Biblio

Today’s Supply Chains (SC) are engulfed in a maelstrom of risks which arise mainly from uncertain, contradictory, and incomplete information. A decision-making process is required in order to detect threats, assess risks, and implements mitigation methods to address these issues. However, Neutrosophic Data Analytic Hierarchy Process (NDAHP) allows for a more realistic reflection of real-world problems while taking into account all factors that lead to effective risk assessment for Multi Criteria Decision-Making (MCDM). The purpose of this paper consists of an implementation of the NDAHP for MCDM aiming to identifying, ranking, prioritizing and analyzing risks without considering SC’ expert opinions. To that end, we proceed, first, for selecting and analyzing the most 23 relevant risk indicators that have a significant impact on the SC considering three criteria: severity, occurrence, and detection. After that, the NDAHP method is implemented and showcased, on the selected risk indicators, throw an illustrative example. Finally, we discuss the usability and effectiveness of the suggested method for the SCRM purposes.

Logistics risk assessment in the supply chain is considered as one of the important topics that has attracted the attention of researchers in recent years; Companies that struggle to manage their logistical risks by not putting in place resilient strategies to mitigate them, may suffer from significant financial losses; The automotive industry is a vital sector for the Moroccan economy, the year 2020, the added-value of the automotive industry in Morocco is higher than that of the fertilizer (Fathi, n.d.) [1], This sector is considered the first exporter of the country. Our study will focuses on the assessment of the pure logistical risks in the moroccan automotive industry. Our main objective for this study is to assess the logistical risks which will allow us to put in place proactive and predictive resilient strategies for their mitigation.

Critical infrastructure is a key area in cybersecurity. In the U.S., it was front and center in 1997 with the report from the President’s Commission on Critical Infrastructure Protection (PCCIP), and now affects countries worldwide. Critical Infrastructure Protection must address all types of cybersecurity threats - insider threat, ransomware, supply chain risk management issues, and so on. Unsurprisingly, in the past 25 years, the risks and incidents have increased rather than decreased and appear in the news daily. As an important component of critical infrastructure protection, secure supply chain risk management must be integrated into development projects. Both areas have important implications for security requirements engineering.

This paper establishes a novel approach to supply chain risk management (SCRM), through establishing a risk assessment framework addressing the importance of SCRM and supply chain visibility (SCV). Through a quantitative assessment and empirical evidence, the paper also discusses the specific risks within the manufacturing industry. Based on survey data collected and a case study from Asia, the paper finds that supplier delays and poor product quality can be considered as prevailing risks relevant to the manufacturing industry. However, as supply chain risks are inter-related, one must increase supply chain visibility to fully consider risk causes that ultimately lead to the risk effects. The framework established can be applied to different industries with the view to inform organisations on prevailing risks and prompt motivate improvement in supply chain visibility, thereby, modify risk management strategies. Through suggesting possible risk sources, organisations can adopt proactive risk mitigation strategies so as to more efficiently manage their exposure.

In this presentation, I describe how the SEI's Security Engineering Risk Analysis (SERA) method provides a structure that connects desired system functionality with the underlying software to evaluate the sufficiency of requirements for software security and the potential operational security risks based on mission impact.