Fundamental Limits in Multimedia Forensics and Anti-forensics

As the use of multimedia editing tools increases, people become questioning the authenticity of multimedia content. This is specially a big concern for authorities, such as law enforcement, news reporter and government, who constantly use multimedia evidence to make critical decisions. To verify the authenticity of multimedia content, many forensic techniques have been proposed to identify the processing history of multimedia content under question. However, as new technologies emerge and more complicated scenarios are considered, the limitation of multimedia forensics has been gradually realized by forensic researchers. It is the inevitable trend in multimedia forensics to explore the fundamental limits. In this dissertation, we propose several theoretical frameworks to study the fundamental limits in various forensic problems. Specifically, we begin by developing empirical forensic techniques to deal with the limitation of existing techniques due to the emergence of new technology, compressive sensing. Then, we go one step further to explore the fundamental limit of forensic performance. Two types of forensic problems have been examined. In operation forensics, we propose an information theoretical framework and define forensicability as the maximum information features contain about hypotheses of processing histories. Based on this framework, we have found the maximum number of JPEG compressions one can detect. In order forensics, an information theoretical criterion is proposed to determine when we can and cannot detect the order of manipulation operations that have been applied on multimedia content. Additionally, we have examined the fundamental tradeoffs in multimedia antiforensics, where attacking techniques are developed by forgers to conceal manipulation fingerprints and confuse forensic investigations. In this field, we have defined concealability as the effectiveness of anti-forensics concealing manipulation fingerprints. Then, a tradeoff between concealability, rate and distortion is proposed and characterized for compression anti-forensics, which provides us valuable insights of how forgers may behave under their best strategy

Resiliency Assessment and Enhancement of Intrinsic Fingerprinting

Intrinsic fingerprinting is a class of digital forensic technology that can detect traces left in digital multimedia data in order to reveal data processing history and determine data integrity. Many existing intrinsic fingerprinting schemes have implicitly assumed favorable operating conditions whose validity may become uncertain in reality. In order to establish intrinsic fingerprinting as a credible approach to digital multimedia authentication, it is important to understand and enhance its resiliency under unfavorable scenarios. This dissertation addresses various resiliency aspects that can appear in a broad range of intrinsic fingerprints. The first aspect concerns intrinsic fingerprints that are designed to identify a particular component in the processing chain. Such fingerprints are potentially subject to changes due to input content variations and/or post-processing, and it is desirable to ensure their identifiability in such situations. Taking an image-based intrinsic fingerprinting technique for source camera model identification as a representative example, our investigations reveal that the fingerprints have a substantial dependency on image content. Such dependency limits the achievable identification accuracy, which is penalized by a mismatch between training and testing image content. To mitigate such a mismatch, we propose schemes to incorporate image content into training image selection and significantly improve the identification performance. We also consider the effect of post-processing against intrinsic fingerprinting, and study source camera identification based on imaging noise extracted from low-bit-rate compressed videos. While such compression reduces the fingerprint quality, we exploit different compression levels within the same video to achieve more efficient and accurate identification. The second aspect of resiliency addresses anti-forensics, namely, adversarial actions that intentionally manipulate intrinsic fingerprints. We investigate the cost-effectiveness of anti-forensic operations that counteract color interpolation identification. Our analysis pinpoints the inherent vulnerabilities of color interpolation identification, and motivates countermeasures and refined anti-forensic strategies. We also study the anti-forensics of an emerging space-time localization technique for digital recordings based on electrical network frequency analysis. Detection schemes against anti-forensic operations are devised under a mathematical framework. For both problems, game-theoretic approaches are employed to characterize the interplay between forensic analysts and adversaries and to derive optimal strategies. The third aspect regards the resilient and robust representation of intrinsic fingerprints for multiple forensic identification tasks. We propose to use the empirical frequency response as a generic type of intrinsic fingerprint that can facilitate the identification of various linear and shift-invariant (LSI) and non-LSI operations

