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Proximity-based mobile social networks (PMSNs) are becoming increasingly popular in recent years with the explosive growth of mobile devices, where a user can find a best matching friend in vicinity through profile matching. However, the matching process calls for the publication of users' personal information, which conflicts with users' growing privacy concerns about revealing their profiles to strangers. To achieve privacypreserving friend discovery, many schemes are proposed based on traditional cryptographic methods, such as homomorphic and commutative encryption, which inevitably introduce tremendous overhead to the system and are not practical for the resourcelimited mobile devices. In this paper, we propose an Efficient Weight-based Private Matching (EWPM) protocol, which provides a realistic matching approach considering both the number of common interests and the corresponding weights on them. In EWPM, we utilize the Confusion Matrix Transformation (CMT) algorithm to achieve a secure and efficient matching. Security analysis and detailed simulations show that our proposed scheme can realize privacy-preserving friend discovery with higher efficiency.

Since viscoelastic attenuation effects are ubiquitous in subsurface media, the seismic source wavelet rapidly evolves as the wave travels through the subsurface. Eliminating the source wavelet and compensating the attenuation effect together may improve seismic resolution. Gabor deconvolution can achieve these two processes simultaneously, by removing the propagating wavelet which is the combination of the source wavelet and the attenuation effect. The Gabor deconvolution operator is determined based on the Gabor spectrum of a nonstationary seismic trace. By assuming white reflectivity, the Gabor amplitude spectrum can be smoothed to produce the required amplitude spectrum of the propagating wavelet. In this paper, smoothing is set as a least-squares inverse problem, and is referred to as regularized smoothing. By assuming that the source wavelet and the attenuation process are both minimum phased, the phase spectrum of the propagating wavelet can be defined by the Hilbert transform of the natural logarithm of the smoothed amplitude spectrum. The inverse of the complex spectrum of the propagating wavelet is the Gabor deconvolution operator. Applying it to the original time-frequency spectrum of the nonstationary trace produces an estimated time-frequency spectrum of reflectivity series. The final time-domain highresolution trace, obtained by an inverse Gabor transform, is close to a band-pass filtered version of the reflectivity series.

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