Physical Integrity

Trojan attacks are the most common and serious threat to network users. It is a program that appears to be useful program but actually harmful one. It is difficult to detect Trojan attacks because it uses special techniques to conceal its activities from antiviruses and users. Thus, this research intends to retrieve and investigate of Trojan attacks on the network using digital forensic tools namely Wireshark, FTK Imager and Volatility. Two types of Trojan attacks called Remote Access Trojan (RAT) and HTTP Trojan (HT) are created and experimented in this research. These Trojans are sent to the targeted computer in the network through email. Wireshark is used to capture the network packets and then analyze the suspicious packets. FTK Imager is used to capture RAM data on targeted computer. Volatility is used to analyze the captured RAM data and extract suspicious process. This suspicious process is dumped into file and scanned using the Avast antivirus to check whether this process is running Trojan or otherwise. This research may benefit and contribute to the computer security and forensic domain. It can be extends to investigate other Trojan attacks such as Zeus, SubSeven or Back Orifice by using the same digital forensic tools.

Olbers’s paradox, known as the dark night paradox, is an argument in astrophysics that the darkness of the night sky conflicts with the assumption of an infinite and eternal static universe. Big-Bang theory was used to partially explain this paradox, while introducing new problems. Hereby, we propose a better theory, named Sun Matters Theory, to explain this paradox. Moreover, this unique theory supports and extended the Einstein’s static universe model proposed by Albert Einstein in 1917. Further, we proposed our new universe model, “Sun Model of Universe”. Based on the new model and novel theory, we generated innovative field equation by upgrading Einstein’s Field Equation through adding back the cosmological constant, introducing a new variable and modifying the gravitationally-related concepts. According to the Sun Model of Universe, the dark matter and dark energy comprise the so-called “Sun Matters”. The observed phenomenon like the red shift is explained as due to the interaction of ordinary light with Sun Matters leading to its energy and frequency decrease. In Sun Model, our big universe consists of many universes with ordinary matter at the core mixed and surrounded with the Sun Matters. In those universes, the laws of physics may be completely or partially different from that of our ordinary universe with parallel civilizations. The darkness of night can be easily explained as resulting from the interaction of light with the Sun Matters leading to the sharp decrease in the light intensity. Sun Matters also scatter the light from a star, which makes it shining as observed by Hubble. Further, there is a kind of Sun Matters named “Sun Waters”, surrounding every starts. When lights pass by the sun, the Sun Waters deflect the lights to bend the light path. According to the Sun Model, it is the light bent not the space bent that was proposed in the theory of relativities.

The ever increasing prevalence of smartphones and the popularity of social network platforms have facilitated instant sharing of multimedia content through social networks. However, the ease in taking and sharing photos and videos through social networks also allows privacy-intrusive and illegal content to be widely distributed. As such, images captured and shared by users on their profiles are considered as significant digital evidence for social network data analysis. The Sensor Pattern Noise (SPN) caused by camera sensor imperfections during the manufacturing process mainly consists of the Photo-Response Non-Uniformity (PRNU) noise that can be extracted from taken images without hacking the device. It has been proven to be an effective and robust device fingerprint that can be used for different important digital image forensic tasks, such as image forgery detection, source device identification and device linking. Particularly, by fingerprinting the camera sources captured a set of shared images on social networks, User Profile Linking (UPL) can be performed on social network platforms. The aim of this thesis is to present effective and robust methods and algorithms for better fulfilling shared image analysis based on SPN. We propose clustering and classification based methods to achieve Smartphone Identification (SI) and UPL tasks, given a set of images captured by a known number of smartphones and shared on a set of known user profiles. The important outcome of the proposed methods is UPL across different social networks where the clustered images from one social network are applied to fingerprint the related smartphones and link user profiles on the other social network. Also, we propose two methods for large-scale image clustering of different types of the shared images by users, without prior knowledge about the types and number of the smartphones.

