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Recent years have seen extensive adoption of domain generation algorithms (DGA) by modern botnets. The main goal is to generate a large number of domain names and then use a small subset for actual C&C communication. This makes DGAs very compelling for botmasters to harden the infrastructure of their botnets and make it resilient to blacklisting and attacks such as takedown efforts. While early DGAs were used as a backup communication mechanism, several new botnets use them as their primary communication method, making it extremely important to study DGAs in detail.
In this paper, we perform a comprehensive measurement study of the DGA landscape by analyzing 43 DGAbased malware families and variants. We also present a taxonomy for DGAs and use it to characterize and compare the properties of the studied families. By reimplementing the algorithms, we pre-compute all possible domains they generate, covering the majority of known and active DGAs. Then, we study the registration status of over 18 million DGA domains and show that corresponding malware families and related campaigns can be reliably identified by pre-computing future DGA domains. We also give insights into botmasters’ strategies regarding domain registration and identify several pitfalls in previous takedown efforts of DGA-based botnets. We will share the dataset for future research and will also provide a web service to check domains for potential DGA identity.
Helping Johnny to Analyze Malware: A Usability-Optimized Decompiler and Malware Analysis User Study
(2016)
Doubting - Path to Science
(2016)
The analysis of Δ9-tetrahydrocannabinol (THC) and its metabolites 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) from blood serum is a routine task in forensic toxicology laboratories. For examination of consumption habits, the concentration of the phase I metabolite THC-COOH is used. Recommendations for interpretation of analysis values in medical-psychological assessments (regranting of driver’s licenses, Germany) include threshold values for the free, unconjugated THC-COOH. Using a fully automated two-step liquid-liquid extraction, THC, 11-OH-THC, and free, unconjugated THC-COOH were extracted from blood serum, silylated with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and analyzed by GC/MS. The automation was carried out by an x-y-z sample robot equipped with modules for shaking, centrifugation, and solvent evaporation. This method was based on a previously developed manual sample preparation method. Validation guidelines of the Society of Toxicological and Forensic Chemistry (GTFCh) were fulfilled for both methods, at which the focus of this article is the automated one. Limits of detection and quantification for THC were 0.3 and 0.6 μg/L, for 11-OH-THC were 0.1 and 0.8 μg/L, and for THC-COOH were 0.3 and 1.1 μg/L, when extracting only 0.5 mL of blood serum. Therefore, the required limit of quantification for THC of 1 μg/L in driving under the influence of cannabis cases in Germany (and other countries) can be reached and the method can be employed in that context. Real and external control samples were analyzed, and a round robin test was passed successfully. To date, the method is employed in the Institute of Legal Medicine in Giessen, Germany, in daily routine. Automation helps in avoiding errors during sample preparation and reduces the workload of the laboratory personnel. Due to its flexibility, the analysis system can be employed for other liquid-liquid extractions as well. To the best of our knowledge, this is the first publication on a comprehensively automated classical liquid-liquid extraction workflow in the field of forensic toxicological analysis.
The development of advanced robotic systems is challenging as expertise from multiple domains needs to be integrated conceptually and technically. Model-driven engineering promises an efficient and flexible approach for developing robotics applications that copes with this challenge. Domain-specific modeling allows to describe robotics concerns with concepts and notations closer to the respective problem domain. This raises the level of abstraction and results in models that are easier to understand and validate. Furthermore, model-driven engineering allows to increase the level of automation, e.g. through code generation, and to bridge the gap between modeling and implementation. The anticipated results are improved efficiency and quality of the robotics systems engineering process. Within this contribution, we survey the available literature on domain-specific modeling and languages that target core robotics concerns. In total 137 publications were identified that comply with a set of defined criteria, which we consider essential for contributions in this field. With the presented survey, we provide an overview on the state-of-the-art of domain-specific modeling approaches in robotics. The surveyed publications are investigated from the perspective of users and developers of model-based approaches in robotics along a set of quantitative and qualitative research questions. The presented quantitative analysis clearly indicates the rising popularity of applying domain-specific modeling approaches to robotics in the academic community. Beyond this statistical analysis, we map the selected publications to a defined set of robotics subdomains and typical development phases in robotic systems engineering as reference for potential users. Furthermore, we analyze these contributions from a language engineering viewpoint and discuss aspects such as the methods and tools used for their implementation as well as their documentation status, platform integration, typical use cases and the evaluation strategies used for validation of the proposed approaches. Finally, we conclude with recommendations for discussion in the model-driven engineering and robotics community based on the insights gained in this survey.
