On the Utility of Privacy Measures for Battery-Based Load Hiding: Unterschied zwischen den Versionen

Aktuelle Version vom 19. April 2022, 11:01 Uhr

Vortragende(r)	Hatem Nouri
Vortragstyp	Bachelorarbeit
Betreuer(in)	Vadim Arzamasov
Termin	Fr 22. April 2022
Vortragsmodus	in Präsenz
Kurzfassung	Hybrid presentation : https://kit-lecture.zoom.us/j/67744231815 Battery based load hiding gained a lot of popularity in recent years as an attempt to guarantee a certain degree of privacy for users in smart grids. Our work evaluates a set of the most common privacy measures for BBLH. For this purpose we define logical natural requirements and score how well each privacy measure complies to each requirement. We achieve this by scoring the response for load profile altering (e.g. noise addition) using measures of displacement. We also investigate the stability of privacy measures toward load profile length and number of bins using specific synthetic data experiments. Results show that certain private measures fail badly to one or many requirements and therefore should be avoided.

@@ Zeile 2: / Zeile 2: @@
 |vortragender=Hatem Nouri
 |email=ujews@student.kit.edu
-|vortragstyp=Proposal
+|vortragstyp=Bachelorarbeit
 |betreuer=Vadim Arzamasov
-|termin=Institutsseminar/2021-11-26
+|termin=Institutsseminar/2022-04-22
-|kurzfassung=Smart meters can leak private informations. example : types of devices / number of employees ...
+|vortragsmodus=in Präsenz
+|kurzfassung=Hybrid presentation : https://kit-lecture.zoom.us/j/67744231815
-Battery-based Load Hiding(BBLH) can be used to increase privacy. (pairing a battery with a charge / discharge algorithm)
+Battery based load hiding gained a lot of popularity in recent years as an attempt to guarantee a certain degree of privacy for users in smart grids. Our work evaluates a set of the most common privacy measures for BBLH. For this purpose we define logical natural requirements and score how well each privacy measure complies to each requirement. We achieve this by scoring the response for load profile altering (e.g. noise addition) using measures of displacement. We also investigate the stability of privacy measures toward load profile length and number of bins using specific synthetic data experiments.
+Results show that certain private measures fail badly to one or many requirements and therefore should be avoided.
-In this context, multiple Privacy Measures are essential to measure and compare the efficiency of different BBLH setups.
-However, each measure can rank the BBLH setups differently, which raises the question :
-Which privacy measures are more reliable for this purpose?
-The goal of this study is to compare different privacy measures through analysis of their behaviour in relationship with certain natural requirements.
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