Chapter 1 Photometric Stereo: An Overview

The relevance of studying the eye as a complex optical system, combining principles of physics and physiology, lies in the need for a thorough understanding of image formation processes and the mechanisms of visual perception. This study aimed to identify the interrelations between the physical characteristics of the eye’s optical components and their physiological functions, which together ensure clear and accurate visual perception. The research employed methods of geometric optics to model the path of light rays through the eye’s optical media, physiological methods to assess accommodation and visual acuity, as well as a comparative analysis of data obtained from both healthy and pathological eye models. The optical properties of the cornea, crystalline lens and vitreous body were examined, with aberrations introduced by each component analysed, and the effect of accommodation on image formation on the retina established. It was also found that deviations in the optical parameters of the eye, such as changes in the curvature of the cornea or crystalline lens, lead to visual impairments (myopia, hypermetropia, astigmatism) that affect daily functioning. The findings may be of use to ophthalmologists and optometrists in the diagnosis and correction of visual disorders, as well as in the development of new optical devices

Neste trabalho é apresentado um experimento didático e de baixo custo, de forma simples e intuitiva, chamado de projetor de gotas. Este experimento pode ser uma alternativa mais eficiente ao uso de microscópios para a observação de microrganismos em sala de aula, pois, pode ser visualizado por diversas pessoas de uma só vez, além de seus componentes serem de fácil acesso. Os fundamentos físicos do experimento residem nos conceitos de óptica e podem ser abordados de forma dinâmica e interativa, favorecendo a discussão sobre a interação da luz com a matéria orgânica e a natureza ondulatória e geométrica envolvida. O projetor de gotas pode ser utilizado em aulas de diferentes disciplinas tanto de exatas como biológicas, em nível de ensino fundamental, médio e superior. Inicialmente, mostra-se a metodologia experimental assim como, sugestões de materiais alternativos para montagem do experimento. Em seguida, descreve-se a física envolvida para a formação das imagens, para então demonstrar diversas aplicações que podem ser feitas em sala de aula. O foco principal do trabalho foi o de explorar as diversas possibilidades de abordagens que podem ser feitas com o experimento, a fim de mostrar seu alcance e facilidade de interação da física com outras áreas de conhecimento, como por exemplo a biologia.

The advancement of multimedia technologies has enabled electronic processing of information to be recorded in formats that are different from the standard text format. These include image, audio and video formats. The video format is a rich and expressive form of media used in many areas of our everyday life, such as in education, medicine and engineering. The expressiveness of video documents is the main reason for their domination in future information systems. Therefore, effective and efficient access to video information that supports video-based applications has become a critical research area. This has led to the development of, for example, new digitizing and compression tools and technology, video data models and query languages, video data management systems and video analyzers. With applications of a vast amount of stored video data, such as news archives and digital television, video retrieval became, and still is, an active area of research.

The advancement of multimedia technologies has enabled electronic processing of information to be recorded in formats that are different from the standard text format. These include image, audio and video formats. The video format is a rich and expressive form of media used in many areas of our everyday life, such as in education, medicine and engineering. The expressiveness of video documents is the main reason for their domination in future information systems. Therefore, effective and efficient access to video information that supports video-based applications has become a critical research area. This has led to the development of, for example, new digitizing and compression tools and technology, video data models and query languages, video data management systems and video analyzers. With applications of a vast amount of stored video data, such as news archives and digital television, video retrieval became, and still is, an active area of research.