The Fifth International Conference on Advances in Vehicular Systems, Technologies and Applications (VEHICULAR 2016), held between November 13-17, 2016 - Barcelona, Spain, continued the inaugural event considering the state-of-the-art technologies for information dissemination in vehicle-to-vehicle and vehicle-to-infrastructure and focusing on advances in vehicular systems, technologies and applications.
With the rising interest in vehicular communication systems many proposals for secure vehicle-to-vehicle commu- nication were made in recent years. Also, several standard- ization activities concerning the security and privacy measures in these communication systems were initiated in Europe and in US. Here, we discuss some limitations for secure vehicle- to-infrastructure communication in the existing standards of the European Telecommunications Standards Institute. Next, a vulnerability analysis for roadside stations on one side and security and privacy requirements for roadside stations on the other side are given. Afterwards, a proposal for a multi-domain public key architecture for intelligent transport systems, which considers the necessities of road infrastructure authorities and vehicle manufacturers, is introduced. The domains of the public key infrastructure are cryptographically linked based on local trust lists. In addition, a crypto agility concept is suggested, which takes adaptation of key length and cryptographic algorithms during PKI operation into account.
The design of future materials for biotechnological applications via deposition of molecules on surfaces will require not only exquisite control of the deposition procedure, but of equal importance will be our ability to predict the shapes and stability of individual molecules on various surfaces. Furthermore, one will need to be able to predict the structure patterns generated during the self-organization of whole layers of (bio)molecules on the surface. In this review, we present an overview over the current state of the art regarding the prediction and clarification of structures of biomolecules on surfaces using theoretical and computational methods.
Cognitive robotics aims at understanding biological processes, though it has also the potential to improve future robotics systems. Here we show how a biologically inspired model of motor control with neural fields can be augmented with additional components such that it is able to solve a basic robotics task, that of obstacle avoidance. While obstacle avoidance is a well researched area, the focus here is on the extensibility of a biologically inspired framework. This work demonstrates how easily the biological inspired system can be used to adapt to new tasks. This flexibility is thought to be a major hallmark of biological agents.
A deployment of the Vehicle-to-Vehicle communication technology according to ETSI is in preparation in Europe. Currently, a Public Key Infrastructure policy for Intelligent Transport Systems in Europe is in discussion to enable V2V communication. This policy set aside two classes of keys and certificates for ITS vehicle stations: long term authentication keys and pseudonymous keys and certificates. We show that from our point of view the periodic sent Cooperative Awareness Messages with extensive data have technical limitations and together with the pseudonym concept cause privacy problems.
We propose an artificial slime mould model (ASMM) inspired by the plasmodium of Physarum polucephalum (P. polucephalum). ASMM consists of plural slimes, and each slime shares energy via a tube with neighboring slimes. Outer slimes sense their environment and conform to it. Outer slimes periodically transmit information about their surrounding environment via a contraction wave to inner slimes. Thus, ASMM shows how slimes can sense a better environment even if that environment is not adjacent to the slimes. The slimes subsequently can move in the direction of an attractant.
The work at hand outlines a recording setup for capturing hand and finger movements of musicians. The focus is on a series of baseline experiments on the detectability of coloured markers under different lighting conditions. With the goal of capturing and recording hand and finger movements of musicians in mind, requirements for such a system and existing approaches are analysed and compared. The results of the experiments and the analysis of related work show that the envisioned setup is suited for the expected scenario.
Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.
SDN and WMN evolved to be sophisticated technologies used in a variety of applications. However, a combined approach called wmSDN has not been widely addressed in the research community. Our idea in this field consists of WiFi-based point-to-point links managed by the OpenFlow protocol. We investigate two different issues regarding this idea. First, which WiFi operational mode is suitable in an OpenFlow managed broadcast domain? Second, does the performance decrease compared with other routing or switching principles? Therefore, we set up a real-world testbed and a suitable simulation environment. Unlike previous work, we show that it is possible to use WiFi links without conducting MAC address rewriting at each hop by utilizing the 4-address-mode.
