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Privacy breaching attacks pose considerable challenges in the development and deployment of Internet of Things (IoT) applications. Though privacy preserving data mining (PPDM) minimizes sensitive data disclosure probability, sensitive content analysis, privacy measurement and user's privacy awareness issues are yet to be addressed. In this paper, we propose a privacy management scheme that enables...
In this paper, we propose G-Loc which leverages the gradient-based fingerprint map in localization. G-Loc firstly builds a gradient-based map (Gmap) by comparing RSSI values at nearby positions and runs an online extended particle filter to localize the user/device. With the robust Gmap, G-Loc can be more adaptive to the time-variant RSSI and effectively reduces the overhead in fingerprint map calibration...
Smart metering is an essential part of the future smart grid but causes privacy issues by collecting sensitive data from households with a high temporal resolution. Peer-based privacy mechanisms can solve this problem through privacy-aware aggregation. The SMART algorithm, originally proposed for wireless sensor networks, is a lightweight approach to this problem. In this paper, we propose to adapt...
A robust transmit beamforming scheme is proposed for green cognitive radio networks in presence of incorrect steering vector estimations. The beamformer is designed using a stochastic optimization approach. The proposed beamforming scheme achieves three objectives: a) Probability for large-than-a-threshold for secondary user's received power in the steering direction is maximized; b) Probabilities...
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