Monday 3pm to 4pm
but not on July 8 and July 29, 2019
from August 5 on: Monday 12.30pm to 1.30pm
Prof. Dr.-Ing. Franz J. Hauck
Prof. Hauck studied computer science at the University of Erlangen-Nürnberg. After two years in industry he earnt his dissertation and habilitation also from the University of Erlangen-Nürnberg interrupted by a one year stay at the Vrije Universiteit Amsterdam. Since 2002 he is teaching and doing research at the Ulm University as a professor for distributed systems at the institute with same name.
His research interests are special-purpose middleware systems with focus on fault-tolerant server systems, but currently also on resource management of soft real-time systems, privacy-preserving communication, and mobile crowd sensing. Current projects are OptSCORE, PriCloud and ESIT.
Prof. Hauck is a member of the ACM, the German Computer Society, GI and of its special interest groups on Operating Systems, Communication and Distributed Systems (KuVS), and Fault-tolerant Computer Systems (FERS).
He is also an elected member of the Faculty Council of his Faculty, appointed member and head of the Doctoral Committee for Dr. rer. nat., and appointed member of the Joint Comission for Teacher Education. As such he is also member of the Academic Affairs Commission, the Examination Board and the Admission Committee for teacher education programmes. Besides, he is elected chairman of the Examination Board.
His three most recent publications:
Resource-Efficient State-Machine Replication with Multithreading and Vertical Scaling
Proc. of the 14th Eur. Dep. Comp. Conf. (EDCC)
Abstract: State-machine replication (SMR) enables transparent and delayless masking of node faults. It can tolerate crash faults and malicious misbehavior, but usually comes with high resource costs, not only by requiring multiple active replicas, but also by providing the replicas with enough resources for the expected peak load. This paper presents a vertical resource-scaling solution for SMR systems in virtualized environments, which can dynamically adapt the number of available cores to current load. In similar approaches, benefits of CPU core scaling are usually small due to the inherent sequential execution of SMR systems in order to achieve determinism. In our approach, we utilize sophisticated deterministic multithreading to avoid this bottleneck and experimentally demonstrate that core scaling then allows SMR systems to effectively tailor resources to service load, dramatically reducing service provider costs.
A Flexible Network Approach to Privacy of Blockchain Transactions
Proc. of the 38th IEEE Int. Conf. on Distrib. Comp. Sys. (ICDCS) , page 1486-1491.
Abstract: For preserving privacy, blockchains can be equipped with dedicated mechanisms to anonymize participants. How- ever, these mechanism often take only the abstraction layer of blockchains into account whereas observations of the underlying network traffic can reveal the originator of a transaction request. Previous solutions either provide topological privacy that can be broken by attackers controlling a large number of nodes, or offer strong and cryptographic privacy but are inefficient up to practical unusability. Further, there is no flexible way to trade privacy against efficiency to adjust to practical needs. We propose a novel approach that combines existing mechanisms to have quantifiable and adjustable cryptographic privacy which is further improved by augmented statistical measures that prevent frequent attacks with lower resources. This approach achieves flexibility for privacy and efficency requirements of different blockchain use cases.
Towards Enhanced Network Privacy for Blockchains
Short research statement for the DSN Workshop on Byzantine Consensus and Resilient Blockchains (BCRB)
Abstract: Privacy aspects of blockchains have gained attention as the log of transactions can be view by any interested party. Privacy mechanisms applied to the ledger can be undermined by attackers on the network level, resulting in deanonymization of the transaction senders. We discuss current approaches to this problem, e.g. Dandelion, sketch our own approach to provide even stronger privacy mechanisms and discuss the challenges and open questions for further research in this area.
A complete list of publications as well as further details to projects, Ph.D. students and given classes can be found on a details page.