Adversarial Audio: A New Information Hiding Method and Backdoor for DNN-based Speech Recognition Models

Audio is an important medium in people's daily life, hidden information can be embedded into audio for covert communication. Current audio information hiding techniques can be roughly classed into time domain-based and transform domain-based techniques. Time domain-based techniques have large hiding capacity but low imperceptibility. Transform domain-based techniques have better imperceptibility, but the hiding capacity is poor. This paper proposes a new audio information hiding technique which shows high hiding capacity and good imperceptibility. The proposed audio information hiding method takes the original audio signal as input and obtains the audio signal embedded with hidden information (called stego audio) through the training of our private automatic speech recognition (ASR) model. Without knowing the internal parameters and structure of the private model, the hidden information can be extracted by the private model but cannot be extracted by public models. We use four other ASR models to extract the hidden information on the stego audios to evaluate the security of the private model. The experimental results show that the proposed audio information hiding technique has a high hiding capacity of 48 cps with good imperceptibility and high security. In addition, our proposed adversarial audio can be used to activate an intrinsic backdoor of DNN-based ASR models, which brings a serious threat to intelligent speakers.Comment: Submitted to RAID201

Audio Steganography: LSB Technique Using a Pyramid Structure and Range of Bytes

The demand for keeping the information secure and confidential simultaneously has been progressively increasing. Among various techniques- Audio Steganography, a technique of embedding information transparently in a digital media thereby restricting the access to such information has been prominently developed. Imperceptibility, robustness, and payload or hiding capacity are the main character for it. In earlier, LSB techniques increased payload capacity would hamper robustness as well as imperceptibility of the cover media and vice versa. The proposed technique overcomes the problem. It provides relatively good improvement in the payload capacity by dividing the bytes of cover media into ranges to hide the bits of secret message appropriately. As well as due to the use of ranges of bytes the robustness of cover media has maintained and imperceptibility preserved by using a pyramid structure.Comment: 12 page, 16 Figure

Genetic Algorithm in Audio Steganography

With the advancement of communication technology,data is exchanged digitally over the network. At the other side the technology is also proven as a tool for unauthorized access to attackers. Thus the security of data to be transmitted digitally should get prime focus. Data hiding is the common approach to secure data. In steganography technique, the existence of data is concealed. GA is an emerging component of AI to provide suboptimal solutions. In this paper the use of GA in Steganography is explored to find future scope of research.Comment: 6 pages,2 figures Published with International Journal of Engineering Trends and Technology (IJETT). arXiv admin note: text overlap with arXiv:1003.4084, arXiv:1205.2800 by other authors without attributio

Hiding Sound in Image by K-LSB Mutation

In this paper a novel approach to hide sound files in a digital image is proposed and implemented such that it becomes difficult to conclude about the existence of the hidden data inside the image. In this approach, we utilize the rightmost k-LSB of pixels in an image to embed MP3 sound bits into a pixel. The pixels are so chosen that the distortion in image would be minimized due to embedding. This requires comparing all the possible permutations of pixel values, which may would lead to exponential time computation. To speed up this, Cuckoo Search (CS) could be used to find the most optimal solution. The advantage of using proposed CS is that it is easy to implement and is very effective at converging in relatively less iterations/generations.Comment: appears in ISCBI 201

A reversible high embedding capacity data hiding technique for hiding secret data in images

As the multimedia and internet technologies are growing fast, the transmission of digital media plays an important role in communication. The various digital media like audio, video and images are being transferred through internet. There are a lot of threats for the digital data that are transferred through internet. Also, a number of security techniques have been employed to protect the data that is transferred through internet. This paper proposes a new technique for sending secret messages securely, using steganographic technique. Since the proposed system uses multiple level of security for data hiding, where the data is hidden in an image file and the stego file is again concealed in another image. Previously, the secret message is being encrypted with the encryption algorithm which ensures the achievement of high security enabled data transfer through internet.Comment: IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 7 No. 3, March 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis

