Detection of Early-Stage Enterprise Infection by Mining Large-Scale Log Data

Recent years have seen the rise of more sophisticated attacks including advanced persistent threats (APTs) which pose severe risks to organizations and governments by targeting confidential proprietary information. Additionally, new malware strains are appearing at a higher rate than ever before. Since many of these malware are designed to evade existing security products, traditional defenses deployed by most enterprises today, e.g., anti-virus, firewalls, intrusion detection systems, often fail at detecting infections at an early stage. We address the problem of detecting early-stage infection in an enterprise setting by proposing a new framework based on belief propagation inspired from graph theory. Belief propagation can be used either with "seeds" of compromised hosts or malicious domains (provided by the enterprise security operation center -- SOC) or without any seeds. In the latter case we develop a detector of C&C communication particularly tailored to enterprises which can detect a stealthy compromise of only a single host communicating with the C&C server. We demonstrate that our techniques perform well on detecting enterprise infections. We achieve high accuracy with low false detection and false negative rates on two months of anonymized DNS logs released by Los Alamos National Lab (LANL), which include APT infection attacks simulated by LANL domain experts. We also apply our algorithms to 38TB of real-world web proxy logs collected at the border of a large enterprise. Through careful manual investigation in collaboration with the enterprise SOC, we show that our techniques identified hundreds of malicious domains overlooked by state-of-the-art security products

Klassifizierung verschiedener Stadtteile Hamburgs hinsichtlich der Bikesharing-Nutzung

Die vorliegende Arbeit analysiert am Beispiel Hamburg die Stadtteile hinsichtlich der Bikesharing-Nutzung. Ein Großteil der Untersuchungen im Bereich der öffentlichen Fahrradverleihsysteme geben einen Überblick über verschiedene Kundengruppen. Nur Wenige spezialisieren sich auf eine räumlich städtische Betrachtung bezüglich des Bikesharing. Für zukünftige Auswertungen ist es bedeutsam für Städte, die Bikesharing-Systeme betreiben, Auswirkungen eines solchen Systems auf verschiedene Räumlichkeiten in einer Stadt zu prüfen. Das Ziel dieser Forschung ist es zu erfassen, wie sich ausgewählte zeitbezogene und technische Merkmale der Bikesharing-Nutzung auf Stadtteile auswirken. Über einen Zeitraum vom Mai 2016 bis Mai 2017 werden Fahrten in ausgewählten Stadtteilen 24 Stunden lang betrachtet. Die dabei entstehenden Gruppen sollen untereinander möglichst heterogen sein. Als Datengrundlage wurden Daten des „Call a Bike“ Dienstes der Deutschen Bahn aufbereitet. Der Datensatz beinhaltet alle Stadtteile, in denen sich eine oder mehrere Verleihstationen befinden. Eine Clusteranalyse wurde durchgeführt. Drei in sich homogene Cluster sind entstanden, die daraufhin in allen ihren Merkmalsausprägungen ausgewertet wurden. Diese Gruppen unterscheiden sich hauptsächlich in der durchschnittlichen Dauer einer Fahrt und im Anteil der Kurzfahrten unter 30 Minuten. Je weiter ein Ortsteil vom Zentrum entfernt ist, desto länger dauert eine Fahrt. Der Kurzfahrtenanteil sinkt ebenfalls mit zunehmender Entfernung. Diese Erkenntnisse beweisen, dass die Dauer einer Fahrt den größten Einfluss auf das Klassifizieren besitzt. Die meisten Fahrten in den Stadtteilen beginnen primär am Nachmittag. In Hinblick auf die Wochentage fahren Kunden des ersten Clusters vermehrt am Wochenende. In den anderen beiden Clustern bewegen sich die Personen mehr unter der Woche. Bei der technischen Ausleihe ist festzustellen, dass die ersten beiden Cluster mehr Android-Nutzer beinhalten im dritten Cluster mehr iPhone-Nutzer. Die technische Ausleihe ist unabhängig von der Lage der Stadtteile. Untersuchungen haben ergeben, dass die Stadtteile in drei heterogene Cluster zu unterscheiden sind. Das zweite und das dritte Cluster ähneln sich in Zeiträumen sowie in Wochentagen. Weitere Forschung könnte auf andere zeitbezogene Eigenschaften wie Monate und Jahreszeiten eingehen. Der Einfluss der Techniker wäre ebenfalls interessant

FashionFlow: Leveraging Diffusion Models for Dynamic Fashion Video Synthesis from Static Imagery

