Robust information hiding in low-resolution videos with quantization index modulation in DCT-CS domain

Video information hiding and transmission over noisy channels leads to errors on video and degradation of the visual quality notably. In this paper, a video signal fusion scheme is proposed to combine sensed host signal and the hidden signal with quantization index modulation (QIM) technology in the compressive sensing (CS) and discrete cosine transform (DCT) domain. With quantization based signal fusion, a realistic solution is provided to the receiver, which can improve the reconstruction video quality without requiring significant extra channel resource. The extensive experiments have shown that the proposed scheme can effectively achieve the better trade-off between robustness and statistical invisibility for video information hiding communication. This will be extremely important for low-resolution video analytics and protection in big data era

Privacy Intelligence: A Survey on Image Sharing on Online Social Networks

Image sharing on online social networks (OSNs) has become an indispensable part of daily social activities, but it has also led to an increased risk of privacy invasion. The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharing images on OSNs. However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection. As a result, an more intelligent environment for privacy-friendly OSN image sharing is in demand. To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing. Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field. The framework is divided into three main stages: local management, online management and social experience. At each stage, we identify typical sharing-related user behaviors, the privacy issues generated by those behaviors, and review representative intelligent solutions. The resulting analysis describes an intelligent privacy-enhancing chain for closed-loop privacy management. We also discuss the challenges and future directions existing at each stage, as well as in publicly available datasets.Comment: 32 pages, 9 figures. Under revie

Introductory Computer Forensics

INTERPOL (International Police) built cybercrime programs to keep up with emerging cyber threats, and aims to coordinate and assist international operations for ?ghting crimes involving computers. Although signi?cant international efforts are being made in dealing with cybercrime and cyber-terrorism, ?nding effective, cooperative, and collaborative ways to deal with complicated cases that span multiple jurisdictions has proven dif?cult in practic

A framework for biometric recognition using non-ideal iris and face

Off-angle iris images are often captured in a non-cooperative environment. The distortion of the iris or pupil can decrease the segmentation quality as well as the data extracted thereafter. Moreover, iris with an off-angle of more than 30° can have non-recoverable features since the boundary cannot be properly localized. This usually becomes a factor of limited discriminant ability of the biometric features. Limitations also come from the noisy data arisen due to image burst, background error, or inappropriate camera pixel noise. To address the issues above, the aim of this study is to develop a framework which: (1) to improve the non-circular boundary localization, (2) to overcome the lost features, and (3) to detect and minimize the error caused by noisy data. Non-circular boundary issue is addressed through a combination of geometric calibration and direct least square ellipse that can geometrically restore, adjust, and scale up the distortion of circular shape to ellipse fitting. Further improvement comes in the form of an extraction method that combines Haar Wavelet and Neural Network to transform the iris features into wavelet coefficient representative of the relevant iris data. The non-recoverable features problem is resolved by proposing Weighted Score Level Fusion which integrates face and iris biometrics. This enhancement is done to give extra distinctive information to increase authentication accuracy rate. As for the noisy data issues, a modified Reed Solomon codes with error correction capability is proposed to decrease intra-class variations by eliminating the differences between enrollment and verification templates. The key contribution of this research is a new unified framework for high performance multimodal biometric recognition system. The framework has been tested with WVU, UBIRIS v.2, UTMIFM, ORL datasets, and achieved more than 99.8% accuracy compared to other existing methods

The use of wavelet watermarking and statistical classification techniques for collusion detection and identification in multimedia forensics

This research proposes a wavelet-based multimedia fingerprint scheme and statistical clustering algorithm for collusion detection and identification. The use of digital multimedia has steadily increased using mediums like the Internet. Encryption is generally used to safeguard content while in transmission, but offers no protection against duplication. Tracing unauthorized content distributors has become an increasing concern for the media industry. Unauthorized duplication, piracy, and illegal redistribution of multimedia content account for several billion dollars in losses every year. It is important to design reliable investigative techniques against unauthorized duplication and propagation, and provide protection in the form of theft deterrence. Some fingerprint embedding schemes are robust against single-user modification attacks. However, a new breed of attacks, known as collusion attacks, have been used to defeat those underlying schemes. These attacks use the combination of multiple fingerprinted copies to create a new version where the underlying fingerprint is highly attenuated, becoming untraceable to the colluders. This research adopts the use of wavelet transforms and statistical classification techniques to effectively identify the set of colluders involved in a collusion attack while maintaining low miss rates and false accusation rates. The experimental results show that the solution is effective in identifying large colluder sets without the knowledge of the number of colluders involved in an attack and the collusion attack used

Watermarking techniques for genuine fingerprint authentication.

