IOTFLA : A Secured and Privacy-Preserving Smart Home Architecture Implementing Federated Learning
| Autor: | Ulrich Aïvodji, Alexandre Martin, Sébastien Gambs |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry 020208 electrical & electronic engineering 020206 networking & telecommunications Context (language use) 02 engineering and technology Computer security computer.software_genre Federated learning Privacy preserving Home automation 0202 electrical engineering electronic engineering information engineering Architecture business Internet of Things computer |
| Zdroj: | IEEE Symposium on Security and Privacy Workshops |
| Popis: | Slowly but steadily, the Internet of Things (IoT) is becoming more and more ubiquitous in our daily life. However, it also brings important security and privacy challenges along with it, especially in a sensitive context such as the smart home. In this position paper, we propose a novel architecture for smart home, called our, focusing on the security and privacy aspects, which combines federated learning with secure data aggregation. We hope that our proposition will provide a step forward towards achieving more security and privacy in smart homes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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