Abstract:Today's internet community the secure data transfer is bounded due to its attack on data communication. Security of data can be achieved by implementing steganography techniques. All of the existing steganographic techniques use the digital multimedia files as a cover mediums to conceal secret data. Audio file use as a cover medium in steganography because of its larger size compare to other carrier's file such as text, image. So there are more possibilities to hide large amount of data inside digital audio fi… Show more
“…This framework served as a basis for cover audio selection optimisation, involving a multi-objective problem based on capacity and imperceptibility characteristics while considering its trade-off. For the value of a good trade-off between imperceptibility and capacity, this framework considered all cover audios that achieved 30 dB of Signal-to-Noise Ratio (SNR) following Singh (2014). Meanwhile, the capacity was fixed based on user input.…”
Existing embedding techniques depend on cover audio selected by users. Unknowingly, users may make a poor cover audio selectionthat is not optimised in its capacity or imperceptibility features, which could reduce the effectiveness of any embedding technique. As a trade-off exists between capacity and imperceptibility, producing a method focused on optimising both features is crucial. One ofthe search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. The proposed method provided suggestions for cover audio to users based on imperceptibility and capacity features. The sample difference calculation was initially formulated to determine the maximum capacity for each cover audio defined in the cover audio database. Next, NSGA-II was implemented to determine the optimised solutions based on the parameters provided by each chromosome. The experimental results demonstrated the effectiveness of the proposed method as it managed to dominate thesolutions from the previous method selected based on one criterion only. In addition, the proposed method considered that the trade-off managed to select the solution as the highest priority compared to the previous method, which put the same solution as low as 71 in the priority ranking. In conclusion, the method optimised the cover audio selected, thus, improving the effectiveness of the audio steganography used. It can be a response to help people whose computers and mobile devices continue to be unfamiliar with audio steganography in an age where information security is crucial.
“…This framework served as a basis for cover audio selection optimisation, involving a multi-objective problem based on capacity and imperceptibility characteristics while considering its trade-off. For the value of a good trade-off between imperceptibility and capacity, this framework considered all cover audios that achieved 30 dB of Signal-to-Noise Ratio (SNR) following Singh (2014). Meanwhile, the capacity was fixed based on user input.…”
Existing embedding techniques depend on cover audio selected by users. Unknowingly, users may make a poor cover audio selectionthat is not optimised in its capacity or imperceptibility features, which could reduce the effectiveness of any embedding technique. As a trade-off exists between capacity and imperceptibility, producing a method focused on optimising both features is crucial. One ofthe search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. The proposed method provided suggestions for cover audio to users based on imperceptibility and capacity features. The sample difference calculation was initially formulated to determine the maximum capacity for each cover audio defined in the cover audio database. Next, NSGA-II was implemented to determine the optimised solutions based on the parameters provided by each chromosome. The experimental results demonstrated the effectiveness of the proposed method as it managed to dominate thesolutions from the previous method selected based on one criterion only. In addition, the proposed method considered that the trade-off managed to select the solution as the highest priority compared to the previous method, which put the same solution as low as 71 in the priority ranking. In conclusion, the method optimised the cover audio selected, thus, improving the effectiveness of the audio steganography used. It can be a response to help people whose computers and mobile devices continue to be unfamiliar with audio steganography in an age where information security is crucial.
“…2. However this domain suffers from low robustness and (Singh, 2014). The earliest algorithm employed in such domain is LSB which is used in embedding process.…”
The aim of this study is to present different types of steganography in brief and to give a special attention to audio steganography technique because a huge number of audio files are exchanged through the networks. Nowadays the widening of attacker's abilities to access the private and public information transmitted over public communication system makes way for highlighting a tool that guarantees the secure transmission of hidden information. Information hiding was a common security term that mainly includes three techniques: cryptography, steganography and watermark. Cryptography was an ancient form that is used for confidential data. Steganography is a popular tool that uses digital medium to hide confidential data in innocent carrier such as image, audio, text and video. Steganography is in fact a complement for the earlier data hiding technique cryptography. However watermark is used for copyright protection. Audio steganography is technique that hides any type of secret data in cover audio file. This study also discusses the main requirements of steganography methods and how those methods achieve them. Furthermore it shows steganography domain and, carriers and information hiding techniques used in audio.
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