RAPID THERMOCYCLER SYSTEM FOR RAPID AMPLIFICATION OF NUCLEIC ACIDS AND RELATED METHODS

A thermo cycling device and method of operating a thermocycler instrument, the instrument including a sample holder, at least one thermal cycling element, and at least one first and second temperature sensors, for causing the sample holder containing the at least one sample to undergo polymerase chain reaction amplification by repeated cycling between at least a denaturation heating stage and an aunealing cooling stage. The first temperature corresponding with the temperature of the sample holder is monitored using the at least one first temperature sensor, and a second temperature corresponding with the temperature external of the sample holder is monitored using the at least one second temperature sensor. Based upon the first temperature and the second temperature, the power that is delivered to the at least one thermal cycling element of the instrument is dynamically controlled

Optical Signal Processing For Data Compression In Ultrafast Measurement

Today the world is filled with continuous deluge of digital information which are ever increasing by every fraction of second. Real-time analog information such as images, RF signals needs to be sampled and quantized to represent in digital domain with help of measurement systems for information analysis, further post processing and storage. Photonics offers various advantages in terms of high bandwidth, security, immunity to electromagnetic interference, reduction in frequency dependant loss as compared to conventional electronic measurement systems. However the large bandwidth data needs to be acquired as per Nyquist principle requiring high bandwidth electronic sampler and digitizer. To address this problem, Photonic Time Stretch has been introduced to reduce the need for high speed electronic measurement equipment by significantly slowing down the speed of sampling signal. However, this generates massive data volume. Photonics-assisted methods such as Anamorphic Stretch Transform, Compressed Sensing and Fourier spectrum acquisition sensing have been addressed to achieve data compression while sampling the information. In this thesis, novel photonic implementations of each of these methods have been investigated through numerical and experimental demonstrations. The main contribution of this thesis include (1) Application of photonic implementation of compressed sensing for Optical Coherence Tomography, Fiber Bragg Grating enabled signal sensing and blind spectrum sensing applications (2) Photonic compressed sensing enabled ultra-fast imaging system (3) Fourier spectrum acquisition for RF spectrum sensing with all-optical approach (4) Adaptive non-uniform photonic time stretch methods using anamorphic stretch transform to reduce the the number of samples to be measured

Optical Signal Processing For Data Compression In Ultrafast Measurement

Today the world is filled with continuous deluge of digital information which are ever increasing by every fraction of second. Real-time analog information such as images, RF signals needs to be sampled and quantized to represent in digital domain with help of measurement systems for information analysis, further post processing and storage. Photonics offers various advantages in terms of high bandwidth, security, immunity to electromagnetic interference, reduction in frequency dependant loss as compared to conventional electronic measurement systems. However the large bandwidth data needs to be acquired as per Nyquist principle requiring high bandwidth electronic sampler and digitizer. To address this problem, Photonic Time Stretch has been introduced to reduce the need for high speed electronic measurement equipment by significantly slowing down the speed of sampling signal. However, this generates massive data volume. Photonics-assisted methods such as Anamorphic Stretch Transform, Compressed Sensing and Fourier spectrum acquisition sensing have been addressed to achieve data compression while sampling the information. In this thesis, novel photonic implementations of each of these methods have been investigated through numerical and experimental demonstrations. The main contribution of this thesis include (1) Application of photonic implementation of compressed sensing for Optical Coherence Tomography, Fiber Bragg Grating enabled signal sensing and blind spectrum sensing applications (2) Photonic compressed sensing enabled ultra-fast imaging system (3) Fourier spectrum acquisition for RF spectrum sensing with all-optical approach (4) Adaptive non-uniform photonic time stretch methods using anamorphic stretch transform to reduce the the number of samples to be measured

Mathematically inspired approaches to face recognition in uncontrolled conditions: super resolution and compressive sensing

