Institutsseminar/2021-04-09

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Version vom 22. März 2021, 11:39 Uhr von Daniel Milbaier (Diskussion | Beiträge) (Die Seite wurde neu angelegt: „{{Termin |datum=2021/04/09 14:00:00 |raum=https://conf.dfn.de/webapp/conference/979160755 }} The rapid growth of renewable energy sources and the increased sal…“)
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Termin (Alle Termine)
Datum Freitag, 9. April 2021
Uhrzeit 14:00 – 14:30 Uhr (Dauer: 30 min)
Ort https://conf.dfn.de/webapp/conference/979160755
Webkonferenz
Vorheriger Termin Fr 9. April 2021
Nächster Termin Fr 16. April 2021

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Vorträge

Vortragende(r) Daniel Milbaier
Titel Measuring the Privacy Loss with Smart Meters
Vortragstyp Bachelorarbeit
Betreuer(in) Vadim Arzamasov
Vortragsmodus
Kurzfassung The rapid growth of renewable energy sources and the increased sales in

electric vehicels contribute to a more volatile power grid. Energy suppliers rely on data to predict the demand and to manage the grid accordingly. The rollout of smart meters could provide the necessary data. But on the other hand, smart meters can leak sensitive information about the customer. Several solution were proposed to mitigate this problem. Some depend on privacy measures to calculate the degree of privacy one could expect from a solution. This bachelor thesis constructs a set of experiments which help to analyse some privacy measures and thereby determine, whether the value of a privacy measure increases or decreases with an increase in privacy.

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Hinweise

The rapid growth of renewable energy sources and the increased sales in electric vehicels contribute to a more volatile power grid. Energy suppliers rely on data to predict the demand and to manage the grid accordingly. The rollout of smart meters could provide the necessary data. But on the other hand, smart meters can leak sensitive information about the customer. Several solution were proposed to mitigate this problem. Some depend on privacy measures to calculate the degree of privacy one could expect from a solution. This bachelor thesis constructs a set of experiments which help to analyse some privacy measures and thereby determine, whether the value of a privacy measure increases or decreases with an increase in privacy.