Effiziente und erklärbare Erkennung von mobiler Schadsoftware mittels maschineller Lernmethoden

In recent years, mobile devices shipped with Google’s Android operating system have become ubiquitous. Due to their popularity and the high concentration of sensitive user data on these devices, however, they have also become a profitable target of malware authors. As a result, thousands of new malware instances targeting Android are found almost every day. Unfortunately, common signature-based methods often fail to detect these applications, as these methods can- not keep pace with the rapid development of new malware. Consequently, there is an urgent need for new malware detection methods to tackle this growing threat. In this thesis, we address the problem by combining concepts of static analysis and machine learning, such that mobile malware can be detected directly on the mobile device with low run-time overhead. To this end, we first discuss our analysis results of a sophisticated malware that uses an ultrasonic side channel to spy on unwitting smartphone users. Based on the insights we gain throughout this thesis, we gradually develop a method that allows detecting Android malware in general. The resulting method performs a broad static analysis, gathering a large number of features associated with an application. These features are embedded in a joint vector space, where typical patterns indicative of malware can be automatically identified and used for explaining the decisions of our method. In addition to an evaluation of its overall detection and run-time performance, we also examine the interpretability of the underlying detection model and strengthen the classifier against realistic evasion attacks. In a large set of experiments, we show that the method clearly outperforms several related approaches, including popular anti-virus scanners. In most experiments, our approach detects more than 90% of all malicious samples in the dataset at a low false positive rate of only 1%. Furthermore, even on older devices, it offers a good run-time performance, and can output a decision along with a proper explanation within a few seconds, despite the use of machine learning techniques directly on the mobile device. Overall, we find that the application of machine learning techniques is a promising research direction to improve the security of mobile devices. While these techniques alone cannot defeat the threat of mobile malware, they at least raise the bar for malicious actors significantly, especially if combined with existing techniques.Die Verbreitung von Smartphones, insbesondere mit dem Android-Betriebssystem, hat in den vergangenen Jahren stark zugenommen. Aufgrund ihrer hohen Popularität haben sich diese Geräte jedoch zugleich auch zu einem lukrativen Ziel für Entwickler von Schadsoftware entwickelt, weshalb mittlerweile täglich neue Schadprogramme für Android gefunden werden. Obwohl verschiedene Lösungen existieren, die Schadprogramme auch auf mobilen Endgeräten identifizieren sollen, bieten diese in der Praxis häufig keinen ausreichenden Schutz. Dies liegt vor allem daran, dass diese Verfahren zumeist signaturbasiert arbeiten und somit schädliche Programme erst zuverlässig identifizieren können, sobald entsprechende Erkennungssignaturen vorhanden sind. Jedoch wird es für Antiviren-Hersteller immer schwieriger, die zur Erkennung notwendigen Signaturen rechtzeitig bereitzustellen. Daher ist die Entwicklung von neuen Verfahren nötig, um der wachsenden Bedrohung durch mobile Schadsoftware besser begegnen zu können. In dieser Dissertation wird ein Verfahren vorgestellt und eingehend untersucht, das Techniken der statischen Code-Analyse mit Methoden des maschinellen Lernens kombiniert, um so eine zuverlässige Erkennung von mobiler Schadsoftware direkt auf dem Mobilgerät zu ermöglichen. Die Methode analysiert hierfür mobile Anwendungen zunächst statisch und extrahiert dabei spezielle Merkmale, die eine Abbildung einer Applikation in einen hochdimensionalen Vektorraum ermöglichen. In diesem Vektorraum sind schließlich maschinelle Lernmethoden in der Lage, automatisch Muster zur Erkennung von Schadprogrammen zu finden. Die gefundenen Muster können dabei nicht nur zur Erkennung, sondern darüber hinaus auch zur Erklärung einer getroffenenen Entscheidung dienen. Im Rahmen einer ausführlichen Evaluation wird nicht nur die Erkennungsleistung und die Laufzeit der vorgestellten Methode untersucht, sondern darüber hinaus das gelernte Erkennungsmodell im Detail analysiert. Hierbei wird auch die Robustheit des Modells gegenüber gezielten Angriffe untersucht und verbessert. In einer Reihe von Experimenten kann gezeigt werden, dass mit dem vorgeschlagenen Verfahren bessere Ergebnisse erzielt werden können als mit vergleichbaren Methoden, sogar einschließlich einiger populärer Antivirenprogramme. In den meisten Experimenten kann die Methode Schadprogramme zuverlässig erkennen und erreicht Erkennungsraten von über 90% bei einer geringen Falsch-Positiv-Rate von 1%

Nitrogen isotope ratios trace high-pH conditions in a terrestrial Mars analog site

