Audio steganography is the embedding of data into an audio file. Current research in audio steganography has only shown that audio and image files can be used as the embedded media. For this project, a Java program was written that allows for any type of file to be the embedded media within an audio file. The research that was needed for this program to be written was conducted using the Java Media Composition Library written at Georgia Institute of Technology and the jGrasp programming environment. The project was conducted with the goal to create an algorithm for audio steganography that would allow for multiple types of files to be embedded in an audio file and to construct a method of embedding data into the slopes of the sound wave in areas of high frequency. The process by which the research was conducted consisted of constructing a test class, constructing an abstract class, modifying the abstract class, and finally testing for the detection of changes within the sound file. It was discovered that by embedding the data linearly along the slopes of the sound wave, one could not detect the changes that were made to the sound file. It was then concluded that by using this Java program instead of the commonly used Least Significant Bit methodology the data could be embedded more efficiently by analyzing the cover file and using the areas determined to have high wave frequency as the cover area. ABSTRACT ENGINEERING GOAL Materials: 1.Java 8 Runtime Environment 2.jGrasp Integrated Development Environment by Auburn University 3.Minimum 4GB RAM computer 4.Java Media Composition Library by Georgia Institute of Technology MATERIALS AND PROCEDURES Procedure: 1.Setup jGrasp to use a minimum of 2GB of RAM on startup 2.Write sample program to understand the functions and limitations of the Java Media Composition Library 3.Write abstract class, which will be used for all extensions within the scope of this research 4.Write an extension class that works with text(.txt) files 5.Edit the abstract and extension classes to use an algorithm to locate areas of the cover file to embed to the data 6.Write extract method that uses the same algorithm as the abstract class to find the areas in which data is embedded and extract them. 7.Write an extension class that works for images 8.Write an extension class that works for sounds RESULTS The human subjects were split into two groups; musicians and non-musicians. This separation is important because the musicians are trained in active listening, so it should be easier for them to detect a change within the sound file than a non-musician. The two groups were then split into two groups; test and control. The non-musician control group was successful in not hearing changes in the sound file, but there were some musicians in the control group that thought that they heard changes in the sound file. There was a noticeable difference in how the non-musicians listened to the sound files and how they responded to the questions. The non-musicians purposely sat closely to the speakers, while the musicians scattered themselves around the testing area. The non-musicians also responded positively to the question, “Would you like to hear the original sound file again?”, which was asked immediately after playing every sound sample. The non-musicians, both control and test, decided to listen to the original sound sample multiple times, while the musicians decided to listen to the original sound file only once. There may be a correlation between how the test subjects conducted the tests and the results that were collected. Musicians, as well as non-musicians, were able to detect the changes within the sound file. Definite conclusions were not able to be drawn due to a small sample size and possible placebo effect. CONCLUSIONS AND FUTURE RESEARCH The program was able to successfully embed and extract sound files, text files and image files within a sound file with an algorithm that is not a derivative of the Least Significant Bit methodology. The program was successful in breaking away from the Least Significant Bit methodology by pre-analysis of the cover file and determining areas in which data can be hidden. This research can be expanded upon by “doubly encoding” by implementing the algorithm for file encryption as well as the steganography. No formal conclusion can be drawn from the human testing due to the small sample size and the possible placebo effect. REFERENCES Altaei, Mohammed S., Hmood, Dalal N., and Khudhiar, Khamael A. “A New Steganographic Method for Embedded Image In Audio File”, International Journal of Computer Science and Security (IJCSS), Volume (6) : Issue (2) : 2012 pp Amin, Muhalim M., Ibrahim, Subariah., Katmin, Mohd R., and Salleh, Mazleena. “Information Hiding Using Steganography”. Department of Computer System & Communication Faculty of Computer Science and Information system Universiti Teknologi Malaysia Anderson, Ross J. and Petitcolas, Fabien A., “On the Limits of Steganography” IEEE Journal On Selected Areas In Communications, Vol. 16, No. 4, May 1998 pp Anupama, H.S., Jayaram P., and Ranganatha H R. “Information Hiding Using Audio Steganography – A Survey”. The International Journal of Multimedia & Its Applications (IJMA) Vol.3, No.3, August 2011 Dhar, Puja and Nehru, Gunjan. “A Detailed look of Audio Steganography Techniques using LSB and Genetic Algorithm Approach” IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 1, No 2, January 2012 ISSN (Online): pp Galshetwar, Gajanan, Jeyakumar, Amutha, and Mane, Ashiwini. “Data Hiding Technique: Audio Steganography Using LSB Technique”. International Journal of Engineering Research and Applications (IJERA) ISSN: Vol. 2, Issue 3, May-Jun 2012, pp Khalil, M. I. “Image Steganography: Hiding Short Audio Messages Within Digital Images” Reactor Physics Department, Nuclear Research Center, Atomic Energy Authority, Cairo Egypt. JCS&T Vol. 11 No. 2 October 2011 Rana, Manisha and Tanwar, Rohit. “Genetic Algorithm in Audio Steganography” International Journal of Engineering Trends and Technology (IJETT) – Volume 13 Number 1 – Jul 2014 The goal of this project was to write a Java program that can embed and extract data retrieved from any type of media file into a sound file without using Least Significant Bit methodology, which is the process of embedding data in an uniform fashion, by replacing data in the cover file every n-th bit of data. Creating a Multi-Functional Algorithm for Audio Steganography Sound file before steganography Sound to be embedded CODE SAMPLE Sound extracted from cover file DATA SAMPLES