Our study introduces a new image-to-video generator called FashionFlow to generate fashion videos. By utilising a diffusion model, we are able to create short videos from still fashion images. Our approach involves developing and connecting relevant components with the diffusion model, which results in the creation of high-fidelity videos that are aligned with the conditional image. The components include the use of pseudo-3D convolutional layers to generate videos efficiently. VAE and CLIP encoders capture vital characteristics from still images to condition the diffusion model at a global level. Our research demonstrates a successful synthesis of fashion videos featuring models posing from various angles, showcasing the fit and appearance of the garment. Our findings hold great promise for improving and enhancing the shopping experience for the online fashion industry

A terahertz grid frequency doubler

We present a 144-element terahertz quasi-optical grid frequency doubler. The grid is a planar structure with bow-tie antennas as a unit cell, each loaded with a planar Schottky diode. The maximum output power measured for this grid is 24 mW at 1 THz for 3.1-μs 500-GHz input pulses with a peak input power of 47 W. An efficiency of 0.17% for an input power of 6.3 W and output power of 10.8 mW is measured. To date, this is the largest recorded output power for a multiplier at terahertz frequencies. Input and output tuning curves are presented and an output pattern is measured and compared to theory

Outcome of Communication Training in Veterinary Studies: Influence on the Perception of the Relevance of Veterinary Competencies and Self-Assessment of Communication Skills

Since communication skills contribute significantly to professional success among veterinarians, there is a particular focus on developing communication classes in veterinary curricula. At Freie Universität Berlin, an e-learning course covering the basics of communication and a practical communication course based on role plays with and without simulation persons have been established. The outcome of these communication courses on the assessment of the relevance of several veterinary competencies and on the self-assessment of communication skills using the SE-12 questionnaire was investigated. For this purpose, students were surveyed before and after the e-learning course as well as before and after the practical course. Veterinarians were also surveyed on the relevance of veterinary competencies. The relevance of communicative competencies for professional success was rated significantly higher by the students after completing the practical course than by the other students and the veterinarians. Self-assessment of communication skills showed little increase after the e-learning course, but a significant increase after the practical course. Thus, an effective outcome of the communication classes was observed mainly after the practical course. However, the effect of the e-learning course cannot be ruled out since the students participating in the practical course have also completed the e-learning course beforehand

Transforming Digital Marketing with Generative AI

© 2024 The Author(s). Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The current marketing landscape faces challenges in content creation and innovation, relying heavily on manually created content and traditional channels like social media and search engines. While effective, these methods often lack the creativity and uniqueness needed to stand out in a competitive market. To address this, we introduce MARK-GEN, a conceptual framework that utilises generative artificial intelligence (AI) models to transform marketing content creation. MARK-GEN provides a comprehensive, structured approach for businesses to employ generative AI in producing marketing materials, representing a new method in digital marketing strategies. We present two case studies within the fashion industry, demonstrating how MARK-GEN can generate compelling marketing content using generative AI technologies. This proposition paper builds on our previous technical developments in virtual try-on models, including image-based, multipose, and image-to-video techniques, and is intended for a broad audience, particularly those in business managementPeer reviewe

ENHANCED GRAVITROPISM 2 coordinates molecular adaptations to gravistimulation in the elongation zone of barley roots

Root gravitropism includes gravity perception in the root cap, signal transduction between root cap and elongation zone, and curvature response in the elongation zone. The barley (Hordeum vulgare) mutant enhanced gravitropism 2 (egt2) displays a hypergravitropic root phenotype. We compared the transcriptomic reprogramming of the root cap, the meristem, and the elongation zone of wild-type (WT) and egt2 seminal roots upon gravistimulation in a time-course experiment and identified direct interaction partners of EGT2 by yeast-two-hybrid screening and bimolecular fluorescence complementation validation. We demonstrated that the elongation zone is subjected to most transcriptomic changes after gravistimulation. Here, 33% of graviregulated genes are also transcriptionally controlled by EGT2, suggesting a central role of this gene in controlling the molecular networks associated with gravitropic bending. Gene co-expression analyses suggested a role of EGT2 in cell wall and reactive oxygen species-related processes, in which direct interaction partners of EGT2 regulated by EGT2 and gravity might be involved. Taken together, this study demonstrated the central role of EGT2 and its interaction partners in the networks controlling root zone-specific transcriptomic reprogramming of barley roots upon gravistimulation. These findings can contribute to the development of novel root idiotypes leading to improved crop performance