Article (Scientific journals)
A Privacy Preserving Approach to Collaborative Systemic Risk Identification : the Use-case of Supply Chain Network
Garizy, Tirazheh Zare; Fridgen, Gilbert; Wederhake, Lars
2018In Security and Communication Networks
Peer reviewed
 

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Keywords :
Multiparty Computation; Algorithms; Privacy Preservation; Supply Chain Network; Systemic Risk; Risk Management
Abstract :
[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.
Disciplines :
Computer science
Author, co-author :
Garizy, Tirazheh Zare
Fridgen, Gilbert  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Wederhake, Lars
External co-authors :
yes
Language :
English
Title :
A Privacy Preserving Approach to Collaborative Systemic Risk Identification : the Use-case of Supply Chain Network
Publication date :
2018
Journal title :
Security and Communication Networks
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 22 October 2020

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