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pro vyhledávání: '"Neumann, Christoph P."'
Autor:
Stangl, Philipp, Neumann, Christoph P.
Current methods to prevent crypto asset fraud are based on the analysis of transaction graphs within blockchain networks. While effective for identifying transaction patterns indicative of fraud, it does not capture the semantics of transactions and
Externí odkaz:
http://arxiv.org/abs/2405.19762
Autor:
Levi, Patrick, Neumann, Christoph P.
Publikováno v:
Proc of the 15th International Conference on Cloud Computing, GRIDs, and Virtualization (Cloud Computing 2024), Venice, Italy, April 2024, pp. 19-24, ISSN 2308-4294
The fast advancements in Large Language Models (LLMs) are driving an increasing number of applications. Together with the growing number of users, we also see an increasing number of attackers who try to outsmart these systems. They want the model to
Externí odkaz:
http://arxiv.org/abs/2404.02637
Autor:
Bauer, Tobias, Beer, Fabian, Holl, Daniel, Imeraj, Ardian, Schweiger, Konrad, Stangl, Philipp, Weigl, Wolfgang, Neumann, Christoph P.
Reddiment is a web-based dashboard that links sentiment analysis of subreddit texts with share prices. The system consists of a backend, frontend and various services. The backend, in Node.js, manages the data and communicates with crawlers that coll
Externí odkaz:
http://arxiv.org/abs/2312.05289
Inadequate availability of patient information is a major cause for medical errors and affects costs in healthcare. Traditional approaches to information integration in healthcare do not solve the problem. Applying a document-oriented paradigm to sys
Externí odkaz:
http://arxiv.org/abs/2311.14349
Autor:
Stangl, Philipp, Neumann, Christoph P.
Publikováno v:
Proc of the 14th International Conference on Cloud Computing, GRIDs, and Virtualization (Cloud Computing 2023), Nice, France, June 2023, pp. 41-46, ISSN 2308-4294
We consider the problem of supply chain data visibility in a blockchain-enabled supply chain network. Existing methods typically record transactions happening in a supply chain on a single blockchain and are limited in their ability to deal with diff
Externí odkaz:
http://arxiv.org/abs/2310.19461
Publikováno v:
Proc of the 14th International Conference on Cloud Computing, GRIDs, and Virtualization (Cloud Computing 2023), Nice, France, June 2023, pp. 21-29, ISSN 2308-4294
Security challenges for Cloud or Fog-based machine learning services pose several concerns. Securing the underlying Cloud or Fog services is essential, as successful attacks against these services, on which machine learning applications rely, can lea
Externí odkaz:
http://arxiv.org/abs/2310.19459
Autor:
Suárez-Varela, José, Ferriol-Galmés, Miquel, López, Albert, Almasan, Paul, Bernárdez, Guillermo, Pujol-Perich, David, Rusek, Krzysztof, Bonniot, Loïck, Neumann, Christoph, Schnitzler, François, Taïani, François, Happ, Martin, Maier, Christian, Du, Jia Lei, Herlich, Matthias, Dorfinger, Peter, Hainke, Nick Vincent, Venz, Stefan, Wegener, Johannes, Wissing, Henrike, Wu, Bo, Xiao, Shihan, Barlet-Ros, Pere, Cabellos-Aparicio, Albert
Publikováno v:
ACM SIGCOMM Computer Communication Review, Vol. 51, No. 3, pp. 9-16, 2021
During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This pos
Externí odkaz:
http://arxiv.org/abs/2107.12433
Diagnosing problems in Internet-scale services remains particularly difficult and costly for both content providers and ISPs. Because the Internet is decentralized, the cause of such problems might lie anywhere between an end-user's device and the se
Externí odkaz:
http://arxiv.org/abs/2004.03343
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Byzantine-Fault-Tolerant (BFT) systems are rapidly emerging as a viable technology for production-grade systems, notably in closed consortia deployments for nancial and supply-chain applications. Unfortunately, most algorithms proposed so far to coor
Externí odkaz:
http://arxiv.org/abs/1911.03291