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Marcel von Maltitz

dblp:159/2433 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2019
0000-0002-0680-0434ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 3 · 3 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 100%
Network and information security
1 paper
Cryptographic protocols and secure computation · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › iot security and privacy
iot privacy
0.312018
Leveraging Secure Multiparty Computation in the Internet of Things · MobiSys 2018
Cryptographic protocols and secure computation
secure multiparty computation
0.112018
Leveraging Secure Multiparty Computation in the Internet of Things · MobiSys 2018

Methods — techniques the papers use, named apart from their topics

secure multiparty computation · 0.7
YearPublicationVenuePosition
2019 Data Querying and Access Control for Secure Multiparty Computation
Marcel von Maltitz, Georg Carle
IM1
2018 Leveraging Secure Multiparty Computation in the Internet of Things
abstract
Centralized systems in the Internet of Things---be it local middleware or cloud-based services---fail to fundamentally address privacy of the collected data. We propose an architecture featuring secure multiparty computation at its core in order to realize data processing systems which already incorporate support for privacy protection in the architecture.
Marcel von Maltitz, Georg Carle
MobiSys1
2018 A management framework for secure multiparty computation in dynamic environments
abstract
Secure multiparty computation (SMC) is a promising technology for privacy-preserving collaborative computation. In the last years several feasibility studies have shown its practical applicability in different fields. However, it is recognized that administration, and management overhead of SMC solutions are still a problem. A vital next step is the incorporation of SMC in the emerging fields of the Internet of Things and (smart) dynamic environments. In these settings, the properties of these contexts make utilization of SMC even more challenging since some vital premises for its application regarding environmental stability and preliminary configuration are not initially fulfilled. We bridge this gap by providing FlexSMC, a management and orchestration framework for SMC which supports the discovery of nodes, supports a trust establishment between them and realizes robustness of SMC session by handling nodes failures and communication interruptions. The practical evaluation of FlexSMC shows that it enables the application of SMC in dynamic environments with reasonable performance penalties and computation durations allowing soft real-time and interactive use cases.
Marcel von Maltitz, Stefan Smarzly, Holger Kinkelin, Georg Carle
NOMS1
2017 Privacy Assessment Using Static Taint Analysis (Tool Paper)
Marcel von Maltitz, Cornelius Diekmann, Georg Carle
FORTE1