scholarly journals НАВЧАЛЬНИЙ ПРИКЛАД МАСКУВАННЯ ІНФОРМАЦІЇ В АКУСТИЧНОМУ СИГНАЛІ

2021 ◽  
Vol 1 (2) ◽  
pp. 203-210
Author(s):  
M. HOLOVIN ◽  
◽  
N. HOLOVINA ◽  
Keyword(s):  
Classical Music ◽  
Tuning Fork ◽  
Frequency Change ◽  
Least Significant Bit ◽  
Educational Value ◽  
Audio File ◽  
Text Input ◽  
Python Language ◽  
Human Ear ◽  
Sound Files

The paper presents a steganographic method of hiding textual information in an audio file. Hiding is implemented by a program in Python. The introduction of individual letters of the text into the sound is carried out by the method of «the least significant bit». The program can be used for both educational and practical purposes. The commonly used wave library was used to work with sound files. It is not a library specialized for cryptographic and steganographic needs. Its use and the conciseness of the program code makes it possible to visualize the mechanism of hiding information in the classroom and demonstrate in the process of creating a program its debugging and testing. It is also important for educational purposes that working within the library allows you to see the state of an empty and filled audio container at the level of individual bits. To assess the practical value of the program, it was tested with texts of different lengths and with sound containers of different grades. In particular, the sound of a tuning fork, the sound of a guitar string, classical music, rap, jazz, and an audiobook were used. The experiment showed the correct reproduction of texts. It was found that if you listen carefully to the «pure sound» of the tuning fork, when the container is overloaded with information, suspicions of a text bookmark may arise. A text bookmark in the sound, in which the volume, tempo and frequency change quickly, does not reveal the suspicion of a possible bookmark. However, if the party who intercepted the masked message has guesses about how to bookmark the text, then the text is easily removed. Therefore, the use of the program for practical purposes requires additional manipulations in the code, in particular related to the order of text input and the choice of location. Additional text encryption is also desirable. Analysis of sound and its manipulation at the level of individual bits also has educational value in the sense that it gives an idea of the noise level, the magnitude of the useful physical signal and the sensitivity of the human ear. Key words: Python language, steganography, hiding information, masking information in an audio file, educational example.

Testing the Use of Voice Input in a Smartphone Web Survey

2018 ◽  
Vol 38 (2) ◽  
pp. 207-224 ◽  
Author(s):  
Melanie Revilla ◽  
Mick P. Couper ◽  
Oriol J. Bosch ◽  
Marc Asensio
Keyword(s):  
Completion Time ◽  
Control Group ◽  
Web Survey ◽  
Control Groups ◽  
Audio File ◽  
Voice Input ◽  
Text Input ◽  
Standard Text ◽  
The Voice ◽  
Voice Recording

We implemented an experiment within a smartphone web survey to explore the feasibility of using voice input (VI) options. Based on device used, participants were randomly assigned to a treatment or control group. Respondents in the iPhone operating system (iOS) treatment group were asked to use the dictation button, in which the voice was translated automatically into text by the device. Respondents with Android devices were asked to use a VI button which recorded the voice and transmitted the audio file. Both control groups were asked to answer open-ended questions using standard text entry. We found that the use of VI still presents a number of challenges for respondents. Voice recording (Android) led to substantially higher nonresponse, whereas dictation (iOS) led to slightly higher nonresponse, relative to text input. However, completion time was significantly reduced using VI. Among those who provided an answer, when dictation was used, we found fewer valid answers and less information provided, whereas for voice recording, longer and more elaborated answers were obtained. Voice recording (Android) led to significantly lower survey evaluations, but not dictation (iOS).

scholarly journals STEGANOGRAFI AUDIO (WAV) MENGGUNAKAN METODE LSB (LEAST SIGNIFICANT BIT)

CCIT Journal ◽  
2016 ◽  
Vol 9 (2) ◽  
pp. 214-224
Author(s):  
Sugeng Santoso ◽  
Arisman Arisman ◽  
Windy Sentanu
Keyword(s):  
Digital Media ◽  
Digital Audio ◽  
Least Significant Bit ◽  
Audio File ◽  
Distributed Information ◽  
Hide Information

Security of distributed information is essential for maintaining the confidentiality of the information. The process of securing is done by hiding the information on other digital media that are not visible existence. This technique is called steganography, the art of hiding data into digital media with a particular method so that other people do not realize there is something in the digital media. In this paper conducted a study to hide information into digital audio file is not compressed (. Wav) as a carrier file using the Least Significant Bit Modification. Least Significant Bit Modification is a method of hiding information by modifying the last bits of carrier files with the bits of information and only cause changes in the value of a bit higher or a lower one. The system was designed with two main processes, namely phase Embedding and Extracting stage

scholarly journals Aplikasi Steganografi Menggunakan Least Significant Bit (LSB) dengan Enkripsi Caesar Chipper dan Rivest Code 4 (RC4) Menggunakan Bahasa Pemrograman JAVA

2021 ◽  
Vol 5 (3) ◽  
pp. 277
Author(s):  
Ade Davy Wiranata ◽  
Rima Tamara Aldisa
Keyword(s):  
Secret Message ◽  
Least Significant Bit ◽  
File Size ◽  
Audio File ◽  
Encrypted Image ◽  
Image File

The research objective is to hide messages through images using the LSB (Least Significant Bit) method and Caesar Chipper and Rivest Code 4 encryption. The LSB (Least Significant Bit) method is used as a message hiding technique in steganography where hiding hidden messages is done by changing a few bits in the segment. image with a secret message. The results of this study resulted in an implementation using the Least Significant Bit (LSB) to be applied to institutions with an interest in maintaining the confidentiality of encrypted image output, changing the image file size and sound (audio) file size.Keywords:Steganography, Least Significant Bit (LSB), Caesar Chiper and RC4.