A computational camera uses a combination of optics and processing to produce images that cannot be captured with traditional cameras. Over the last decade, a range of computational cameras have been proposed, which use various optics designs to encode and use computation to decode useful visual information. What is often missing, however, is the quantitative analysis of the relation between camera design and the captured visual information, and little systematic work has been done to evaluate and optimize these computational camera designs. While the optics of computational cameras may be quite complicated, many of them can be effectively characterized by their point spread functions (PSFs): the intensity distribution on an image sensor as a response to a point light source in a scene. This thesis explores the techniques to characterize, evaluate and optimize computational cameras via PSF engineering for computer vision tasks, including image recovery, 3D reconstruction, and image refocusing. I first explore PSF engineering techniques to recover image details from blurry images. Image blur is a problem commonly seen in photography due to a number of reasons, including defocus, lens aberration, diffraction, atmospheric turbulence, object motion, and etc. Image blur is often formulated as a convolution of the latent blur-free image and a PSF, and deconvolution (or deblurring) techniques have to be used to recover image details from a blurry region. Here, I propose a comprehensive framework of PSF evaluation for the purpose of image deblurring, in which the effects of image noise, deblurring algorithm, and the structure of natural images are all taken into account. In defocus blur, the shape of defocus PSF is largely determined by the aperture pattern of the camera lens. By using an evaluation criterion derived from the comprehensive framework, I optimize the aperture pattern to preserve many more image details when defocus occurs. Both through simulations and experiments, I demonstrate the significant improvement gained by using optimized aperture patterns. While defocus blur causes a loss in image detail, it also encodes depth information of scenes in images. A typical depth from defocus (DFD) technique computes depth from two or more images that are captured with circular aperture lenses of different focus settings. Circular apertures produce circular defocus PSFs. In this thesis, I show that the use of a circular aperture severely restricts the accuracy of DFD, and propose a comprehensive framework of PSF evaluation for depth recovery. With this framework, we can derive a criterion for evaluating a pair of apertures with respect to the precision of depth recovery. This criterion is optimized using a genetic algorithm and gradient descent search to arrive at a pair of high resolution apertures. The two coded apertures are found to complement each other in the scene frequencies they preserve. With this property it becomes possible to not only recover depth with greater fidelity but also to obtain a high quality all-focused image from the two defocused images. While depth recovery can significantly benefit from optimized aperture patterns, its overall performance is rigidly limited by the lens aperture's physical size. To transcend this limitation, I propose a novel depth recovery technique using an optical diffuser - referred to as depth from diffusion (DFDiff). I show that DFDiff is analogous to conventional DFD, in which the scatter angle of the diffuser determines the system's effective aperture. High precision depth estimation can be achieved by choosing a proper diffuser and no longer requires the large lenses that DFD requires. Even a consumer camera with a low-end small lens can be used to do high-precision depth estimation when coupled with an optical diffuser. In my detailed analysis of the image formation properties of a DFDiff system, I show a number of examples demonstrating greater precision in depth estimation when using DFDiff. While the finite depth of field (DOF) of a lens camera leads to defocus blur, it also produces artistic visual experience. Many of today's displays are interactive in nature, which opens up a possibility for new kind of visual representations. Users could, for example, interactively refocus images to different depths, so that they can experience the artistic narrow DOF images while simultaneously making available the image detail for the entire image. To enable image refocusing, one typical approach is to capture the entire light field. But this method has the drawback of a significant sacrifice in spatial resolution due to the dimensionality gap: the captured information (light field) is 4D, while the required information (focal stack) is only 3D.In this thesis, I present an imaging system that directly captures focal stacks by a sweeping focal plane. First, I describe how to synchronize focus sweeping with image capturing so that the summed DOF of a focal stack efficiently covers the entire depth range. Then, I take a customized algorithm to enable a seamless refocusing experience, even in textureless regions or with moving objects. Prototype cameras are presented to capture real space-time focal stacks. There is also an interactive refocusing viewer available online at www.focalsweep.com.

In this modern world where information is stored and shared in digital manner in the format of image, video, document privacy and authenticity of the data needs to be preserved which is not an easy task. It has become a major threat where data shared or stored can be tampered or manipulated with and it is very difficult to check for the same. The main principle behind this study is to provide a way to store data in secure manner with the ability to check its authenticity when the need arises. The proposed method integrates blockchain technology to the system which helps to add the media file to the system and store the 256-bit unique hash value generated through keccak-256 hashing algorithm into blockchain using Proof-of-Work protocol. The generated 256-bit hash is stored in blockchain is of immutable nature and it takes approximately 3.5*10^63 seconds to crack the 256-bit encryption. In cases where the need arises to check if the media file is tampered or manipulated it can be done by comparing hash of the media file against hash value that is stored in blockchain. If both hash values are exactly same then the media file is authentic and its integrity is preserved.

