A New Crypto-Classifier Service for Energy Efficiency in Smart Cities
| Autor: | Amira Ben Hamida, Mohamed-Haykel Zayani, Renaud Sirdey, Alessandro Ferreira Leite, Oana Stan, Mallek Mziou-Sallami |
|---|---|
| Přispěvatelé: | Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), IRT SystemX (IRT SystemX), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), IRT SystemX |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Information privacy
Computer science business.industry Energy management Homomorphic encryption 020206 networking & telecommunications Cryptography 02 engineering and technology Energy consumption Computer security computer.software_genre Encryption [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR] Smart city 11. Sustainability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business computer Efficient energy use |
| Zdroj: | Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems 7th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2018) 7th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2018), Mar 2018, Funchal, Portugal. pp.78-88, ⟨10.5220/0006697500780088⟩ SMARTGREENS |
| DOI: | 10.5220/0006697500780088⟩ |
| Popis: | International audience; Smart Cities draw a nice picture of a connected city where useful services and data are ubiquitous, energy is properly used and urban infrastructures are well orchestrated. Fulfilling this vision in our cities implies unveiling citizens data and assets. Thus, security and data privacy appear as crucial issues to consider. In this paper, we study a way of offering a secured energy management service for diagnosis and classification of buildings in a district upon their energy consumption. Our remote service can be beneficial both for local authorities and householders without revealing private data. Our framework is designed such that the private data is permanently encrypted and that the server performing the classification algorithm has no information about the sensitive data and no capability to decrypt it. The underlying cryptographic technology used is homomorphic encryption, allowing to perform calculations directly on encrypted data. We present here the prototype of a crypto-classification service for energy consumption profiles involving different actors of a smart city community, as well as the associated performances results. We assess our proposal atop of real data taken from an Irish residential district and we show that our service can achieve acceptable performances in terms of security, execution times and memory requirements. |
| Databáze: | OpenAIRE |
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