LSBR Speech Steganalysis Based on Percent of Equal Adjacent Samples

2021 ◽  
Author(s):  
Saeid Yazdanpanah ◽  
Mohammad Kheyrandish ◽  
Mohammad Mosleh
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Statistical Characteristics ◽  
Least Significant Bit ◽  
Implementation Cost ◽  
Audio File ◽  
Audio Files ◽  
Mlp Classifier ◽  
Processing Techniques ◽  
Signal Processing Techniques

Wide utilization of audio files has attracted the attention of cyber-criminals to employ this media as a cover for their concealed communications. As a countermeasure and to protect cyberspace, several techniques have been introduced for steganalysis of various audio formats, such as MP3, VoIP, etc. The combination of machine learning and signal processing techniques has helped steganalyzers to obtain higher accuracies. However, as the statistical characteristics of a normal audio file differ from the speech ones, the current methods cannot discriminate clean and stego speech instances efficiently. Another problem is the high numbers of extracted features and analysis dimensions that drastically increase the implementation cost. To tackle these, this paper proposes the Percent of Equal Adjacent Samples (PEAS) feature for single-dimension least-significant-bit replacement (LSBR) speech steganalysis. The model first classifies the samples into speech and silence groups according to a threshold which has been determined through extensive experiments. It then uses an MLP classifier to detect stego instances and determine the embedding ratio. PEAS steganalysis detects 99.8% of stego instances in the lowest analyzed embedding ratio — 12.5% — and its sensitivity increases to 100% for the ratios of 37.5% and above.

scholarly journals IMPLEMENTASI STEGANOGRAFI PESAN TEKS KE DALAM FILE AUDIO (.MP3) DENGAN ALGORITMA ADVANCED ENCRYPTION STANDARD DAN LEAST SIGNIFICANT BIT

JURNAL IT ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 122-139
Author(s):  
Nursobah Nursobah ◽  
Siti Lailiyah ◽  
Asri Kurnia
Keyword(s):  
Black Box ◽  
Advanced Encryption Standard ◽  
Least Significant Bit ◽  
Audio File

Tujuan dari penelitian ini adalah untuk menghasilkan Aplikasi desktop Steganografi audio dengan Implementasi Steganografi Pesan Teks Ke Dalam File Sound (.MP3) Dengan Algoritma Advanced Encryption Standard dan Least Significant Bit. Bahasa pemrograman yang digunakan adalah C#. Penelitian ini dilakukan di Samarinda. teknik pengumpulan data yang digunakan adalah studi pustaka, dan pengamatan, alat bantu pengembangan sistem menggunakan metode Waterfall serta pengujian menggunakan black-box. Hasil dari penelitian ini adalah berupa aplikasi desktop steganografi audio yang diamankan dengan enkripsi Advanced Enryption Standard (AES) 128 bit, di embedding dengan Least Significant Bit dimana file pesan di enkripsi dan di injeksikan ke dalam file media mp3 yang output nya akan tersimpan di lokasi yang telah ditentukan dan hanya bisa di ekstrak oleh pemegang kunci dan memiliki aplikasi steganogarafi audio, file didekripsi menggunakan algoritma Advanced Enryption Standard (AES) 128 bit dan di ekstrak dengan Least Significant Bit

scholarly journals Performance Enhancement of a Quartz Tuning Fork Sensor Using a Cellulose Nanocrystal-Reinforced Nanoporous Polymer Fiber

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 437 ◽  
Author(s):  
Wuseok Kim ◽  
Eunjin Park ◽  
Sangmin Jeon
Keyword(s):  
Tuning Fork ◽  
Performance Enhancement ◽  
Quartz Tuning Fork ◽  
Ethanol Vapor ◽  
Composite Fiber ◽  
Cellulose Nanocrystal ◽  
Vapor Concentration ◽  
Frequency Change ◽  
Moisture Adsorption ◽  
Highly Porous

A cellulose nanocrystal (CNC)-reinforced polymethylmethacrylate (PMMA) fiber was obtained via electrospinning, and then attached between the two tines of a quartz tuning fork (QTF). The change in the resonance frequency of the CNC/PMMA composite fiber-coated QTF (CP-QTF) was measured upon being exposed to various concentrations of ethanol vapor. The frequency decreased as the ethanol vapor concentration increased, because the modulus of the composite fiber decreased due to the adsorption of the ethanol vapor. The composite fiber obtained at a high relative humidity (RH; 60% RH, CP60 fiber) produced a highly porous structure as a result of the moisture adsorption-induced phase separation of PMMA. The porosity of the CP60 fiber was higher than that of a CNC/PMMA composite fiber obtained at 30% RH (CP30 fiber) or that of a plain PMMA fiber obtained at 60% RH (P60 fiber), because hygroscopic CNCs promote moisture adsorption. The CP60 fiber-coated QTF (CP60-QTF) exhibited a greater frequency change and faster response time than P60-QTF and CP30-QTF upon exposure to ethanol vapor at the same concentration. The enhanced performance of CP60-QTF was attributed to its higher surface area and larger fiber modulus.

scholarly journals Steganography in Audio Using Wavelet and DES

2015 ◽  
Vol 12 (2) ◽  
pp. 431-436
Author(s):  
Baghdad Science Journal
Keyword(s):  
Frequency Domain ◽  
High Frequency ◽  
Text Message ◽  
Data Encryption ◽  
Secret Message ◽  
Least Significant Bit ◽  
Secret Data ◽  
Audio File ◽  
Using Data ◽  
Two Stages

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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