This research was financially supported by the Leverhulme Trust to T.W.L. E.E.S. acknowledges start-up funds from the University of St. Andrews. The NASA Astrobiology Institute under Cooperative Agreement no. NNA15BB03A issued through the Science Mission Directorate also provided funds as did a NASA Fellowship in support of C.T. under Cooperative Agreement no. 80NSSC19K1739 issued through the NASA Office of STEM Engagement.High-pH alkaline lakes are among the most productive ecosystems on Earth and prime targets in the search for life on Mars; however, a robust proxy for such settings does not yet exist. Nitrogen isotope fractionation resulting from NH3 volatilization at high pH has the potential to fill this gap. To validate this idea, we analyzed samples from the Nördlinger Ries, a Miocene impact crater lake that displayed pH values up to 9.8 as inferred from mineralogy and aqueous modeling. Our data show a peak in δ15N of +17‰ in the most alkaline facies, followed by a gradual decline to around +5‰, concurrent with the proposed decline in pH, highlighting the utility of nitrogen isotopes as a proxy for high-pH conditions. In combination with independent mineralogical indicators for high alkalinity, nitrogen isotopes can provide much-needed quantitative constraints on ancient atmospheric Pco2 (partial pressure of CO2) and thus climatic controls on early Earth and Mars.Publisher PDFPeer reviewe

Standard Operating Procedure and Workplan for the Terrestrial Environmental Observation Network (TEON) – Arctic Landscape Conservation Cooperative: Kuparuk River Basin and Adjacent Catchments

TABLE OF CONTENTS ................................................................................................................. i DISCLAIMER ................................................................................................................................ ii CONVERSION FACTORS, UNITS, WATER QUALITY UNITS, VERTICAL AND HORIZONTAL DATUM, ABBREVIATIONS AND SYMBOLS .............................................. iii 1 INTRODUCTION .................................................................................................................. 1 2 STATION HISTORY ............................................................................................................. 5 3 DATA COLLECTION METHODS ....................................................................................... 8 3.1 Air Temperature and Relative Humidity ........................................................................ 12 3.2 Wind Speed and Direction ............................................................................................. 14 3.3 Radiation ........................................................................................................................ 15 3.3.1 Net Radiation .......................................................................................................... 15 3.3.2 Shortwave Radiation ............................................................................................... 16 3.3.3 Longwave Radiation ............................................................................................... 17 3.4 Summer Precipitation ..................................................................................................... 18 3.5 Snow Depth .................................................................................................................... 18 3.6 Field Snow Survey ......................................................................................................... 20 3.7 Water Levels .................................................................................................................. 21 3.8 Discharge Measurements ............................................................................................... 23 3.8.1 Acoustic Doppler Current Profiler .......................................................................... 25 4 STATION TELEMETRY ..................................................................................................... 28 5 DATALOGGER PROGRAM .............................................................................................. 30 6 METADATA ........................................................................................................................ 31 7 QUALITY CONTROL AND DATA PROCESSING .......................................................... 32 8 DATA REPORTING AND ARCHIVING ........................................................................... 33 9 REFERENCES ..................................................................................................................... 36 10 APPENDIX LIST ................................................................................................................. 3

Modern Erosion Rates and Loss of Coastal Features and Sites, Beaufort Sea Coastline, Alaska

This study presents modern erosion rate measurements based upon vertical aerial photography captured in 1955, 1979, and 2002 for a 100 km segment of the Beaufort Sea coastline. Annual erosion rates from 1955 to 2002 averaged 5.6 m a-1. However, mean erosion rates increased from 5.0 m a-1 in 1955–79 to 6.2 m a-1 in 1979–2002. Furthermore, from the first period to the second, erosion rates increased at 60% (598) of the 992 sites analyzed, decreased at 31% (307), and changed less than ± 30 cm at 9% (87). Historical observations and quantitative studies over the past 175 years allowed us to place our erosion rate measurements into a longer-term context. Several of the coastal features along this stretch of coastline received Western place names during the Dease and Simpson expedition in 1837, and the majority of those features had been lost by the early 1900s as a result of coastline erosion, suggesting that erosion has been active over at least the historical record. Incorporation of historical and modern observations also allowed us to detect the loss of both cultural and historical sites and modern infrastructure. U.S. Geological Survey topographic maps reveal a number of known cultural and historical sites, as well as sites with modern infrastructure constructed as recently as the 1950s, that had disappeared by the early 2000s as a result of coastal erosion. We were also able to identify sites that are currently being threatened by an encroaching coastline. Our modern erosion rate measurements can potentially be used to predict when a historical site or modern infrastructure will be affected if such erosion rates persist.Cette étude présente les mesures de taux d’érosion contemporains établies en fonction de photographies aériennes verticales prises en 1955, en 1979 et en 2002 sur un segment de 100 km du littoral de la mer de Beaufort. Entre 1955 et 2002, les taux d’érosion annuels ont atteint 5,6 m a-1 en moyenne. Cependant, les taux d’érosion moyens se sont accrus pour passer de 5,0 m a-1 pendant les années 1955- 1979 à 6,2 m a-1 dans les années 1979 - 2002. Par ailleurs, de la première période à la deuxième période, les taux d’érosion ont augmenté à 60 % (598) des 992 sites analysés, ont diminué dans le cas de 31 % (307) des sites, et changé de moins de ± 30 cm à 9 % (87) des sites. Les observations historiques et les études quantitatives recueillies au cours des 175 dernières années nous ont permis de placer nos mesures des taux d’érosion dans un contexte à plus long terme. Plusieurs des caractéristiques côtières le long de cette étendue du littoral ont reçu des noms d’endroits typiques de l’Ouest dans le cadre de l’expédition de Dease et Simpson en 1837, et la majorité de ces caractéristiques avaient disparu vers le début des années 1900 en raison de l’érosion côtière. Cela laisse donc entendre que l’érosion s’est à tout le moins manifestée pendant la période visée par les données historiques. Grâce à l’utilisation d’observations historiques et d’observations contemporaines, nous avons pu déceler la perte de sites culturels et historiques de même que d’infrastructures modernes. Les cartes topographiques de l’U.S. Geological Survey révèlent un certain nombre de sites culturels et historiques connus, ainsi que des sites dotés d’infrastructures modernes datant des années 1950, sites et infrastructures qui avaient disparu vers le début des années 2000 en raison de l’érosion côtière. Nous avons également été en mesure de cerner des sites qui sont présentement menacés par un littoral qui empiète sur le terrain. Nos mesures des taux d’érosion contemporains pourraient éventuellement servir à déterminer à quel moment un site historique ou une infrastructure moderne sera touché advenant que des taux d’érosion similaires persistent

