Consumed Energy (100 records) Your university logo here Characterization of Energy Consumption of Privacy Mechanism for Participatory Sensing Omar J. Avilés-Rivera, Yarelis Ares-Mendoza, Mentor: Idalides Vergara-Laurens Abstract Participatory Sensing systems rely on the willingness of people to gather and report data using their mobile devices. Privacy is one of the major concerns in PS as well as energy consumption. Every privacy mechanism has some limitations in terms of the provided privacy or energy consumption. A Hybrid Privacy Mechanism has been designed for addressing the performance limitation of available privacy mechanisms. This project focus on the characterization of energy consumption of such mechanism and comparison with other mechanisms available in the literature. Motivation Participants location need to be protected, in order to make mobile device users became part of the system. There is a need for an energy efficient and privacy preserving mechanism. Depending on how they are transmitting the data (Wi-Fi or 3G), it is the amount of consumed energy. Quality of Estimation1 System Architecture Privacy Mechanisms Results Comparison between Wi-Fi and 3G Storage for Point of Interest Conclusion Our experiments show that the Hybrid algorithm achieves a reduction on energy consumption compared to encryption based techniques. When transmitting the data and if the system allows to do it, is recommended to use Wi-Fi because it is more energy efficient. In addition, is better to keep the Points of Interest in disk, instead of memory, because the amount of energy consumed is almost similar and in case that the battery is fully discharged, the data is not lost. Acknowledgements The authors thank Dr. Miguel Labrador, the University of South Florida, the National Science Foundation under grant No. 1062160, Luis Ruiz-Linares, Nelson Rivera-Garcia and Yanira Rivera-Negron. *Equipment: Samsung SPH-D720 Nexus S with an Android OS Version 4.0.3, Hewlett Packard E3631A 0-6V,5A/0-(+-) 25V, 1A Triple Output DC Power Supply. Cache Points Run App Configuration Data Report (Double Encrypted) or (Anonymized location, sensed data) Encrypted (sensed data) Data Broker Application Server Server Participant Location (X,Y) Anonymized (A,B) Anonymization K – anonymity Algorithm TCP UDP Server Participant Location (X,Y) Anonymized (A,B) Obfuscation Points of Interest Algorithm UDP Consumed Energy (100 records) Technique Memory Disk Points of Interest 0.28 1.21 Hybrid - 30% 15.02 16.90 Hybrid - 50% 25.09 25.48 Hybrid - 70% 33.30 35.28 Encryption - 100% 45.39 Server Participant Location, sensed data Encryption Encryption Algorithm Encrypted Data Asymmetric Symmetric SSL Hybrid Algorithm (Localization, sensed data) Selection Algorithm Points of Interest (Anonymized location, Encrypted Encryption Data Broker 1Vergara-Laurens, IdalidesJ. and Mendez-Chaves, Diego and Labrador, MiguelA. On the Interactions between Privacy-Preserving, Incentive, and Inference Mechanisms in Participatory Sensing Systems. Network and System Security. Vol 7873. 2013. 614-620 Your university logo here