Advancing the Security of LDACS

The "Single European Sky" air traffic management master plan foresees the introduction of several modern digital data links for aeronautical communications. The candidate for long-range continental communications is the L-band Digital Aeronautical Communications System (LDACS). LDACS is a cellular, ground-based digital communications system for flight guidance and communications related to safety and regularity of flight. Hence, the aeronautical standards, imposed by the International Civil Aviation Organization (ICAO), for cybersecurity of the link and network layer, apply. In previous works, threat-and risk analyses of LDACS were conducted, a draft for an LDACS cybersecurity architecture introduced, algorithms proposed, and the security of a Mutual Authentication and Key Establishment (MAKE) procedure of LDACS formally verified. However, options for cipher-suites and certificate management for LDACS were missing. Also, previous works hardly discussed the topic of post-quantum security for LDACS. This paper proposes a cell-attachment procedure, which establishes a secure LDACS communication channel between an aircraft and corresponding ground-station upon cell-entry of the aircraft. Via the design of a hybrid LDACS Public Key Infrastructure (PKI), the choice of a pre-or post-quantum Security Level (SL) is up to the communications participants. With that, this work introduces a full LDACS cell-attachment protocol based on a PKI, certificates, certificate revocation and cipher-suites including pre-and post-quantum options. Evaluations in the symbolic model show the procedure to fulfill LDACS security requirements and a communications performance evaluation demonstrates feasibility, matching requirements imposed by regulatory documents

Holocnemus pluchei (Araneae, Pholcidae) in beverage stores and do-it-yourself stores in Germany

Einige Vorkommen der mediterranen Zitterspinnenart Holocnemus pluchei (Scopoli, 1763) wurden in Deutschland in Getränkemärkten und Baumärkten gefunden. Neu nachgewiesen wurde die Art für Berlin, Hamburg, Niedersachsen und Mecklenburg-Vorpommern.Some colonies of spiders belonging to the Mediterranean cellar spider Holocnemus pluchei (Scopoli, 1763), were found in both beverage and do-it-yourself stores in Germany. Among these are the first records of H. pluchei in Berlin, Hamburg, Lower Saxony and Mecklenburg-Western Pomerania

Holocnemus pluchei (Araneae, Pholcidae) in Getr\ue4nke- und Baum\ue4rkten in Deutschland

Volume: 48Start Page: 24End Page: 2

Neunachweis der exotischen Speispinne Scytodes fusca (Araneae, Scytodidae) in Mitteleuropa aus Deutschland und der Slowakei

The spitting spider Scytodes fusca Walckenaer, 1837 is recorded for the first time in Central Europe from both Germany and Slovakia. The species was found in two localities, within the Botanical Garden in Bratislava (Slovakia), specifically from a heated greenhouse with high humidity, and the "Tropical Islands", a tropical holiday resort in Krausnick (Germany). It seems that this Pantropical species has probably been introduced here along with imported plants. A description of diagnostic characters, as well as figures, is given.Die Speispinne Scytodes fusca Walckenaer, 1837 konnte erstmals für Mitteleuropa in Deutschland und der Slowakei nachgewiesen werden. Die Funde stammen aus dem Botanischen Garten in Bratislava (Slowakei) sowie aus dem Freizeitbad "Tropical Islands" in Krausnick (Deutschland). Es wird vermutet, dass die pantropische Art durch Zierpflanzen eingeschleppt wurde. Die charakteristischen Merkmale der Art werden beschrieben und abgebildet

Back in Europe: Quamtana spiders (Araneae: Pholcidae) in Germany

Volume: 50Start Page: 51End Page: 5

Fruit Volume and Leaf-Area Determination of Cabbage by a Neural-Network-Based Instance Segmentation for Different Growth Stages

Fruit volume and leaf area are important indicators to draw conclusions about the growth condition of the plant. However, the current methods of manual measuring morphological plant properties, such as fruit volume and leaf area, are time consuming and mainly destructive. In this research, an image-based approach for the non-destructive determination of fruit volume and for the total leaf area over three growth stages for cabbage (brassica oleracea) is presented. For this purpose, a mask-region-based convolutional neural network (Mask R-CNN) based on a Resnet-101 backbone was trained to segment the cabbage fruit from the leaves and assign it to the corresponding plant. Combining the segmentation results with depth information through a structure-from-motion approach, the leaf length of single leaves, as well as the fruit volume of individual plants, can be calculated. The results indicated that even with a single RGB camera, the developed methods provided a mean accuracy of fruit volume of 87% and a mean accuracy of total leaf area of 90.9%, over three growth stages on an individual plant level

Steatoda nobilis, a false widow on the rise: a synthesis of past and current distribution trends

The Noble False Widow, Steatoda nobilis (Thorell, 1875) (Araneae, Theridiidae), is, due to its relatively large size and potential medical importance, one of the most notable invasive spider species worldwide. Probably originating from the Canary Islands and Madeira, the species is well established in Western Europe and large parts of the Mediterranean area and has spread recently into California and South America, while Central European populations were not known until 2011. We report on long-time observations that reveal that at least two flourishing populations in Germany (Cologne) have been present for over five years, while in Ecuador one population has been observed between 2014 and 2018 and several other records were made in other parts of the country. Data obtained from the British Spider Recording Scheme demonstrate that the species moved significantly northwards since the report of the first populations in the very South of England, after several decades of relative stasis. The sudden northward expansion highly correlates with a massive rise in press coverage of the species. In the Americas, S. nobilis is currently known from four countries (USA, Chile, Ecuador, Colombia), and available DNA barcoding data obtained for specimens from this area suggest that multiple introductions occurred within each country. Using ecological niche modeling, we identified suitable climate regions for the species and discuss possible reasons for its current spread. We propose that seaside cities and villages with a temperate oceanic or Mediterranean climate are especially favourable potential habitats for S. nobilis and will face the highest colonization pressure in the future, while tropical upland regions with temperate climates are also vulnerable to invasion by S. nobilis

Unsupervised image-to-image translation to reduce the annotation effort for instance segmentation of field vegetables

Due to the constantly increasing shortage of labour availability in the agricultural sector, automation is on the rise. This trend is particularly evident in field vegetable production, where the majority of costs are associated with human labour. To automate labour-intensive tasks, intelligent camera systems are required. Typical state of the art learning algorithms requires large amounts of labelled data for a reliable detection and segmentation. The effort for recording and labelling is increased by the diverse conditions on a field that need to be included in the datasets. In this paper, an unsupervised approach is presented, which unifies varying environmental conditions in the field, as well as an analysis to transfer this unpaired deep learning based unification to unknown exposure scenarios, different growth stages and other varieties. For this purpose, a Cycle-Consistent Adversarial Network (CycleGAN) is used which balance varying exposure and background situations to the training data variance without additional labelling effort. By adapting the exposure with a CycleGAN, the required labelling effort could be reduced by up to five times in relation to a heterogeneous dataset, as fewer variations need to be covered for a robust segmentation. The transfer of this approach to other growth stages, as well as the transfer to another cabbage cultivar shows the potential of additional data generalisation