Identification of Sparse Audio Tampering Using Distributed Source Coding and Compressive Sensing Techniques

In the past few years, a large amount of techniques have been proposed to identify whether a multimedia content has been illegally tampered or not. Nevertheless, very few efforts have been devoted to identifying which kind of attack has been carried out, especially due to the large data required for this task. We propose a novel hashing scheme which exploits the paradigms of compressive sensing and distributed source coding to generate a compact hash signature, and we apply it to the case of audio content protection. The audio content provider produces a small hash signature by computing a limited number of random projections of a perceptual, time-frequency representation of the original audio stream; the audio hash is given by the syndrome bits of an LDPC code applied to the projections. At the content user side, the hash is decoded using distributed source coding tools. If the tampering is sparsifiable or compressible in some orthonormal basis or redundant dictionary, it is possible to identify the time-frequency position of the attack, with a hash size as small as 200 bits/second; the bit saving obtained by introducing distributed source coding ranges between 20% to 70%

Detection and identification of sparse audio tampering using distributed source coding and compressive sensing techniques

In most practical applications, for the sake of information integrity not only it is useful to detect whether a multimedia content has been modified or not, but also to identify which kind of attack has been carried out. In the case of audio streams, for example, it may be useful to localize the tamper in the time and/or frequency domain. In this paper we devise a hash-based tampering detection and localization system exploiting compressive sensing principles. The multimedia content provider produces a small hash signature using a limited number of random projections of a time-frequency representation of the original audio stream. At the content user side, the hash signature is used to estimate the distortion between the original and the received stream and, provided that the tamper is sufficiently sparse or sparsifiable in some orthonormal basis expansion or redundant dictionary (e.g. DCT or wavelet), to identify the time-frequency portion of the stream that has been manipulated. In order to keep the hash length small, the algorithm exploits distributed source coding techniques

The multimedia blockchain: a distributed and tamper-proof media transaction framework

A distributed and tamper proof media transaction framework is proposed based on the blockchain model. Current multimedia distribution does not preserve self-retrievable information of transaction trails or content modification histories. For example, digital copies of valuable artworks, creative media and entertainment contents are distributed for various purposes including exhibitions, gallery collections or in media production workflow. Original media is often edited for creative content preparation or tampered with to fabricate false propaganda over social media. However there is no existing trusted mechanism that can easily retrieve either the transaction trails or the modification histories. We propose a novel watermarking based Multimedia Blockchain framework that can address such issues. The unique watermark information contains two pieces of information: a) a cryptographic hash that contains transaction histories (blockchain transactions log) and b) an image hash that preserves retrievable original media content. Once the watermark is extracted, first part of the watermark is passed to a distributed ledger to retrieve the historical transaction trail and the latter part is used to identify the edited / tampered regions. The paper outlines the requirements, the challenges and demonstrates the proof of this concept

A review of compressive sensing in information security field

The applications of compressive sensing (CS) in the fi eld of information security have captured a great deal of researchers\u27 attention in the past decade. To supply guidance for researchers from a comprehensive perspective, this paper, for the fi rst time, reviews CS in information security field from two aspects: theoretical security and application security. Moreover, the CS applied in image cipher is one of the most widespread applications, as its characteristics of dimensional reduction and random projection can be utilized and integrated into image cryptosystems, which can achieve simultaneous compression and encryption of an image or multiple images. With respect to this application, the basic framework designs and the corresponding analyses are investigated. Speci fically, the investigation proceeds from three aspects, namely, image ciphers based on chaos and CS, image ciphers based on optics and CS, and image ciphers based on chaos, optics, and CS. A total of six frameworks are put forward. Meanwhile, their analyses in terms of security, advantages, disadvantages, and so on are presented. At last, we attempt to indicate some other possible application research topics in future

PERANCANGAN DAN ANALISIS COMPRESSIVE SAMPLING PADA AUDIO WATERMARKING STEREO BERBASIS DISCRETE SINE TRANSFORM DENGAN METODE HYBRID LIFTING WAVELET TRANSFORM DAN CEPSTRUM

