3 citations · 5 across the 4 of their papers we have counts for
6 papers · 1 filter
Secure Deep-JSCC Against Multiple Eavesdroppers
Seyyed Amirhossein Ameli Kalkhoran, Mehdi Letafati, Ecenaz Erdemir +3
In this paper, a generalization of deep learning-aided joint source channel coding (Deep-JSCC) approach to secure communications is studied. We propose an end-to-end (E2E) learning…
Active Privacy-Utility Trade-off Against Inference in Time-Series Data Sharing
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
Internet of things (IoT) devices, such as smart meters, smart speakers and activity monitors, have become highly popular thanks to the services they offer. However, in addition to…
Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
We consider a user releasing her data containing some personal information in return of a service. We model user's personal information as two correlated random variables, one of t…
Privacy-Aware Time-Series Data Sharing with Deep Reinforcement Learning
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
Internet of things (IoT) devices are becoming increasingly popular thanks to many new services and applications they offer. However, in addition to their many benefits, they raise…
Privacy-Aware Location Sharing with Deep Reinforcement Learning
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
Location-based services (LBSs) have become widely popular. Despite their utility, these services raise concerns for privacy since they require sharing location information with unt…
Privacy-cost trade-off in a smart meter system with a renewable energy source and a rechargeable battery
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
We study the privacy-cost trade-off in a smart meter (SM) system with a renewable energy source (RES) and a finite-capacity rechargeable battery (RB). Privacy is measured by the mu…