Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Digital Watermarking for Verification of Perception-based Integrity of Audio Data

In certain application fields digital audio recordings contain sensitive content. Examples are historical archival material in public archives that preserve our cultural heritage, or digital evidence in the context of law enforcement and civil proceedings. Because of the powerful capabilities of modern editing tools for multimedia such material is vulnerable to doctoring of the content and forgery of its origin with malicious intent. Also inadvertent data modification and mistaken origin can be caused by human error. Hence, the credibility and provenience in terms of an unadulterated and genuine state of such audio content and the confidence about its origin are critical factors. To address this issue, this PhD thesis proposes a mechanism for verifying the integrity and authenticity of digital sound recordings. It is designed and implemented to be insensitive to common post-processing operations of the audio data that influence the subjective acoustic perception only marginally (if at all). Examples of such operations include lossy compression that maintains a high sound quality of the audio media, or lossless format conversions. It is the objective to avoid de facto false alarms that would be expectedly observable in standard crypto-based authentication protocols in the presence of these legitimate post-processing. For achieving this, a feasible combination of the techniques of digital watermarking and audio-specific hashing is investigated. At first, a suitable secret-key dependent audio hashing algorithm is developed. It incorporates and enhances so-called audio fingerprinting technology from the state of the art in contentbased audio identification. The presented algorithm (denoted as ”rMAC” message authentication code) allows ”perception-based” verification of integrity. This means classifying integrity breaches as such not before they become audible. As another objective, this rMAC is embedded and stored silently inside the audio media by means of audio watermarking technology. This approach allows maintaining the authentication code across the above-mentioned admissible post-processing operations and making it available for integrity verification at a later date. For this, an existent secret-key ependent audio watermarking algorithm is used and enhanced in this thesis work. To some extent, the dependency of the rMAC and of the watermarking processing from a secret key also allows authenticating the origin of a protected audio. To elaborate on this security aspect, this work also estimates the brute-force efforts of an adversary attacking this combined rMAC-watermarking approach. The experimental results show that the proposed method provides a good distinction and classification performance of authentic versus doctored audio content. It also allows the temporal localization of audible data modification within a protected audio file. The experimental evaluation finally provides recommendations about technical configuration settings of the combined watermarking-hashing approach. Beyond the main topic of perception-based data integrity and data authenticity for audio, this PhD work provides new general findings in the fields of audio fingerprinting and digital watermarking. The main contributions of this PhD were published and presented mainly at conferences about multimedia security. These publications were cited by a number of other authors and hence had some impact on their works

A NOVEL JOINT PERCEPTUAL ENCRYPTION AND WATERMARKING SCHEME (JPEW) WITHIN JPEG FRAMEWORK

Due to the rapid growth in internet and multimedia technologies, many new commercial applications like video on demand (VOD), pay-per-view and real-time multimedia broadcast etc, have emerged. To ensure the integrity and confidentiality of the multimedia content, the content is usually watermarked and then encrypted or vice versa. If the multimedia content needs to be watermarked and encrypted at the same time, the watermarking function needs to be performed first followed by encryption function. Hence, if the watermark needs to be extracted then the multimedia data needs to be decrypted first followed by extraction of the watermark. This results in large computational overhead. The solution provided in the literature for this problem is by using what is called partial encryption, in which media data are partitioned into two parts - one to be watermarked and the other is encrypted. In addition, some multimedia applications i.e. video on demand (VOD), Pay-TV, pay-per-view etc, allow multimedia content preview which involves „perceptual‟ encryption wherein all or some selected part of the content is, perceptually speaking, distorted with an encryption key. Up till now no joint perceptual encryption and watermarking scheme has been proposed in the literature. In this thesis, a novel Joint Perceptual Encryption and Watermarking (JPEW) scheme is proposed that is integrated within JPEG standard. The design of JPEW involves the design and development of both perceptual encryption and watermarking schemes that are integrated in JPEG and feasible within the „partial‟ encryption framework. The perceptual encryption scheme exploits the energy distribution of AC components and DC components bitplanes of continuous-tone images and is carried out by selectively encrypting these AC coefficients and DC components bitplanes. The encryption itself is based on a chaos-based permutation reported in an earlier work. Similarly, in contrast to the traditional watermarking schemes, the proposed watermarking scheme makes use of DC component of the image and it is carried out by selectively substituting certain bitplanes of DC components with watermark bits. vi ii Apart from the aforesaid JPEW, additional perceptual encryption scheme, integrated in JPEG, has also been proposed. The scheme is outside of joint framework and implements perceptual encryption on region of interest (ROI) by scrambling the DCT blocks of the chosen ROI. The performances of both, perceptual encryption and watermarking schemes are evaluated and compared with Quantization Index modulation (QIM) based watermarking scheme and reversible Histogram Spreading (RHS) based perceptual encryption scheme. The results show that the proposed watermarking scheme is imperceptible and robust, and suitable for authentication. Similarly, the proposed perceptual encryption scheme outperforms the RHS based scheme in terms of number of operations required to achieve a given level of perceptual encryption and provides control over the amount of perceptual encryption. The overall security of the JPEW has also been evaluated. Additionally, the performance of proposed separate perceptual encryption scheme has been thoroughly evaluated in terms of security and compression efficiency. The scheme is found to be simpler in implementation, have insignificant effect on compression ratios and provide more options for the selection of control factor