Linear and multilinear models (PCA, 3DMM, AAM/ASM, and multilinear tensors) of object shape/appearance have been very popular in computer vision. In this paper, we analyze the applicability of these heuristic models from the fundamental physical laws of object motion and image formation. We prove that under suitable conditions, the image appearance space can be closely approximated to be multilinear, with the illumination and texture subspaces being trilinearly combined with the direct sum of the motion and deformation subspaces. This result provides a physics-based understanding of many of the successes and limitations of the linear and multilinear approaches existing in the computer vision literature, and also identifies some of the conditions under which they are valid. It provides an analytical representation of the image space in terms of different physical factors that affect the image formation process. Numerical analysis of the accuracy of the physics-based models is performed, and tracking results on real data are presented.

During the current Covid-19 pandemic, foreign people can't visit Indonesia to enjoy the beauty of the cultural heritage of the Indonesian archipelago. The internet has become an effective medium for bridging, as the medium is interactive using multimedia, combining text, image, audio, and video formats. For this reason, the purpose of this study is to determine the effect of the use of English in informing cultural heritage of the Indonesian archipelago to the outside community using the internet. This research uses qualitative methods with data collection using literature study and documentation. The results showed that the use of English in disseminating information on the cultural heritage of the Indonesian archipelago is just descriptive only. Thus, it is necessary to use persuasive dictions to attract foreign tourists to visit Indonesia after the Covid-19 pandemic has vanished.

Visualization is very much needed in present day education but many students are lacking it. So to improve visualization, augmented reality(AR) is used. The augmented reality provides interaction for the students so that they can learn more excitingly. Implementing this results in drastic change in present day education system.. To change the present way of learning in classroom we are going to new technological advancements using augmented reality. In this paper we are proposing a new project in the unity we have to import the vuforia unity interfacing package into the unity setup. On importing this we get assets from vuforia to unity which contains the AR components which are used to develop AR applications.in this work we have more better one when compare to previous computer based application like 2-D. in this application all the teaching topics can observe in 3D graphical image and video format. This is the improvement application in AR.

Digital source materials such as films can be transformed in ways that suggest an innovative path for digital humanities research: computationally manipulating sounds and images to create new audiovisual artifacts whose insights might be revealed through their aesthetic power and transformative strangeness. Following upon the strain of digital humanities practice that Mark Sample terms the deformed humanities, this essay subjects a single film to a series of deformations: the classic musical Singin' in the Rain. Accompanying more than twenty original audiovisual deformations in still image, GIF, and video formats, the essay considers both what each new version reveals about the film (and cinema more broadly) and how we might engage with the emergent derivative aesthetic object created by algorithmic practice as a product of the deformed humanities.

Todays many devices generate data everywhere and anytime. Data grow massively and becomes complex thing that needs to be handled. Unstructured data is one type of big data that is difficult to process and consists of unstable attributes. In traffic management, CCTVs are installed to monitor the specific location in the highway. CCTV generates unstructured data in image and video format. These data are difficult to process due to the complexity of the data. This research proposes to implement big data analytics to process real-time unstructured data from CCTV into knowledge displayed in web dashboard. We implement the YOLO framework with YoloV4 Architecture and COCO dataset for traffic flow counting and detecting illegal parking which is categorized as abnormal situation. Unstructured data from CCTV then transformed into semi-structured format in JSON. Data also can be visualized in real time to facilitate local authority to understand the highway situation. Historical data are stored in the NoSQL database to deep more knowledge such as vehicle traffic pattern. The proposed system requires the ROI drawing line as trigger to count the passing vehicles. These experiments are conducted from open CCTV for traffic online in Bali Tower Public Streaming. The prototype result is able to detect the object with 10 fps.