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Danielle Blanche Kapsa Selambi


Taught Masters, 2020/2021

The Covid-19 pandemic has forced several changes in the world of work, leading companies and institutions to accelerate digital transformation by embracing remote working. The new approach of work has made cybersecurity one of the biggest challenges facing society today, attracting the attention of researchers and insurers. Danielle’s work has been to estimate the cost of a data breach using the number of records compromised, the number of such records being predicted using a machine learning model. She analyzed the “fat tail” phenomenon, which is the underlying dynamic of the number of affected records, with the aim of calculating the maximum loss, to answer the question of the insurability of the risk. Her results showed that the total number of affected records follows a Fréchet distribution. These results make it possible to anticipate the determination of premiums for cyber-risk coverage in the insurance field.

Danielle is currently a junior cybersecurity expert at Ai4sense Argenteuil, France.

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