Landsat-Based Trend Analysis of Lake Dynamics across Northern Permafrost Regions

Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here, we present a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM, ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (−0.69%), Western Alaska (−2.82%), and Kolyma Lowland (−0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e., upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region

Development of Light‐Activated LXR Agonists

Activation of the oxysterol-sensing transcription factor liver X receptor (LXR) has been studied as a therapeutic strategy in metabolic diseases and cancer but is compromised by the side effects of LXR agonists. Local LXR activation in cancer treatment may offer an opportunity to overcome this issue suggesting potential uses of photopharmacology. We report the computer-aided development of photoswitchable LXR agonists based on the T0901317 scaffold, which is a known LXR agonist. Azologization and structure-guided structure-activity relationship evaluation enabled the design of an LXR agonist, which activated LXR with low micromolar potency in its light-induced (Z)-state and was inactive as (E)-isomer. This tool sensitized human lung cancer cells to chemotherapeutic treatment in a light-dependent manner supporting potential of locally activated LXR agonists as adjuvant cancer treatment

Final Results From the Circumarctic Lakes Observation Network (CALON) Project

Since 2012, the physical and biogeochemical properties of ~60 lakes in northern Alaska have been investigated under CALON, a project to document landscape-scale variability of Arctic lakes in permafrost terrain. The network has ten nodes along two latitudinal transects extending inland 200 km from the Arctic Ocean. A meteorological station is deployed at each node and six representative lakes instrumented and continuously monitored, with winter and summer visits for synoptic assessment of lake conditions. Over the 4-year period, winter and summer climatology varied to create a rich range of lake responses over a short period. For example, winter 2012-13 was very cold with a thin snowpack producing thick ice across the region. Subsequent years had relatively warm winters, yet regionally variable snow resulted in differing gradients of ice thickness. Ice-out timing was unusually late in 2014 and unusually early in 2015. Lakes are typically well–mixed and largely isothermal, with minor thermal stratification occurring in deeper lakes during calm, sunny periods in summer. Lake water temperature records and morphometric data were used to estimate the ground thermal condition beneath 28 lakes. Application of a thermal equilibrium steady-state model suggests a talik penetrating the permafrost under many larger lakes, but lake geochemical data do not indicate a significant contribution of subpermafrost groundwater. Biogeochemical data reveal distinct spatial and seasonal variability in chlorophyll biomass, chromophoric dissolved organic carbon (CDOM), and major cations/anions. Generally, waters sampled beneath ice in April had distinctly higher concentrations of inorganic solutes and methane compared with August. Chlorophyll concentrations and CDOM absorption were higher in April, suggesting significant biological/biogeochemical activity under lake ice. Lakes are a positive source of methane in summer, and some also emit nitrous oxide and carbon dioxide. As part of the Indigenous Knowledge component,76 Iñupiat elders, hunters and berry pickers have been interviewed and over 75 hours of videotaped interviews produced. The video library and searchable interview logs are archived with the North Slope community. All field data is archived at ACADIS, and further information is at www.arcticlakes.org

Ice-rich permafrost thaw under sub-aquatic conditions

Degradation of sub-aquatic permafrost can release large quantities of methane into the atmosphere, impact offshore drilling activities, and affect coastal erosion. The degradation rate depends on the duration of inundation, warming rate, sediment characteristics, the coupling of the bottom to the atmosphere through bottom-fast ice, and brine injections into the sediment. The relative importance of these controls on the rate of sub-aquatic permafrost degradation, however, remains poorly understood. This poster presents a conceptual evaluation of sub-aquatic permafrost thaw mechanisms and an approach to their representation using one-dimensional modelling of heat and dissolved salt diffusion. We apply this model to permafrost degradation observed below Peatball Lake on the Alaska North Slope and compare modelling results to talik geometry information inferred from transient electromagnetic (TEM) soundings