Generalization is a well-known method for privacy preserving data publication. Despite its vast popularity, it has several drawbacks such as heavy information loss, difficulty of supporting marginal publication, and so on. To overcome these drawbacks, we develop ANGEL,1 a new anonymization technique that is as effective as generalization in privacy protection, but is able to retain significantly more information in the microdata. ANGEL is applicable to any monotonic principles (e.g., l-diversity, t-closeness, etc.), with its superiority (in correlation preservation) especially obvious when tight privacy control must be enforced. We show that ANGEL lends itself elegantly to the hard problem of marginal publication. In particular, unlike generalization that can release only restricted marginals, our technique can be easily used to publish any marginals with strong privacy guarantees.

The localization of sensor nodes is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from GPS devices or by virtue of being manually placed. In this paper, we propose a distributed method to localization of sensor nodes using a single moving beacon, where sensor nodes compute their position estimate based on the range-free technique. Two parameters are critical to the location accuracy of sensor nodes: the radio transmission range of the beacon and how often the beacon broadcasts its position. Theoretical analysis shows that these two parameters determine the upper bound of the estimation error when the traverse route of the beacon is a straight line. We extend the position estimate when the traverse route of the beacon is randomly chosen in a real-world situation, where the radio irregularity might cause a node to miss some crucial coordinate information from the beacon. We further point out that the movement pattern of the beacon plays a pivotal role in the localization task for sensors. To minimize estimation errors, sensor nodes can carry out a variety of algorithms in accordance with the movement of the beacon. Simulation results compare variants of the distributed method in a variety of testing environments. Real experiments show that the proposed method is feasible and can estimate the location of sensor nodes accurately, given a single moving beacon.

The localization of the sensor node is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from a GPS device or by virtue of being manually placed. In this paper, we propose two distributed methods to localization of sensor nodes using a single moving beacon where sensor nodes compute their position estimate based on the range-free technique. The first method uses the arrival and departure information of a walking beacon and the second method exploits the variance of the received signal strength (RSS) from the beacon. We provide the upper bound of the estimation error for these methods in an ideal environment. Critical to the location accuracy of sensor nodes are two more parameters, the radio transmission range of the beacon, and how often the beacon broadcasts its position. Simulation results show the location estimate error of sensor nodes applying the proposed two methods. The results are consistent to the theoretical analysis and the average estimate errors could be within one meter.