Face recognition systems under uncontrolled conditions using surveillance cameras is becom-ing essential for establishing the identity of a person at a distance from the camera and providing safety and security against terrorist, attack, robbery and crime. Therefore, the performance of face recognition in low-resolution degraded images with low quality against im-ages with high quality/and of good resolution/size is considered the most challenging tasks and constitutes focus of this thesis. The work in this thesis is designed to further investigate these issues and the following being our main aim: “To investigate face identification from a distance and under uncontrolled conditions by pri-marily addressing the problem of low-resolution images using existing/modified mathemati-cally inspired super resolution schemes that are based on the emerging new paradigm of compressive sensing and non-adaptive dictionaries based super resolution.” We shall firstly investigate and develop the compressive sensing (CS) based sparse represen-tation of a sample image to reconstruct a high-resolution image for face recognition, by tak-ing different approaches to constructing CS-compliant dictionaries such as Gaussian Random Matrix and Toeplitz Circular Random Matrix. In particular, our focus is on constructing CS non-adaptive dictionaries (independent of face image information), which contrasts with ex-isting image-learnt dictionaries, but satisfies some form of the Restricted Isometry Property (RIP) which is sufficient to comply with the CS theorem regarding the recovery of sparsely represented images. We shall demonstrate that the CS dictionary techniques for resolution enhancement tasks are able to develop scalable face recognition schemes under uncontrolled conditions and at a distance. Secondly, we shall clarify the comparisons of the strength of sufficient CS property for the various types of dictionaries and demonstrate that the image-learnt dictionary far from satisfies the RIP for compressive sensing. Thirdly, we propose dic-tionaries based on the high frequency coefficients of the training set and investigate the im-pact of using dictionaries on the space of feature vectors of the low-resolution image for face recognition when applied to the wavelet domain. Finally, we test the performance of the de-veloped schemes on CCTV images with unknown model of degradation, and show that these schemes significantly outperform existing techniques developed for such a challenging task. However, the performance is still not comparable to what could be achieved in controlled en-vironment, and hence we shall identify remaining challenges to be investigated in the future

Advanced Automation for Space Missions

The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied

Equity Perception and Communication Among Arab Expatriate Professionals in the Kingdom of Saudi Arabia

The research aims to study how the communication context within the Arab cultures influences the employees’ perception of equity and reaction to inequity. Specifically, the study explores how employees from Arab cultural backgrounds communicate with each other within the Saudi working context; and how they collect, interpret and use the different contextual information – from the contexts in which they live and work – in order to make judgements about issues related to the perception of equity and reaction to inequity. In order to study the research topic, a conceptual framework is developed to reconcile between Equity Theory, Social Comparison Theory and Hall’s Context Model; and as a base serving the process of designing/choosing the methods of collecting and analysing the data. Three main research questions are developed which are about (i) how the communication context is related to employees’ willingness and ability to react to inequity (ii) how the communication context shapes the nature of inequity reactions executed by employees and (iii) how the communication context is related to the way equity is perceived among employees. A modified version of critical realism is adopted to focus on exploring the mechanisms, within the communication context, which influence the perception of equity and reaction to inequity. A combination of retroduction and abduction is developed in a sense that retroduction is used to direct the research toward exploring the structure and mechanisms within the research setting, while abduction is used to draw conclusions about how the phenomena studied in the research are evolving by the structure and mechanisms. A mixed methods approach is adopted in the research. The research includes data from thirty-five semi-structured interviews which are conducted in mainly three Saudi private-sector organisations located in Jeddah with twenty-nine male employees and six male managers of six different Arab nationalities. Template analysis is used to analyse the qualitative interview transcripts and field notes, while cluster analysis is used to group the research participants based on their quantitative responses. The research finds that there are no clear-cut areas separating the activities linked to the perception of equity and reaction to inequity. I also conclude that the perception of equity norms and equity comparison components can sometimes be separate activities. Some factors such as the religious interpretation, face-saving, and contextual norms and powers influence the employees’ willingness to react to inequity by altering the way in which those employees perceive equity norms. Here, unwillingness decisions are often made not as a result of personal conviction but as a compromise based on the personal evaluation of the surrounding context, realising the inability of the self to react to such situations in the first place. Thus, it can be concluded that inability to react to inequity can reduce the employees’ willingness to react against under-rewarded situations. The process of perceiving equity comparison components is found to be related to the type of reaction adopted to re-establish the equity; this relationship is represented by groups affiliated by a hidden factor or factors, which is more influential than the ethnicity/nationality of the group’s members. The research makes a methodological contribution to knowledge by suggesting a new approach to study human relations through the communication context; a conceptual contribution by combining the concepts of equity perception, social comparison and communication context in one conceptual framework; and an empirical contribution by providing a fresh insight to contextual themes in the Saudi working environment