Information Theoretical Analysis of Identification based on Active Content Fingerprinting

Content fingerprinting and digital watermarking are techniques that are used for content protection and distribution monitoring. Over the past few years, both techniques have been well studied and their shortcomings understood. Recently, a new content fingerprinting scheme called {\em active content fingerprinting} was introduced to overcome these shortcomings. Active content fingerprinting aims to modify a content to extract robuster fingerprints than the conventional content fingerprinting. Moreover, contrary to digital watermarking, active content fingerprinting does not embed any message independent of contents thus does not face host interference. The main goal of this paper is to analyze fundamental limits of active content fingerprinting in an information theoretical framework.Comment: 35th WIC Symposium on Information Theory in the Benelu

An Indoor Navigation System Using a Sensor Fusion Scheme on Android Platform

With the development of wireless communication networks, smart phones have become a necessity for people’s daily lives, and they meet not only the needs of basic functions for users such as sending a message or making a phone call, but also the users’ demands for entertainment, surfing the Internet and socializing. Navigation functions have been commonly utilized, however the navigation function is often based on GPS (Global Positioning System) in outdoor environments, whereas a number of applications need to navigate indoors. This paper presents a system to achieve high accurate indoor navigation based on Android platform. To do this, we design a sensor fusion scheme for our system. We divide the system into three main modules: distance measurement module, orientation detection module and position update module. We use an efficient way to estimate the stride length and use step sensor to count steps in distance measurement module. For orientation detection module, in order to get the optimal result of orientation, we then introduce Kalman filter to de-noise the data collected from different sensors. In the last module, we combine the data from the previous modules and calculate the current location. Results of experiments show that our system works well and has high accuracy in indoor situations

Microbial diversity in Baltic Sea sediments

This thesis focuses on microbial community structures and their functions in Baltic Sea sediments. First we investigated the distribution of archaea and bacteria in Baltic Sea sediments along a eutrophication gradient. Community profile analysis of 16S rRNA genes using terminal restriction length polymorphism (T-RFLP) indicated that archaeal and bacterial communities were spatially heterogeneous. By employing statistical ordination methods we observed that archaea and bacteria were structured and impacted differently by environmental parameters that were significantly linked to eutrophication. In a separate study, we analyzed bacterial communities at a different site in the Baltic Sea that was heavily contaminated with polyaromatic hydrocarbons (PAHs) and several other pollutants. Sediment samples were collected before and after remediation by dredging in two consecutive years. A polyphasic experimental approach was used to assess growing bacteria and degradation genes in the sediments. The bacterial communities were significantly different before and after dredging of the sediment. Several isolates collected from contaminated sediments showed an intrinsic capacity for degradation of phenanthrene (a PAH model compound). Quantititative real-time PCR was used to monitor the abundance of degradation genes in sediment microcosms spiked with phenanthrene. Although both xylE and phnAc genes increased in abundance in the microcosms, the isolates only carried phnAc genes. Isolates with closest 16S rRNA gene sequence matches to Exigobacterium oxidotolerans, a Pseudomonas sp. and a Gammaproteobacterium were identified by all approaches used as growing bacteria that are capable of phenanthrene degradation. These isolates were assigned species and strain designations as follows: Exiguobacterium oxidotolerans AE3, Pseudomonas fluorescens AE1 and Pseudomonas migulae AE2. We also identified and studied the distribution of actively growing bacteria along red-ox profiles in Baltic Sea sediments. Community structures were found to be significantly different at different red-ox depths. Also, according to multivariate statistical ordination analysis organic carbon, nitrogen, and red-ox potential were crucial parameters for structuring the bacterial communities on a vertical scale. Novel lineages of bacteria were obtained by sequencing 16S rRNA genes from different red-ox depths and sampling stations indicating that bacterial diversity in Baltic Sea sediments is largely unexplored

Republican Monsters: The Cultural Construction of American Positivist Criminology, 1767-1920

This dissertation examines the history of and cultural influences on positivist criminology in the United States. From Benjamin Rush to the present day, the U.S. has produced an extensive corpus of empirical and theoretical studies that seeks to discern an objective, scientifically-grounded basis for criminal behavior. American positivist criminology has drawn on numerous subfields and theories, including rational choice / economic theory, biology, and psychology, but in all cases, maintains that a purely scientific explanation of offending is possible. This study proceeds from the perspective that divisions between scientific and non-scientific thought are untenable. Drawing on scholarship in literary criticism and sociology, I argue that positivist criminology confronts an inherent contradiction in purporting to develop a purely scientific account of phenomena that are defined by the moral and cultural sentiments of a society. I thus hypothesize that positivist criminology is in fact reliant on the irrational and fictive cultural tropes and images of crime that it claims to exorcize. The dissertation proceeds by reviewing the literature on the history of criminology, developing a set of functional types or tropes for character analysis, and then examining four separate periods in the development of scientific criminology: eighteenth century studies of rational action, nineteenth century studies of defective reasoning, early twentieth century studies of race and crime, and the development of scientifically informed criminalistics programs. Each of these cases captures a different period and focus in the development of scientific criminology. In threading continuity between these cases, I show how criminological positivism is consistently reliant on culturally informed tropes and characters to render itself sensible and coherent

FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic

Mobile-application fingerprinting of network traffic is valuable for many security solutions as it provides insights into the apps active on a network. Unfortunately, existing techniques require prior knowledge of apps to be able to recognize them. However, mobile environments are constantly evolving, i.e., apps are regularly installed, updated, and uninstalled. Therefore, it is infeasible for existing fingerprinting approaches to cover all apps that may appear on a network. Moreover, most mobile traffic is encrypted, shows similarities with other apps, e.g., due to common libraries or the use of content delivery networks, and depends on user input, further complicating the fingerprinting process.As a solution, we propose FlowPrint, a semi-supervised approach for fingerprinting mobile apps from (encrypted) network traffic.We automatically find temporal correlations among destination-related features of network traffic and use these correlations to generate app fingerprints.Our approach is able to fingerprint previously unseen apps, something that existing techniques fail to achieve.We evaluate our approach for both Android and iOS in the setting of app recognition, where we achieve an accuracy of 89.2%, significantly outperforming state-of-the-art solutions.In addition, we show that our approach can detect previously unseen apps with a precision of 93.5%, detecting 72.3% of apps within the first five minutes of communication

Two-dimensional infrared spectroscopy for protein analysis

A number of forms of coherent multi-dimensional vibrational spectroscopy (CMDVS) have been identified as being useful for addressing a range of biological problems. Here a particular member of this family of spectroscopies, electronvibration- vibration two-dimensional infrared (EVV 2DIR) spectroscopy (also known as DOubly-Vibrationally Enhanced InfraRed (DOVE-IR)), is explored for its possible utility for two particular bioanalytical applications; protein identification and the study of enzyme mechanisms. The main focus of this work is on the development of EVV 2DIR as a tool for high-throughput, label-free proteomics, in particular for protein identification and absolute quantification. The protein fingerprinting strategy is based on the identification of proteins through their spectroscopically determined amino acid compositions. To this end, spectral signatures of amino acid side chains (tyrosine, phenylalanine and tryptophan) have been identified, as well as those from CH2 and CH3 groups which have been found to be appropriate for use as internal references. The intensities of these cross peaks are measured to give proteins’ amino acid compositions in the form of amino acid / CHx ratios. Specialised databases comprising the amino acid / CHx ratios of proteins have been developed for achieving protein identifications using the EVV 2DIR data. The second strand of this research considers the potential of triply resonant EVV 2DIR for studying protein structures and mechanisms. It is possible to use the electronic polarising properties of EVV 2DIR to good effect to achieve significant enhancement of the signal size when probing a chromophore. Here this effect is demonstrated for the case of bacteriorhodopsin (bR) membranes isolated from Halobacterium salinarium. The signal enhancement that is achievable from the retinal chromophore at the heart of bR makes it possible to study this whilst avoiding the surrounding protein

Multimedia Protection using Content and Embedded Fingerprints

Improved digital connectivity has made the Internet an important medium for multimedia distribution and consumption in recent years. At the same time, this increased proliferation of multimedia has raised significant challenges in secure multimedia distribution and intellectual property protection. This dissertation examines two complementary aspects of the multimedia protection problem that utilize content fingerprints and embedded collusion-resistant fingerprints. The first aspect considered is the automated identification of multimedia using content fingerprints, which is emerging as an important tool for detecting copyright violations on user generated content websites. A content fingerprint is a compact identifier that captures robust and distinctive properties of multimedia content, which can be used for uniquely identifying the multimedia object. In this dissertation, we describe a modular framework for theoretical modeling and analysis of content fingerprinting techniques. Based on this framework, we analyze the impact of distortions in the features on the corresponding fingerprints and also consider the problem of designing a suitable quantizer for encoding the features in order to improve the identification accuracy. The interaction between the fingerprint designer and a malicious adversary seeking to evade detection is studied under a game-theoretic framework and optimal strategies for both parties are derived. We then focus on analyzing and understanding the matching process at the fingerprint level. Models for fingerprints with different types of correlations are developed and the identification accuracy under each model is examined. Through this analysis we obtain useful guidelines for designing practical systems and also uncover connections to other areas of research. A complementary problem considered in this dissertation concerns tracing the users responsible for unauthorized redistribution of multimedia. Collusion-resistant fingerprints, which are signals that uniquely identify the recipient, are proactively embedded in the multimedia before redistribution and can be used for identifying the malicious users. We study the problem of designing collusion resistant fingerprints for embedding in compressed multimedia. Our study indicates that directly adapting traditional fingerprinting techniques to this new setting of compressed multimedia results in low collusion resistance. To withstand attacks, we propose an anti-collusion dithering technique for embedding fingerprints that significantly improves the collusion resistance compared to traditional fingerprints