Sensor Data Integrity Verification for Real-time and Resource Constrained Systems

Sensors are used in multiple applications that touch our lives and have become an integral part of modern life. They are used in building intelligent control systems in various industries like healthcare, transportation, consumer electronics, military, etc. Many mission-critical applications require sensor data to be secure and authentic. Sensor data security can be achieved using traditional solutions like cryptography and digital signatures, but these techniques are computationally intensive and cannot be easily applied to resource constrained systems. Low complexity data hiding techniques, on the contrary, are easy to implement and do not need substantial processing power or memory. In this applied research, we use and configure the established low complexity data hiding techniques from the multimedia forensics domain. These techniques are used to secure the sensor data transmissions in resource constrained and real-time environments such as an autonomous vehicle. We identify the areas in an autonomous vehicle that require sensor data integrity and propose suitable water-marking techniques to verify the integrity of the data and evaluate the performance of the proposed method against different attack vectors. In our proposed method, sensor data is embedded with application specific metadata and this process introduces some distortion. We analyze this embedding induced distortion and its impact on the overall sensor data quality to conclude that watermarking techniques, when properly configured, can solve sensor data integrity verification problems in an autonomous vehicle.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/167387/3/Raghavendar Changalvala Final Dissertation.pdfDescription of Raghavendar Changalvala Final Dissertation.pdf : Dissertatio

Deep Intellectual Property: A Survey

With the widespread application in industrial manufacturing and commercial services, well-trained deep neural networks (DNNs) are becoming increasingly valuable and crucial assets due to the tremendous training cost and excellent generalization performance. These trained models can be utilized by users without much expert knowledge benefiting from the emerging ''Machine Learning as a Service'' (MLaaS) paradigm. However, this paradigm also exposes the expensive models to various potential threats like model stealing and abuse. As an urgent requirement to defend against these threats, Deep Intellectual Property (DeepIP), to protect private training data, painstakingly-tuned hyperparameters, or costly learned model weights, has been the consensus of both industry and academia. To this end, numerous approaches have been proposed to achieve this goal in recent years, especially to prevent or discover model stealing and unauthorized redistribution. Given this period of rapid evolution, the goal of this paper is to provide a comprehensive survey of the recent achievements in this field. More than 190 research contributions are included in this survey, covering many aspects of Deep IP Protection: challenges/threats, invasive solutions (watermarking), non-invasive solutions (fingerprinting), evaluation metrics, and performance. We finish the survey by identifying promising directions for future research.Comment: 38 pages, 12 figure

