information Technology, no. 2 (June 27, 2023): 61–66. http://dx.doi.org/10.26636/jtit.2011.2.1146.

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Steganography is the approach for hiding any secret message in a variety of multimedia carriers like images, audio or video files. Whenever we are hiding a data, it is very important to make it invisible, so that it could be protected. A number of steganographic algorithms have been proposed based on this property of a steganographic system. This paper concentrates on integrating Tri way pixel value differencing approach and LSB matching revisited. The secret data embedded in images were images, text and audio signals so far. The proposed scheme has also come with the executable file as secret data. Also, the experimentation results show that, the important properties of a steganographic system such as imperceptibility, capacity of the carrier image and also resistance against the various steganalytic tools have also been achieved with this stego-system.

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Sayed, Mohamed H., and Talaat M. Wahbi. "Information Security for Audio Steganography Using a Phase Coding Method." European Journal of Theoretical and Applied Sciences 2, no. 1 (2024): 634–47. http://dx.doi.org/10.59324/ejtas.2024.2(1).55.

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The art and science of steganography are dedicated to concealing the presence of a secret message from a third party, such that only the sender and recipient are aware of its content. Various types of media can be used to conceal these communications. When information is hidden in an audio signal, this is referred to as audio steganography. In this paper, two distinct steganography techniques are combined with a multi-level steganography approach: the initial message is embedded in an audio cover at the initial stage, employing, a modified LSB technique, additionally, the second message is embedded in the output from the first level, using a phase coding approach at the second level. A stego audio file is the second level's output containing two audio covers with secret messages. The message is split in multiple ways, with varying proportions between the two levels, in order to investigate how the message's size affects the two procedures used here as well as the levels. The PSNR, MSE, and histogram metrics are used to compare the original and stego audio, in order to assess the effectiveness of the suggested approach. The optimum outcome is achieved when the message is divided in the ratio (1:1). The worst outcome is achieved when the message is divided in the ratio (3:1)

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Mangikuppe Venkateshaiah, Namitha, and Manjula Govinakovi Rudrappa. "High-capacity steganography through audio fusion and fission." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 1 (2024): 643. http://dx.doi.org/10.11591/ijeecs.v33.i1.pp643-652.

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<span>Information security is required for two reasons, either to conceal the information completely or to prevent the misuse of the information by adding watermarks or metadata. Audio steganography uses audio signals to hide secret information. In the proposed audio steganography technique, cover audio files and secret audio files are transformed from time domain to wavelet domain using discrete wavelet transform, the secret audio file is transformed in two levels, leading to secure and high-capacity data hiding. 1% of the 2-level compressed secret is fused to 99% of the 1-level compressed cover. “Peak signal to noise ratio and mean squared error, Pearson’s correlation coefficient, spearman’s correlation coefficient, perceptual evaluation of speech quality and short-time objective intelligibility” are considered to assess the similarity of cover audio and stego audio and similarity of secret audio embedded, and secret audio retrieved. Results show that the stego audio signal is perceptually indistinguishable from the cover audio signal. The approach also passed the robustness test.</span>

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Peling, Ida Bagus Adisimakrisna, and Nyoman Putra Sastra. "Enhanced Audio Steganografi dengan Algoritma Advanced Encryption Standard untuk Pengamanan Data pada File Audio." Majalah Ilmiah Teknologi Elektro 17, no. 1 (2018): 66. http://dx.doi.org/10.24843/mite.2018.v17i01.p09.

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Ease of accessing and delivering information makes the Internet more and more needed. But the ease also provides greater opportunities for leaking of information that is confidential. To handle the security of information exchange that is confidential then developed the method of data security on audio using AES (Advanced Encryption Standard) and EAS (Enhanced Audio Steganography) algorithm. From the research results can be concluded by using AES method as cryptography and EAS as steganography, audio file quality can be said good because of the overall test scenario conducted the lowest SNR value obtained is 49.33dB while the highest SNR value is 51.10dB.

