Current techniques of steganography are not impervious to detection using thorough procedures. Th... more Current techniques of steganography are not impervious to detection using thorough procedures. This paper proposes to ascertain security and precision in the process of Text Steganography by presenting a few unexplored techniques. It establishes reliable media to transfer any required message accompanied by hidden data. The process relies on RSA Algorithm to encrypt user data by generating subtle imperfections in the appearance or layout of the characters included in the memo. The message undergoes multilevel encryption and corresponding decryption using both the public and private keys, thus bearing invulnerability to cyber-attacks and security breaches. The receiver acquires the modified message in the sender's format, to fend off digital decryption from unauthorized users. As opposed to contemporary techniques of Text Steganography, the encrypted message has a relative constraint on the size as it depends on the size of the data to be hidden, bearing no definite restrictions on the amount of information to be conveyed.
2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC), 2020
Audio source separation is a cornerstone problem for researchers engaged in Digital Signal Proces... more Audio source separation is a cornerstone problem for researchers engaged in Digital Signal Processing and Artificial Intelligence. Music unmixing is the task of decomposing music into its constitutive components, like yielding separated stems for the vocals, bass, drums, accompaniment, jazz, and others from a mastered song track. Due to recent progress in the field of Deep Learning, researchers have been able to devise Neural Networks that can perform this task with considerable precision. However, these models lack performance when dealing with generic musical audio despite having decent utility over specific music genres. The proposed system aims to develop a universal platform-independent software for accurate domain-specific implementation of music source separation for acute subsets of stereo audio using the Bidirectional Long Short Term Memory (BLSTM) architecture of Recurrent Neural Networks. The Deep Neural Network helps demix audio mixtures into the jazz solo and its accompaniment. In cohesion, these two models extract five independent audio stems from the original audio with reasonable accuracy. Further, the extracted accompaniment stem is processed using ConvNet Model to estimate the instrumental components. In synchronization, these three models can break down audio to its fundamental elements.
Current techniques of steganography are not impervious to detection using thorough procedures. Th... more Current techniques of steganography are not impervious to detection using thorough procedures. This paper proposes to ascertain security and precision in the process of Text Steganography by presenting a few unexplored techniques. It establishes reliable media to transfer any required message accompanied by hidden data. The process relies on RSA Algorithm to encrypt user data by generating subtle imperfections in the appearance or layout of the characters included in the memo. The message undergoes multilevel encryption and corresponding decryption using both the public and private keys, thus bearing invulnerability to cyber-attacks and security breaches. The receiver acquires the modified message in the sender's format, to fend off digital decryption from unauthorized users. As opposed to contemporary techniques of Text Steganography, the encrypted message has a relative constraint on the size as it depends on the size of the data to be hidden, bearing no definite restrictions on the amount of information to be conveyed.
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Papers by Tanmay Bhagwat