Design and Implementation of Algorithms for Traffic Classification

Traffic analysis is the practice of using inherent characteristics of a network flow such as timings, sizes, and orderings of the packets to derive sensitive information about it. Traffic analysis techniques are used because of the extensive adoption of encryption and content-obfuscation mechanisms, making it impossible to infer any information about the flows by analyzing their content. In this thesis, we use traffic analysis to infer sensitive information for different objectives and different applications. Specifically, we investigate various applications: p2p cryptocurrencies, flow correlation, and messaging applications. Our goal is to tailor specific traffic analysis algorithms that best capture network traffic’s intrinsic characteristics in those applications for each of these applications. Also, the objective of traffic analysis is different for each of these applications. Specifically, in Bitcoin, our goal is to evaluate Bitcoin traffic’s resilience to blocking by powerful entities such as governments and ISPs. Bitcoin and similar cryptocurrencies play an important role in electronic commerce and other trust-based distributed systems because of their significant advantage over traditional currencies, including open access to global e-commerce. Therefore, it is essential to the consumers and the industry to have reliable access to their Bitcoin assets. We also examine stepping stone attacks for flow correlation. A stepping stone is a host that an attacker uses to relay her traffic to hide her identity. We introduce two fingerprinting systems, TagIt and FINN. TagIt embeds a secret fingerprint into the flows by moving the packets to specific time intervals. However, FINN utilizes DNNs to embed the fingerprint by changing the inter-packet delays (IPDs) in the flow. In messaging applications, we analyze the WhatsApp messaging service to determine if traffic leaks any sensitive information such as members’ identity in a particular conversation to the adversaries who watch their encrypted traffic. These messaging applications’ privacy is essential because these services provide an environment to dis- cuss politically sensitive subjects, making them a target to government surveillance and censorship in totalitarian countries. We take two technical approaches to design our traffic analysis techniques. The increasing use of DNN-based classifiers inspires our first direction: we train DNN classifiers to perform some specific traffic analysis task. Our second approach is to inspect and model the shape of traffic in the target application and design a statistical classifier for the expected shape of traffic. DNN- based methods are useful when the network is complex, and the traffic’s underlying noise is not linear. Also, these models do not need a meticulous analysis to extract the features. However, deep learning techniques need a vast amount of training data to work well. Therefore, they are not beneficial when there is insufficient data avail- able to train a generalized model. On the other hand, statistical methods have the advantage that they do not have training overhead

A NOVEL JOINT PERCEPTUAL ENCRYPTION AND WATERMARKING SCHEME (JPEW) WITHIN JPEG FRAMEWORK

Due to the rapid growth in internet and multimedia technologies, many new commercial applications like video on demand (VOD), pay-per-view and real-time multimedia broadcast etc, have emerged. To ensure the integrity and confidentiality of the multimedia content, the content is usually watermarked and then encrypted or vice versa. If the multimedia content needs to be watermarked and encrypted at the same time, the watermarking function needs to be performed first followed by encryption function. Hence, if the watermark needs to be extracted then the multimedia data needs to be decrypted first followed by extraction of the watermark. This results in large computational overhead. The solution provided in the literature for this problem is by using what is called partial encryption, in which media data are partitioned into two parts - one to be watermarked and the other is encrypted. In addition, some multimedia applications i.e. video on demand (VOD), Pay-TV, pay-per-view etc, allow multimedia content preview which involves „perceptual‟ encryption wherein all or some selected part of the content is, perceptually speaking, distorted with an encryption key. Up till now no joint perceptual encryption and watermarking scheme has been proposed in the literature. In this thesis, a novel Joint Perceptual Encryption and Watermarking (JPEW) scheme is proposed that is integrated within JPEG standard. The design of JPEW involves the design and development of both perceptual encryption and watermarking schemes that are integrated in JPEG and feasible within the „partial‟ encryption framework. The perceptual encryption scheme exploits the energy distribution of AC components and DC components bitplanes of continuous-tone images and is carried out by selectively encrypting these AC coefficients and DC components bitplanes. The encryption itself is based on a chaos-based permutation reported in an earlier work. Similarly, in contrast to the traditional watermarking schemes, the proposed watermarking scheme makes use of DC component of the image and it is carried out by selectively substituting certain bitplanes of DC components with watermark bits. vi ii Apart from the aforesaid JPEW, additional perceptual encryption scheme, integrated in JPEG, has also been proposed. The scheme is outside of joint framework and implements perceptual encryption on region of interest (ROI) by scrambling the DCT blocks of the chosen ROI. The performances of both, perceptual encryption and watermarking schemes are evaluated and compared with Quantization Index modulation (QIM) based watermarking scheme and reversible Histogram Spreading (RHS) based perceptual encryption scheme. The results show that the proposed watermarking scheme is imperceptible and robust, and suitable for authentication. Similarly, the proposed perceptual encryption scheme outperforms the RHS based scheme in terms of number of operations required to achieve a given level of perceptual encryption and provides control over the amount of perceptual encryption. The overall security of the JPEW has also been evaluated. Additionally, the performance of proposed separate perceptual encryption scheme has been thoroughly evaluated in terms of security and compression efficiency. The scheme is found to be simpler in implementation, have insignificant effect on compression ratios and provide more options for the selection of control factor