Defending Informational Sovereignty by Detecting Deepfakes: Risks and Opportunities of an AI-Based Detector for Deepfake-Based Disinformation and Illegal Activities

This paper will first investigate possible contributions that an AI-based detector for deepfakes could make to the challenge of responding to disinformation as a threat to democracy. Second, this paper will also investigate the implications of such a tool - which was developed, among other reasons, for security purposes - for the emerging European discourse on digital sovereignty in a global environment. While disinformation is surely not a new topic, recent technological developments relating to AI-generated deepfakes have increased the manipulative potential of video and audio-based contents spread online, making it a specific but important current challenge in the global and interconnected information context

Substratumsetzung und Schutz vor Sauerstoffradikalen in <em>Methanosarcina mazei</em>

Methanosarcina (Ms.) mazei ist ein methanogenes Archaeon, das methylierte C1-Verbindungen als Substrate verwenden kann. Bei Wachstum von Ms. mazei auf Trimethylamin (TMA) stehen dem Organismus drei Methylgruppen zur Verfügung, die von einem Methyltransferase-System in den zentralen Stoffwechel übertragen werden. Im Genom von Ms. mazei sind verschiedene Isoenzyme der Methyltransferasen kodiert. Die Art und Weise, wie deren Gene reguliert werden, ist nicht bekannt. Eine Transkriptionsanalyse konnte zeigen, dass einige Gene in Abhängigkeit von der Wachstumsphase exprimiert werden. Außerdem wurde nachgewiesen, dass Ms. mazei TMA stufenweise demethyliert und die Zwischenprodukte zum Teil aus der Zelle transportiert. Über Proteine, die in methanogenen Archaea reaktive Sauerstoffverbindungen eliminieren, ist nur wenig bekannt. Die Proteine MMDx – MM0636 von Ms. mazei haben Ähnlichkeiten zu Enzymen, die in der Antwort der Zelle auf Sauerstoffstress beteiligt sind. Die Proteine wurden heterolog in E. coli produziert. Das Protein MM0632 wurde als Superoxid-Reduktase charakterisiert. Zudem wurde durch biochemische und biophysikalische Analysen der Nachweis erbracht, dass das Protein neben dem [Fe(NHis)4(SCys)]-Zentrum ein [4Fe-4S]-Cluster bindet. MM0632 gehört somit einer neuen Klasse von Superoxid-Reduktasen mit einem Eisen-Schwefel-Cluster an, die in dieser Arbeit als Methanoferrodoxin bezeichnet wurde. Das Desulforedoxin, MMDx, bindet ein [Fe(SCys)4]-Zentrum und wurde als nativer Elektronendonor für Methanoferrodoxin charakterisiert. Die Proteine MM0634 und MM0635 besitzen FMN als prosthetische Gruppe. MM0634 koordiniert zusätzlich ein Eisen-Schwefel-Cluster. Für beide Proteine wurde Ferredoxin als nativer Elektronendonor bestimmt

Statistical pattern recognition for audio-forensics : empirical investigations on the application scenarios audio steganalysis and microphone forensics

Magdeburg, Univ., Fak. für Informatik, Diss., 2013von Christian Krätze

Interaction between Sox proteins of two physiologically distinct bacteria and a new protein involved in thiosulfate oxidation

AbstractOrganisms using the thiosulfate-oxidizing Sox enzyme system fall into two groups: group 1 forms sulfur globules as intermediates (Allochromatium vinosum), group 2 does not (Paracoccus pantotrophus). While several components of their Sox systems are quite similar, i.e. the proteins SoxXA, SoxYZ and SoxB, they differ by Sox(CD)2 which is absent in sulfur globule-forming organisms. Still, the respective enzymes are partly exchangeable in vitro: P. pantotrophus Sox enzymes work productively with A. vinosum SoxYZ whereas A. vinosum SoxB does not cooperate with the P. pantotrophus enzymes. Furthermore, A. vinosum SoxL, a rhodanese-like protein encoded immediately downstream of soxXAK, appears to play an important role in recycling SoxYZ as it increases thiosulfate depletion velocity in vitro without increasing the electron yield

WLAN Steganography: A First Practical Review

Two different approaches for constructing a steganographic channel in an IEEE 802.11 (WLAN) network are introduced in this paper. First test results on the reliability, undetectability and capacity of a prototypical implementation of both approaches are described and discussed

Der Raspberry Pi als Plattform für Fluoreszenzmessungen unter Echtzeitbedingungen

In diesem Beitrag wird vor dem praktischen Hintergrund einer Fluoreszenzmessung der Raspberry Pi als Plattform für ein Echtzeitsystem betrachtet. Es werden dabei Linux und Xenomai im Kernel- und Userspace hinsichtlich der äquidistanten Ausgabe eines Impulses am GPIO-Ausgang verglichen. Für einen Xenomai-Kernelprozess werden die Reaktionszeiten der Flankenerkennung mittels Polling und Interruptsteuerung untersucht. Das Serial Peripheral Interface wird bezüglich seiner Einsetzbarkeit zur Datenübertragung unter Echtzeitbedingungen betrachtet und die Ausführungszeit einer 2 Byte-Übertragung vermessen. Aus diesen Untersuchungen wird die maximal garantierbare Abtastrate für die Fluoreszenzmessung hergeleitet

Information Hiding Patterns Project

This project is driven by a consortium of several scientists from seven institutions spread over four countries. We aim at unifying the terminology and taxonomy for hiding methods in steganography

A Revised Taxonomy of Steganography Embedding Patterns

Steganography embraces several hiding techniques which spawn across multiple domains. However, the related terminology is not unified among the different domains, such as digital media steganography, text steganography, cyber-physical systems steganography, network steganography (network covert channels), local covert channels, and out-of-band covert channels. To cope with this, a prime attempt has been done in 2015, with the introduction of the so-called hiding patterns, which allow to describe hiding techniques in a more abstract manner. Despite significant enhancements, the main limitation of such a taxonomy is that it only considers the case of network steganography. Therefore, this paper reviews both the terminology and the taxonomy of hiding patterns as to make them more general. Specifically, hiding patterns are split into those that describe the embedding and the representation of hidden data within the cover object. As a first research action, we focus on embedding hiding patterns and we show how they can be applied to multiple domains of steganography instead of being limited to the network scenario. Additionally, we exemplify representation patterns using network steganography. Our pattern collection is available under https://patterns.ztt.hs-worms.de

A Revised Taxonomy of Steganography Embedding Patterns

Steganography embraces several hiding techniques which spawn across multiple domains. However, the related terminology is not unified among the different domains, such as digital media steganography, text steganography, cyber-physical systems steganography, network steganography (network covert channels), local covert channels, and out-of-band covert channels. To cope with this, a prime attempt has been done in 2015, with the introduction of the so-called hiding patterns, which allow to describe hiding techniques in a more abstract manner. Despite significant enhancements, the main limitation of such a taxonomy is that it only considers the case of network steganography. Therefore, this paper reviews both the terminology and the taxonomy of hiding patterns as to make them more general. Specifically, hiding patterns are split into those that describe the embedding and the representation of hidden data within the cover object. As a first research action, we focus on embedding hiding patterns and we show how they can be applied to multiple domains of steganography instead of being limited to the network scenario. Additionally, we exemplify representation patterns using network steganography. Our pattern collection is available under https://patterns.ztt.hs-worms.de