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Jangra, Taruna, and Dr Dinesh Singh. "MESSAGE GUIDED RANDOM AUDIO STEGANOGRAPHY USING MODIFIED LSB TECHNIQUE." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 12, no. 5 (2014): 3464–69. http://dx.doi.org/10.24297/ijct.v12i5.2916.

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Steganography is the science of hiding secret data in such a way that its presence can't be noticed. Techniques which hide more secret data in cover files and which doesn't affect transparency of cover signal are better one for steganographic purpose. In the proposed technique which keyless randomization is provided to insert secret information in multiple and variable LSBs. Cover signal is converted into binary format and then with the proposed algorithm binary cover signal is divided into blocks of size 8x8 with 16 bits per sub block, and then checking each sub blocks first two MSBs to find how many LSBs will be used for insertion of secret data bits. PSNR values show that there is no noticeable difference between cover audio signal and stego audio signal. Security increases due to the use of variable number of LSBs for insertion and keyless randomization are provided by counting out technique.

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Susilawati Mohamad, Fatma, and Nurul Sahira Mohd Yasin. "Information Hiding Based on Audio Steganography using Least Significant Bit." International Journal of Engineering & Technology 7, no. 4.15 (2018): 536. http://dx.doi.org/10.14419/ijet.v7i4.15.28363.

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Steganography is the idea of hiding private or sensitive data or information within something that appears to be nothing out of the normal. A few problems arise especially in securing data and information when the information had been lost or stolen from unauthorized user. Traditionally, we give information manually using paper; it is possible that the information could be stolen by unauthorized user. The main objective of this study is to hide secret information in audio, so that other persons will not notice the presence of the information. The proposed method of this study is by using Least Significant Bit (LSB) algorithm to design an audio steganography. In the proposed method, each audio sample is converted into bits and then the text data is embedded. The expected result of this study will produce a steganography audio that will be able to hide data or information efficiently from unauthorized user, also to ensure the safety of the information in an authorized hand.

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Journal, Baghdad Science. "Steganography in Audio Using Wavelet and DES." Baghdad Science Journal 12, no. 2 (2015): 431–36. http://dx.doi.org/10.21123/bsj.12.2.431-436.

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In this paper, method of steganography in Audio is introduced for hiding secret data in audio media file (WAV). Hiding in audio becomes a challenging discipline, since the Human Auditory System is extremely sensitive. The proposed method is to embed the secret text message in frequency domain of audio file. The proposed method contained two stages: the first embedding phase and the second extraction phase. In embedding phase the audio file transformed from time domain to frequency domain using 1-level linear wavelet decomposition technique and only high frequency is used for hiding secreted message. The text message encrypted using Data Encryption Standard (DES) algorithm. Finally; the Least Significant bit (LSB) algorithm used to hide secret message in high frequency. The proposed approach tested in different sizes of audio file and showed the success of hiding according to (PSNR) equation.

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Ali, Rasha H. "Steganography in Audio Using Wavelet and DES." Baghdad Science Journal 12, no. 2 (2015): 431–36. http://dx.doi.org/10.21123/bsj.2015.12.2.431-436.

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OKELLO, Moses Oyaro. "Transmission of Secret Information Based on Time Instances." Eurasia Proceedings of Science Technology Engineering and Mathematics 16 (December 31, 2021): 209–18. http://dx.doi.org/10.55549/epstem.1068612.

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This Paper presents improvement and extension of previous methodology about timing steganography based on network steganography. The previous article uses time interval between two successive time instances of transmissions mixed with cryptography prior to hiding. However, this improvement tends to extend and provide new methods based on single time instance unlike the previous methodology which depend on two-time instances such as hours, minutes, second, millisecond etc. It further examines how to handle effect of different time zone and high precision timing for ultrafast timing such as millisecond, and many more which human actions is too slow for perfect timing. In addition, the extension based on Transmission Control Protocol and Internet Protocol (TCP-IP) status codes where each element of set of status code are index and the index represents certain numeric of combination for hiding. Finally, the cryptography method is improved and extended to series-based cryptography with any defined number of different cryptography methods combined altogether with multiple keys generated dynamically. The methods for both cryptography and steganography were integrated and each module carefully tested for their feasibility and appropriate analysis, comparisons presented too. A brief discussion of possible extension or application of Time Interval and Instance Steganography from network based to Video and Audio time Steganography are presented which depends on time such as rate of change of features in Video, or in Audio as well. However, these video and audio Time steganography are considered as out of scope for this article which is mainly about network Steganography.

