Pattern-sensitive Time-series Anonymization and its Application to Energy-Consumption Data

Time series anonymization is an important problem. One prominent example of time series are energy consumption records, which might reveal details of the daily routine of a household. Existing privacy approaches for time series, e.g., from the field of trajectory anonymization, assume that every single value of a time series contains sensitive information and reduce the data quality very much. In contrast, we consider time series where it is combinations of tuples that represent personal information. We propose (n; l; k)-anonymity, geared to anonymization of time-series data with minimal information loss, assuming that an adversary may learn a few data points. We propose several heuristics to obtain (n; l; k)-anonymity, and we evaluate our approach both with synthetic and real data. Our experiments confirm that it is sufficient to modify time series only moderately in order to fulfill meaningful privacy requirements

Anonymous search histories featuring personalized advertisement - balancing privacy with economic interests

Abstract. Search engines are key to finding information on the web. Search presently is free for users – financed by targeted advertisement. Today, the current search terms determine the ad placement. In the near future, search-engine providers will make use of detailed user profiles for better ad placement. This puts user privacy at risk. Anonymizing search histories, which is a solution in principle, gives way to a trade-off between privacy and the usability of the data for ad placement. This paper studies this tradeoff systematically. To this end, we implement an algorithm for the anonymization of search histories which is flexible regarding the target function. It can retain frequent terms or terms where corresponding ads are clicked with a high probability, keep up the number of users it can derive interests for, etc. We quantify the usefulness of the anonymized log for ad placement in a broad way, e.g., by estimating the number of ad clicks or of ad impressions, based on marketing data from Yahoo! As a result, anonymized search logs are still useful for ad placement, but this very much depends on the target function.

Quantum critical behavior in a CePt ferromagnetic Kondo lattice

6 p. : il.Most of the studies of heavy fermions near a quantum critical point QCP have been carried out on antiferromagnetic systems. In this paper we report on the disappearance of ferromagnetic FM order in CePt as seen by the ac magnetic susceptibility and the electrical resistance measurements under pressures P up to 15 GPa. The pressure dependence of the Curie temperature TC P follows a typical Doniach’s phase diagram for Kondo lattice systems and it is consistent with a QCP at the critical pressure PC 12.1 GPa. The resistance in the vicinity of the QCP shows clearly a non-Fermi liquid NFL and beyond that a Fermi liquid FL state is recovered. A semiquantitative discussion on the nature of the vanishing of TC in a FM Ce Kondo lattice is given for the first time