TY - GEN
T1 - The Unforeseen Blackout and Cyber Risk Management for Business Continuity
T2 - 8th International Conference on Computational Methods in Systems and Software, CoMeSySo 2024
AU - Silvagni, Jack Caneva
AU - Norp, Oliver
AU - Rietze, Emma
AU - Šileris, Linas
AU - Barelds, Nick
AU - Hoffmans, Charlotte
AU - Treur, Jan
AU - Roelofsma, Peter H.M.P.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - This paper analyses a scenario describing a leading tech company that had to deal with an unforeseen blackout. This blackout caused a major disruption to electricity, internet services, telecommunication networks and water supply. The company’s cyber risk management for business continuity plans were tested in this multifaceted challenge. For the computational analysis, an adaptive temporal-causal network model was developed, addressing the scenario. This included adaptive elements such as connection weights and speed factors. The adaptive network model shows how disruptions and responses can unfold. A series of simulation experiments were conducted. These gave an insight into cause-and-effect relationships between different factors involved. A systematic What-If analysis was also provided to assess the impact that changing one factor may have on all other states in the system. All of these provided an enhanced understanding of the scenario and the interconnectedness between the factors involved.
AB - This paper analyses a scenario describing a leading tech company that had to deal with an unforeseen blackout. This blackout caused a major disruption to electricity, internet services, telecommunication networks and water supply. The company’s cyber risk management for business continuity plans were tested in this multifaceted challenge. For the computational analysis, an adaptive temporal-causal network model was developed, addressing the scenario. This included adaptive elements such as connection weights and speed factors. The adaptive network model shows how disruptions and responses can unfold. A series of simulation experiments were conducted. These gave an insight into cause-and-effect relationships between different factors involved. A systematic What-If analysis was also provided to assess the impact that changing one factor may have on all other states in the system. All of these provided an enhanced understanding of the scenario and the interconnectedness between the factors involved.
KW - adaptive network model
KW - Blackout
KW - business continuity
KW - cyber risk management
UR - https://www.scopus.com/pages/publications/105015295884
UR - https://www.scopus.com/inward/citedby.url?scp=105015295884&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-96798-6_28
DO - 10.1007/978-3-031-96798-6_28
M3 - Conference contribution
AN - SCOPUS:105015295884
SN - 9783031967979
T3 - Lecture Notes in Networks and Systems
SP - 352
EP - 375
BT - Artificial Intelligence for System Oriented Design - Proceedings of 8th Computational Methods in Systems and Software, 2024
A2 - Silhavy, Radek
A2 - Silhavy, Petr
PB - Springer Nature Switzerland AG
Y2 - 12 October 2024 through 14 October 2024
ER -