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Mudusu, Rambabu, A. Nagesh, and M. Sadanandam. "Enhancing Data Security Using Audio-Video Steganography." International Journal of Engineering & Technology 7, no. 2.20 (2018): 276. http://dx.doi.org/10.14419/ijet.v7i2.20.14777.

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Steganography may be a strategy for concealing any mystery information like content, picture, sound behind distinctive cowl document .In this paper we have a tendency to planned the mix of image steganography associated sound steganography with confront acknowledgment innovation as an instrument for verification. The purpose is to shroud the mystery information behind sound and therefore the beneficiary's face image of video, because it may be a use of various still casings of images and sound. During this technique we've chosen any casing of video to shroud beneficiary's face image and sound to hide the mystery data. Affordable calculation, maybe, increased LSB and RSA rule is been utilised to shroud mystery content and movie. PCA rule is employed for confront acknowledgment. The parameter for security and verification ar gotten at collector and transmitter facet that ar exactly indistinguishable, consequently the knowledge security is dilated.

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Hussain Ali, Ahmed, MohdRosmadiMokhtar MohdRosmadiMokhtar, and LoayEdwar George. "A Review on Audio Steganography Techniques." Research Journal of Applied Sciences, Engineering and Technology 12, no. 2 (2016): 154–62. http://dx.doi.org/10.19026/rjaset.12.2316.

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Duong, Lai Van. "Detecting Audio Steganography using Machine Learning." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 4 (2020): 5815–20. http://dx.doi.org/10.30534/ijatcse/2020/240942020.

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Rasedur, Md, Partha Chakraborty, Md Zahidur, and Md Golam. "Hiding Confidential File using Audio Steganography." International Journal of Computer Applications 178, no. 50 (2019): 30–35. http://dx.doi.org/10.5120/ijca2019919422.

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Mazdak Zamani, Azizah Bt Abdul Manaf, and Shahidan M. Abdullah. "An Overview on Audio Steganography Techniques." International Journal of Digital Content Technology and its Applications 6, no. 13 (2012): 107–22. http://dx.doi.org/10.4156/jdcta.vol6.issue13.13.

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Malik, Garima. "Effective Security Mechanism for Audio Steganography." IARJSET 4, no. 7 (2017): 109–12. http://dx.doi.org/10.17148/iarjset.2017.4717.

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Yousif, Suhaip A., Talaat M.wahbi, and Mohamed H. Sayed. "Audio Steganography Using Tone Insertion Technique." International Journal of Computer Applications Technology and Research 6, no. 6 (2017): 254–58. http://dx.doi.org/10.7753/ijcatr0606.1004.

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Mohammed, Saja, and Faris Mohammed. "Suggested Method for Audio File Steganography." AL-Rafidain Journal of Computer Sciences and Mathematics 10, no. 1 (2013): 285–95. http://dx.doi.org/10.33899/csmj.2013.163459.

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UdhamSingh, Kamred. "A Survey on Audio Steganography Approaches." International Journal of Computer Applications 95, no. 14 (2014): 7–14. http://dx.doi.org/10.5120/16660-6640.

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Sakthisudhan, K., S. Gayathri Priya, P. Prabhu, and P. Thangaraj. "Secure Data Transmission Using Audio Steganography." i-manager's Journal on Electronics Engineering 2, no. 3 (2012): 1–6. http://dx.doi.org/10.26634/jele.2.3.1763.

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