We demonstrated previously that phosphocholine and phosphocholine-modified macromolecules efficiently inhibit ATP-dependent release of interleukin-1β from human and murine monocytes by a mechanism involving nicotinic acetylcholine receptors (nAChR). Interleukin-1β is a potent pro-inflammatory cytokine of innate immunity that plays pivotal roles in host defence. Control of interleukin-1β release is vital as excessively high systemic levels cause life threatening inflammatory diseases. In spite of its structural similarity to acetylcholine, there are no other reports on interactions of phosphocholine with nAChR. In this study, we demonstrate that phosphocholine inhibits ion-channel function of ATP receptor P2X7 in monocytic cells via nAChR containing α9 and α10 subunits. In stark contrast to choline, phosphocholine does not evoke ion current responses in Xenopus laevis oocytes, which heterologously express functional homomeric nAChR composed of α9 subunits or heteromeric receptors containing α9 and α10 subunits. Preincubation of these oocytes with phosphocholine, however, attenuated choline-induced ion current changes, suggesting that phosphocholine may act as a silent agonist. We conclude that phophocholine activates immuno-modulatory nAChR expressed by monocytes but does not stimulate canonical ionotropic receptor functions.
Hydrogen sulfide (H2S) is a well-known environmental chemical threat with an unpleasant smell of rotten eggs. Aside from the established toxic effects of high-dose H2S, research over the past decade revealed that cells endogenously produce small amounts of H2S with physiological functions. H2S has therefore been classified as a gasotransmitter. A major challenge for cells and tissues is the maintenance of low physiological concentrations of H2S in order to prevent potential toxicity. Epithelia of the respiratory and gastrointestinal tract are especially faced with this problem, since these barriers are predominantly exposed to exogenous H2S from environmental sources or sulfur-metabolising microbiota. In this paper, we review the cellular mechanisms by which epithelial cells maintain physiological, endogenous H2S concentrations. Furthermore, we suggest a concept by which epithelia use their electrolyte and liquid transport machinery as defence mechanisms in order to eliminate exogenous sources for potentially harmful H2S concentrations.
Hydrogen sulfide contributes to hypoxic inhibition of airway transepithelial sodium absorption
(2016)
An exploratory study: Analysis of Serbian tourism market and identification of major market segments
(2016)
The Participation Act, introduced in the Netherlands in 2015, puts into practice the idea that every individual has to make a contribution in a participatory society. The Act includes aspects of income support, compulsory activities in return for benefits, and labour market reintegration. Drawing on 45 interviews, we provide insights into interactions between the individual financial and social situation, an individual’s position in society, and reintegration activities. The narratives show the fundamental need for individual freedom and societal meaning, recognition, and appreciation, as well as the complex circumstances in which social assistance recipients make decisions. Conflicts between those needs and the Act lead to the question of how personal and societal objectives can be reconciled.
The mechanical properties of plastic components, especially if they are made of semi-crystalline polymers, are considerably influenced by the process conditions. The degree of crystallization influences thermal and mechanical properties. Even more important is the orientation of molecules due to stretching of the polymer melt. Anisotropic material properties are the result of such orientations. Up to now all these effects are not considered within the simulation models of blow molded parts.
Large sections of the German society are able to buy and consume meat on a daily basis due to progress in the agri-food sector. However, the way meat is produced, traded and consumed increasingly has become an issue that is controversially discussed by the media, non-governmental organisations (NGOs), lobbyists, the industry itself and consumers – often with a negative connotation. The meat industry reacts to this. By creating information campaigns and animal welfare initiatives it aims to stress that it is going to take its corporate social responsibilities (CSR) for consumers and animal welfare seriously. But, the industry’s actions are still criticised as being not sufficient to improve animal welfare levels significantly. Much of this criticism can be observed in online news portals, where articles about the issue get published and commented by readers. This makes online portals a valuable source for information that is to be tapped in this study. It aims to better understand the multifaceted discussions concerning animal welfare initiatives in online portals. By applying qualitative content analysis and web mining techniques to a sample of documents taken from three major German news sites it can be shown that online discussions refer to various aspects of sustainability and corporate social responsibility. Findings also indicate that the discussions are framed by financial aspects.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data. Hence the generation of robust reviewed global irradiance data is an essential contribution for the energy transition.
The Eighth International Conference on Future Computational Technologies and Applications (FUTURE COMPUTING 2016), held between March 20-24, 2016 in Rome, Italy, continued a series of events targeting advanced computational paradigms and their applications. The target was to cover (i) the advanced research on computational techniques that apply the newest human-like decisions, and (ii) applications on various domains. The new development led to special computational facets on mechanism-oriented computing, large-scale computing and technology-oriented computing. They are largely expected to play an important role in cloud systems, on-demand services, autonomic systems, and pervasive applications and services.