Reference : A Privacy Preserving Approach to Collaborative Systemic Risk Identification : the Use...
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/44530
A Privacy Preserving Approach to Collaborative Systemic Risk Identification : the Use-case of Supply Chain Network
English
Garizy, Tirazheh Zare [> >]
Fridgen, Gilbert mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Wederhake, Lars [> >]
2018
Security and Communication Networks
Yes
[en] Multiparty Computation; Algorithms; Privacy Preservation; Supply Chain Network; Systemic Risk; Risk Management
[en] Globalization, and outsourcing are two main factors which are leading to higher complexity of supply chain networks.
Due to the strategic importance of having a sustainable network it is necessary to have an enhanced supply chain
network risk management. In a supply chain network many firms depend directly or indirectly on a specific supplier.
In this regard, unknown risks of network’s structure can endanger the whole supply chain network’s robustness. In
spite of the importance of risk identification of supply chain network, firms are not willing to exchange the structural information of their network. Firms are concerned about risking their strategic positioning or established connections in the network. The paper proposes to combine secure multiparty computation cryptography methods with risk
identification algorithms from social network analysis to address this challenge. The combination enables structural
risk identification of supply chain networks without endangering firms’ competitive advantage.
http://hdl.handle.net/10993/44530
https://eref.uni-bayreuth.de/45140/

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