Fingerprints have been used to authenticate people remotely and allow them access to a system. However, the fingerprint-capture sensor is cracked easily using false fingerprint features constructed from a glass surface. Fake fingerprints, which can be easily obtained by attackers, could cheat the system and this issue remains a challenge in fingerprint-based authentication systems. Thus, a mechanism that can validate the originality of fingerprint samples is desired. Watermarking techniques have been used to enhance the fingerprint-based authentication process, however, none of them have been found to satisfy genuine person verification requirements. This thesis focuses on improving the verification of the genuine fingerprint owner using watermarking techniques. Four research issues are being addressed to achieve the main aim of this thesis. The first research task was to embed watermark into fingerprint images collected from different angles. In verification systems, an acquired fingerprint image is compared with another image, which was stored in the database at the time of enrolment. The displacements and rotations of fingerprint images collected from different angles lead to different sets of minutiae. In this case, the fingerprint-based authentication system operates on the ‘close enough’ matching principle between samples and template. A rejection of genuine samples can occur erroneously in such cases. The process of embedding watermarks into fingerprint samples could make this worse by adding spurious minutiae or corrupting correct minutiae. Therefore, a watermarking method for fingerprint images collected from different angles is proposed. Second, embedding high payload of watermark into fingerprint image and preserving the features of the fingerprint from being affected by the embedded watermark is challenging. In this scenario, embedding multiple watermarks that can be used with fingerprint to authenticate the person is proposed. In the developed multi-watermarks schema, two watermark images of high payloads are embedded into fingerprints without significantly affecting minutiae. Third, the robustness of the watermarking approach against image processing operations is important. The implemented fingerprint watermarking algorithms have been proposed to verify the origin of the fingerprint image; however, they are vulnerable to several modes of image operations that can affect the security level of the authentication system. The embedded watermarks, and the fingerprint features that are used subsequently for authentication purposes, can be damaged. Therefore, the current study has evaluated in detail the robustness of the proposed watermarking methods to the most common image operations. Fourth, mobile biometrics are expected to link the genuine user to a claimed identity in ubiquitous applications, which is a great challenge. Touch-based sensors for capturing fingerprints have been incorporated into mobile phones for user identity authentication. However, an individual fake fingerprint cracking the sensor on the iPhone 5S is a warning that biometrics are only a representation of a person, and are not secure. To make thing worse, the ubiquity of mobile devices leaves much room for adversaries to clone, impersonate or fabricate fake biometric identities and/or mobile devices to defraud systems. Therefore, the integration of multiple identifiers for both the capturing device and its owner into one unique entity is proposed

Frame-synchronous Blind Audio Watermarking for Tamper Proofing and Self-Recovery

This paper presents a lifting wavelet transform (LWT)-based blind audio watermarking scheme designed for tampering detection and self-recovery. Following 3-level LWT decomposition of a host audio, the coefficients in selected subbands are first partitioned into frames for watermarking. To suit different purposes of the watermarking applications, binary information is packed into two groups: frame-related data are embedded in the approximation subband using rational dither modulation; the source-channel coded bit sequence of the host audio is hidden inside the 2nd and 3rd -detail subbands using 2N-ary adaptive quantization index modulation. The frame-related data consists of a synchronization code used for frame alignment and a composite message gathered from four adjacent frames for content authentication. To endow the proposed watermarking scheme with a self-recovering capability, we resort to hashing comparison to identify tampered frames and adopt a Reed–Solomon code to correct symbol errors. The experiment results indicate that the proposed watermarking scheme can accurately locate and recover the tampered regions of the audio signal. The incorporation of the frame synchronization mechanism enables the proposed scheme to resist against cropping and replacement attacks, all of which were unsolvable by previous watermarking schemes. Furthermore, as revealed by the perceptual evaluation of audio quality measures, the quality degradation caused by watermark embedding is merely minor. With all the aforementioned merits, the proposed scheme can find various applications for ownership protection and content authentication

Optimisation of Tamper Localisation and Recovery Watermarking Techniques

Digital watermarking has found many applications in many fields, such as: copyright tracking, media authentication, tamper localisation and recovery, hardware control, and data hiding. The idea of digital watermarking is to embed arbitrary data inside a multimedia cover without affecting the perceptibility of the multimedia cover itself. The main advantage of using digital watermarking over other techniques, such as signature based techniques, is that the watermark is embedded into the multimedia cover itself and will not be removed even with the format change. Image watermarking techniques are categorised according to their robustness against modification into: fragile, semi-fragile, and robust watermarking. In fragile watermarking any change to the image will affect the watermark, this makes fragile watermarking very useful in image authentication applications, as in medical and forensic fields, where any tampering of the image is: detected, localised, and possibly recovered. Fragile watermarking techniques are also characterised by a higher capacity when compared to semi-fragile and robust watermarking. Semifragile watermarking techniques resist some modifications, such as lossy compression and low pass filtering. Semi-fragile watermarking can be used in authentication and copyright validation applications whenever the amount of embedded information is small and the expected modifications are not severe. Robust watermarking techniques are supposed to withstand more severe modifications, such as rotation and geometrical bending. Robust watermarking is used in copyright validation applications, where copyright information in the image must remains accessible even after severe modification. This research focuses on the application of image watermarking in tamper localisation and recovery and it aims to provide optimisation for some of its aspects. The optimisation aims to produce watermarking techniques that enhance one or more of the following aspects: consuming less payload, having better recovery quality, recovering larger tampered area, requiring less calculations, and being robust against the different counterfeiting attacks. Through the survey of the main existing techniques, it was found that most of them are using two separate sets of data for the localisation and the recovery of the tampered area, which is considered as a redundancy. The main focus in this research is to investigate employing image filtering techniques in order to use only one set of data for both purposes, leading to a reduced redundancy in the watermark embedding and enhanced capacity. Four tamper localisation and recovery techniques were proposed, three of them use one set of data for localisation and recovery while the fourth one is designed to be optimised and gives a better performance even though it uses separate sets of data for localisation and recovery. The four techniques were analysed and compared to two recent techniques in the literature. The performance of the proposed techniques vary from one technique to another. The fourth technique shows the best results regarding recovery quality and Probability of False Acceptance (PFA) when compared to the other proposed techniques and the two techniques in the literature, also, all proposed techniques show better recovery quality when compared to the two techniques in the literature

Digital watermarking methods for data security and authentication

Philosophiae Doctor - PhDCryptology is the study of systems that typically originate from a consideration of the ideal circumstances under which secure information exchange is to take place. It involves the study of cryptographic and other processes that might be introduced for breaking the output of such systems - cryptanalysis. This includes the introduction of formal mathematical methods for the design of a cryptosystem and for estimating its theoretical level of securit