Data Hiding using Graphical Code based Steganography Technique

Data hiding has received much attention due to rapid development of internet and multimedia technologies where security of information is a very important concern. This is achieved by Steganography, which is the art or science of hiding data into another data, so that human eyes cannot catch the hidden information easily. There are many ways to hide information-like inside an image, text, audio/ video etc. Among them image steganography is a very attractive research area. The goal is to transmit a data within a modified image (called stego-image)by minimizing the number of bit flips. In this paper, a new steganography technique has been proposed using Graphical codes and also comparison with steganography technique using BCH codes has been studied.Comment: 5 pages, 3 figures, 2 tables, International Journal of Engineering Trends and Technology (IJETT),Volume 27 Number 3, September 201

Improved information security using robust Steganography system

Steganography is an emerging area which is used for secured data transmission over any public media.Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. It is of Greek origin and means "covered or hidden writing". The carrier can be sent to a receiver without any one except the authenticated receiver knowing the existence of this information. In this paper, a specific image based steganography technique for communicating information more securely between two locations is proposed. The author incorporated the idea of secret key and password security features for authentication at both ends in order to achieve high level of security. As a further improvement of security level, the information has been permuted, encoded and then finally embedded on an image to form the stego image. In addition segmented objects extraction and reassembly of the stego image through normalized cut method has been carried out at the sender side and receiver side respectively in order to prevent distortion of the Stego image during transmission

Embedding of binary image in the Gray planes

For watermarking of the digital grayscale image its Gray planes have been used. With the help of the introduced representation over Gray planes the LSB embedding method and detection have been discussed. It found that data, a binary image, hidden in the Gray planes is more robust to JPEG lossy compression than in the bit planes.Comment: 7 pages, 3 figures, Proceeding of 24rd International Conference on Computer Graphics and Vision GraphiCon'2014, Sept.30 - Oct.3,2014, Rostov-on-Don, Russi

Robust Audio Watermarking Against the D/A and A/D conversions

Audio watermarking has played an important role in multimedia security. In many applications using audio watermarking, D/A and A/D conversions (denoted by DA/AD in this paper) are often involved. In previous works, however, the robustness issue of audio watermarking against the DA/AD conversions has not drawn sufficient attention yet. In our extensive investigation, it has been found that the degradation of a watermarked audio signal caused by the DA/AD conversions manifests itself mainly in terms of wave magnitude distortion and linear temporal scaling, making the watermark extraction failed. Accordingly, a DWT-based audio watermarking algorithm robust against the DA/AD conversions is proposed in this paper. To resist the magnitude distortion, the relative energy relationships among different groups of the DWT coefficients in the low-frequency sub-band are utilized in watermark embedding by adaptively controlling the embedding strength. Furthermore, the resynchronization is designed to cope with the linear temporal scaling. The time-frequency localization characteristics of DWT are exploited to save the computational load in the resynchronization. Consequently, the proposed audio watermarking algorithm is robust against the DA/AD conversions, other common audio processing manipulations, and the attacks in StirMark Benchmark for Audio, which has been verified by experiments.Comment: Pages 2

Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding

Voice interfaces are becoming accepted widely as input methods for a diverse set of devices. This development is driven by rapid improvements in automatic speech recognition (ASR), which now performs on par with human listening in many tasks. These improvements base on an ongoing evolution of DNNs as the computational core of ASR. However, recent research results show that DNNs are vulnerable to adversarial perturbations, which allow attackers to force the transcription into a malicious output. In this paper, we introduce a new type of adversarial examples based on psychoacoustic hiding. Our attack exploits the characteristics of DNN-based ASR systems, where we extend the original analysis procedure by an additional backpropagation step. We use this backpropagation to learn the degrees of freedom for the adversarial perturbation of the input signal, i.e., we apply a psychoacoustic model and manipulate the acoustic signal below the thresholds of human perception. To further minimize the perceptibility of the perturbations, we use forced alignment to find the best fitting temporal alignment between the original audio sample and the malicious target transcription. These extensions allow us to embed an arbitrary audio input with a malicious voice command that is then transcribed by the ASR system, with the audio signal remaining barely distinguishable from the original signal. In an experimental evaluation, we attack the state-of-the-art speech recognition system Kaldi and determine the best performing parameter and analysis setup for different types of input. Our results show that we are successful in up to 98% of cases with a computational effort of fewer than two minutes for a ten-second audio file. Based on user studies, we found that none of our target transcriptions were audible to human listeners, who still understand the original speech content with unchanged accuracy