**ABSTRAK** Seiring dengan perkembangan jaringan internet dan teknologi multimedia mengakibatkan penyebaran informasi berupa data, teks, video, gambar, dan suara semakin mudah. Semakin berkembangnya jaringan internet dan multimedia, maka semakin mudah juga untuk memodifikasinya. Hal ini menyebabkan seringnya terjadi pelanggaran hak cipta dan hak kepemilikan seperti pembajakan pada konten musik atau audio digital. Maka dengan permasalahan tersebut untuk menjaga hak kepemilikan data digital diperlukan teknik *watermark*. Teknik *watermark* digunakan untuk melindungi kepemilikan multimedia, identifikasi hak cipta, penentuan keaslian data, identifikasi pengguna, dan pemantauan data. *Watermarking* adalah proses penyisipan informasi ke salah satu host-data seperti gambar, suara, dan video sehingga informasi $*watermark*$ kemudian dapat diektraksi dan dideteksi informasi tersebut untuk mencegah dan mengendalikan pernyebaran data digital yang dilindungi oleh hak cipta. Dalam digital *watermarking*, bila informasi disisipkan ke dalam audio digital maka disebut *audio watermarking*. Tugas akhir ini akan membahas perancangan sistem *audio watermarking* dengan metode LWT $*Lifting Wavelet Transform*$, *Cepstrum*, dan DST $*Discrete Sine Transform*$ dan *Compressive Sampling* dengan metode penyisipan SMM $*Statistical Mean Manipulation*$ dan QIM $*Quantization Index Modulation*$. Pemilihan metode LWT pada tugas akhir ini karena LWT tahan terhadap serangan seperti *linear speed change* dan TSM, namun kurang tahan terhadap serangan seperti *resampling, pitch shifting, echo*, dan *noise*. *Cepstrum* digunakan untuk mendapatkan kapasitas yang besar dalam penyimpanan data *watermarking*, dan DST diharapkan dapat menghemat waktu komputasi. Sistem *audio watermarking* yang dilakukan dalam penelitian ini menghasilkan kualitas audio dengan memiliki rata-rata BER 0.36651, rata-rata SNR 28.87 dB, rata-rata ODG -2.86832, dan rata-rata MOS 4.08. Kata kunci: *Audio Watermarking*, *Lifting Wavelet Transform*, *Discrete Wavelet Transform*, *Cepstrum*, *Compressive Sampling*

PERANCANGAN DAN ANALISIS COMPRESSIVE SAMPLING DAN SINKRONISASI PADA AUDIO WATERMARKING STEREO BERBASIS STATIONARY WAVELET TRANSFORM DENGAN METODE AUDIO CENTROID

Di era sekarang ini, pertumbuhan informasi di bidang teknologi sangat pesat. Salah satu kemudahan penyebaran media digital(gambar, suara, video) melalui internet membuat masyarakat dengan mudah mengakses semua media digital tersebut. Sisi positif dari kemudahan penyebaran adalah dengan cepatnya pemilik media digital tersebut menyebarkan file citra digital ke berbagai alamat situs di internet dan pemilik hak cipta media digital mendapat penghasilan dari situs itu. Tapi kemudahan itu memiliki sisi negatif yaitu jika tidak ada hak cipta yang berfungsi sebagai pelindung citra yang disebarkan tersebut, maka bisa terjadi pengambilan data secara ilegal. Untuk mengatasi hal itu, kita bisa menggunakan teknik watermark. Watermarking adalah suatu cara penyembunyian informasi atau data pada suatu media tertentu dan harus tahan terhadap serangan. Pada tugas akhir ini menggunakan watermarking dengan penggunaan Compressive sampling untuk memperkecil ukuran watermark. Sinkronisasi untuk mengetahui letak watermark, serta metode Stationary Wavelet Transform (SWT) yang dirancang mencegah pergeseran wátermark untuk mengatasi kelemahan dari Discrete Wavelet Transform (DWT) dan menghasilkan beberapa sinyal yaitu frekuensi tinggi, tengah dan tinggi. Audio centroid adalah menentukan titik berat di sinyal audio dalam suatu frame agar lebih tahan terhadap serangan. Pada tugas akhir ini didapatkan hasil parameter terbaik sebelum diserang dengan BER=0, SNR=22.7915, ODG= -3.8906 dan kapasitas sebesar 30.7617. Untuk optimasi terbaik yang dipilih setelah diserang terletak di drums.wav dengan hasil BER=0, SNR =23.3138, ODG=-3.3625 dan kapasitas 205.0781. Setelah itu didapatkan BER rata-rata yang telah di serang ke semua host yaitu 0.28 Kata Kunci : Watermarking, Stationary Wavelet Transform (SWT), Compressive Sampling (CS), Audio Centroid

Novel Methods for Forensic Multimedia Data Analysis: Part I

The increased usage of digital media in daily life has resulted in the demand for novel multimedia data analysis techniques that can help to use these data for forensic purposes. Processing of such data for police investigation and as evidence in a court of law, such that data interpretation is reliable, trustworthy, and efficient in terms of human time and other resources required, will help greatly to speed up investigation and make investigation more effective. If such data are to be used as evidence in a court of law, techniques that can confirm origin and integrity are necessary. In this chapter, we are proposing a new concept for new multimedia processing techniques for varied multimedia sources. We describe the background and motivation for our work. The overall system architecture is explained. We present the data to be used. After a review of the state of the art of related work of the multimedia data we consider in this work, we describe the method and techniques we are developing that go beyond the state of the art. The work will be continued in a Chapter Part II of this topic

Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read