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Institute
Decentralizing Smart Energy Markets - tamper-proof-documentation of flexibility market processes
(2020)
The evolving granularity and structural decentralization of the energy system leads to a need for new tools for the efficient operation of electricity grids. Local Flexibility Markets (or "Smart Markets") provide platform concepts for market based congestion management. In this context there is a distinct need for a secure, reliable and tamper-resistant market design which requires transparent and independent monitoring of platform operation. Within the following paper different concepts for blockchain-based documentation of relevant processes on the proposed market platform are described. On this basis potential technical realizations are discussed. Finally, the implementation of one setup using Merkle tree operations is presented by using open source libraries.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using
static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
After creating a new blockchain transaction, the next step usually is to make miners aware of it by having it propagated through the blockchain’s peer-to-peer network. We study an unintended alternative to peer-to-peer propagation: Exclusive mining. Exclusive mining is a type of collusion between a transaction initiator and a single miner (or mining pool). The initiator sends transactions through a private channel directly to the miner instead of propagating them through the peerto-peer network. Other blockchain users only become aware of these transactions once they have been included in a block by the miner. We identify three possible motivations for engaging in exclusive mining: (i) reducing transaction cost volatility (“confirmation as a service”), (ii) hiding unconfirmed transactions from the network to prevent frontrunning and (iii) camouflaging wealth transfers as transaction costs to evade taxes or launder money. We further outline why exclusive mining is difficult to prevent and introduce metrics which can be used to identify mining pools engaging in exclusive mining activity.
We present dimensionality reduction methods like autoencoders and t-SNE for visualization of high-dimensional data into a two-dimensional map. In this thesis, we initially implement basic and deep autoencoders using breast cancer and mushroom datasets. Next, we build another dimensionality reduction method t-SNE using the same datasets. The obtained visualization results of the datasets using the dimensionality reduction methods are documented in the experiments section of the thesis. The evaluation of classification and clustering for the dimensionality reduction techniques is also performed. The visualization and evaluation results of t-SNE are significantly better than the other dimensionality reduction techniques.
Both cryptocurrency researchers and early adopters of cryptocurrencies agree that they possess a special kind of materiality, based on the laborious productive process of digital ‘mining’ [1]. This idea first appears in the Bitcoin White Paper [2] that encourages Bitcoin adopters to construct and justify its value in metaphoric comparison to gold mining. In
this paper, I explore three material aspects of blockchain: physical infrastructure, human language and computer code. I apply the concept of 'continuous materiality' [3] to show how these three aspects interact in practical implementations of blockchain such as Bitcoin and Ethereum. I start from the concept of ‘digital metallism’ that stands for ‘fundamental value’ of cryptocurrencies, and end with the move of Ethereum to ‘proof-of-stake’, partially as a countermeasure against ‘evil miners’. I conclude that ignoring material aspects of blockchain technology can only further problematize complicated relations between their technical, semiotic and social materiality.
Glycans play an important role in the intracellular interactions of pathogenic bacteria. Pathogenic bacteria possess binding proteins capable of recognizing certain sugar motifs on other cells, which are found in glycan structures. Artificial carbohydrate synthesis allows scientists to recreate those sugar motifs in a rational, precise, and pure form. However, due to the high specificity of sugar-binding proteins, known as lectins, to glycan structures, methods for identifying suitable binding agents need to be developed. To tackle this hurdle, the Fraunhofer Institute for Cell Therapy and Immunology (Fraunhofer IZI) and the Max-Planck Institute of Colloids and Interfaces (MPIKG) developed a binding assay for the high throughput testing of sugar motifs that are presented on modular scaffolds formed by the assembly of four DNA strands into simple, branched DNA nanostructures. The first generation of this assay was used in combination with bacteria that express a fluorescent protein as a proof-of-concept. Here, the assay was optimized to be used with bacteria not possessing a marker gene for a fluorescent protein by staining their genomic DNA with SYBR® Green. For the binding assay, DNA nanostructures were combined with artificially synthesized mannose polymers, typical targets for many lectins on the surface of bacteria, presenting them in a defined constellation to bind bacteria strongly due to multivalent cooperativity. The testing of multiple mannose polymers identified monomeric mannose with a 5’-carbon linker and 1,2-linked dimeric mannose with linker as the best binding candidates for E. coli, presumably due to binding with the FimH protein on the surface. Despite similarities between the FimH proteins of E. coli and K. pneumoniae, binding was only observed between E. coli and the different sugar molecules on DNA structures. Furthermore, the degree of free movement seemed to affect the binding of mannose polymers to targeted proteins, since when utilizing a more flexible DNA nanostructure, an increase in binding could be observed. An alternative to the simple DNA nanostructures described above is the use of larger, more complex DNA origami structures consisting of several hundred strands. DNA origami structures are capable of carrying dozens of modifications at the same time. The results for the DNA origami structure showed a successful functionalization with up to 71 1,2-linked dimeric mannose with linker molecules. These results point towards a solution for the high-throughput analysis of potential binding agents for pathogenic bacteria e.g. as an alternative treatment for antibiotic-resistant.
In this work a second version for the Python implementation of an algorithm called Probabilistic Regulation of Metabolism (PROM) was created and applied to the metabolic model iSynCJ816 for the organism Synechocystis sp. PCC 6803. A crossvalidation was performed to determine the minimal amount of expression data needed to produce meaningful results with the PROM algorithm. The failed reproduction of the results of a method called Integrated and Deduced Regulation of Metabolism (IDREAM) is documented and causes for the failed reproduction are discussed.
The Infinica product suite consists of multiple individual microservice applications, mainly gathered around Infinica Process Engine which allows the execution of highly individualised process definitions. For estimating process performance, a layered queuing network approach has been applied. In the first step this required the implementation of a basic modelling framework. Subsequently the implemented framework was used to evaluate the applicability of the approach by creating two models and comparing them with actual performance measurements. Although the calculated results deviated from the expected results, analysis showed that the differences may
derive from an inaccurate model. Nevertheless the general approach seems to be appropriate for the given application as well as for microservices in general, especially when extended with advanced modelling techniques, as the analysed modelled results appear consistent.
In an era of global climate change and fast growing cities, local governments are in an urgent need for adopting sustainable urban growth concepts for tackling a liveable and prosperous urban future. Against this background, the smart city notion progressively gained popularity as an urban development concept, which heavily relies on technology and urban data use for fostering sustainable urban growth. However, so far, the understandingof the smart city term is ambiguous, and little scientific research has been done on developing comprehensive conceptual frameworks to support local governments in the making of smarter cities. This paper aims at presenting the current state-of-the-art of smart city research in order to support the making of smart city best practices and to promote a comprehensive understanding of the smart city notion. In doing so, the role of technology in the making of smarter cities and critical success factors in transforming cities are elaborated, following the methodological approach of a multidimensional conceptual framework. The research findings and an expert interview with a representative of the state capital will then serve for the assessment of the weak points and best practices in the smart city pursuit of the German city Munich, providing urban policymaking with valuable insights and fostering the development of a comprehensive smart city conceptualism.
This thesis deals with the development of a methodology / concept to analyse targeted attacks against IIoT / IoT devices. Building on the established background knowledge about honeypots, fileless malware and injection techniques a methodology is created that leads to a concept of a honeypot analyzation system. The system is created to analyse and detect novel threats like fileless attacks which are often utilized by Advanced Persistent Threats. That system is partially implemented and later evaluated by performing a simulated attack utilizing fileless attacks. The effectiveness is discussed and rated based on the results.