Development of an electrical model of a resistive micromegas

We have developped a model to simulate the behavior of a resistive micromegas (MICROMEsh GAseous Structure) detector to a discharge using an electronic software (Virtuoso)

On the Complexity of tt-Closeness Anonymization and Related Problems

An important issue in releasing individual data is to protect the sensitive information from being leaked and maliciously utilized. Famous privacy preserving principles that aim to ensure both data privacy and data integrity, such as $k$-anonymity and $l$-diversity, have been extensively studied both theoretically and empirically. Nonetheless, these widely-adopted principles are still insufficient to prevent attribute disclosure if the attacker has partial knowledge about the overall sensitive data distribution. The $t$-closeness principle has been proposed to fix this, which also has the benefit of supporting numerical sensitive attributes. However, in contrast to $k$-anonymity and $l$-diversity, the theoretical aspect of $t$-closeness has not been well investigated. We initiate the first systematic theoretical study on the $t$-closeness principle under the commonly-used attribute suppression model. We prove that for every constant $t$ such that $0\leq t<1$, it is NP-hard to find an optimal $t$-closeness generalization of a given table. The proof consists of several reductions each of which works for different values of $t$, which together cover the full range. To complement this negative result, we also provide exact and fixed-parameter algorithms. Finally, we answer some open questions regarding the complexity of $k$-anonymity and $l$-diversity left in the literature.Comment: An extended abstract to appear in DASFAA 201

Test in a beam of large-area Micromegas chambers for sampling calorimetry

Application of Micromegas for sampling calorimetry puts specific constraints on the design and performance of this gaseous detector. In particular, uniform and linear response, low noise and stability against high ionisation density deposits are prerequisites to achieving good energy resolution. A Micromegas-based hadronic calorimeter was proposed for an application at a future linear collider experiment and three technologically advanced prototypes of 1$\times$1 m$^{2}$ were constructed. Their merits relative to the above-mentioned criteria are discussed on the basis of measurements performed at the CERN SPS test-beam facility

Parameterized Complexity of the k-anonymity Problem

The problem of publishing personal data without giving up privacy is becoming increasingly important. An interesting formalization that has been recently proposed is the $k$-anonymity. This approach requires that the rows of a table are partitioned in clusters of size at least $k$ and that all the rows in a cluster become the same tuple, after the suppression of some entries. The natural optimization problem, where the goal is to minimize the number of suppressed entries, is known to be APX-hard even when the records values are over a binary alphabet and $k=3$, and when the records have length at most 8 and $k=4$ . In this paper we study how the complexity of the problem is influenced by different parameters. In this paper we follow this direction of research, first showing that the problem is W[1]-hard when parameterized by the size of the solution (and the value $k$). Then we exhibit a fixed parameter algorithm, when the problem is parameterized by the size of the alphabet and the number of columns. Finally, we investigate the computational (and approximation) complexity of the $k$-anonymity problem, when restricting the instance to records having length bounded by 3 and $k=3$. We show that such a restriction is APX-hard.Comment: 22 pages, 2 figure

Synthetic sequence generator for recommender systems - memory biased random walk on sequence multilayer network

Personalized recommender systems rely on each user's personal usage data in the system, in order to assist in decision making. However, privacy policies protecting users' rights prevent these highly personal data from being publicly available to a wider researcher audience. In this work, we propose a memory biased random walk model on multilayer sequence network, as a generator of synthetic sequential data for recommender systems. We demonstrate the applicability of the synthetic data in training recommender system models for cases when privacy policies restrict clickstream publishing.Comment: The new updated version of the pape

Cor-Split: Defending Privacy in Data Re-Publication from Historical Correlations and Compromised Tuples

Abstract. Several approaches have been proposed for privacy preserving data publication. In this paper we consider the important case in which a certain view over a dynamic dataset has to be released a number of times during its history. The insufficiency of techniques used for one-shot publication in the case of subsequent releases has been previously recognized, and some new approaches have been proposed. Our research shows that relevant privacy threats, not recognized by previous proposals, can occur in practice. In particular, we show the cascading effects that a single (or a few) compromised tuples can have in data re-publication when coupled with the ability of an adversary to recognize historical correlations among released tuples. A theoretical study of the threats leads us to a defense algorithm, implemented as a significant extension of the m-invariance technique. Extensive experiments using publicly available datasets show that the proposed technique preserves the utility of published data and effectively protects from the identified privacy threats.

Resistive micromegas for sampling calorimetry

MicromegasInternational audienceMicromegas is an attractive option for a gaseous sampling calorimeter. It delivers proportional and fast signals, achieves high efficiency to minimum ionising particles with a compact design and shows well-uniform performance over meter-square areas. The current R&D focuses on large- size spark-protected Micromegas with integrated front-end electronics. It targets an application at future linear colliders (LC) and possible upgrades of LHC experiments for the running at high luminosity. In the later case, occasional sparking should be suppressed to avoid dead-time and technical solutions using resistive coatings are investigated. Small prototypes of resistive and non-resistive Micromegas were constructed and tested in a beam at DESY. Results are reported with emphasis on the impact of the resistive layer on the detector performance

Construction and test of a 1×1 m2 Micromegas chamber for sampling hadron calorimetry at future lepton colliders

Equipe MicromegasSampling calorimeters can be finely segmented and used to detect showers with high spatial resolution. This imaging power can be exploited at future linear collider experiments where the measurement of jet energy by a Particle flow method requires optimal use of tracking and calorimeter information. Gaseous detectors can achieve high granularity and a hadron sampling calorimeter using Micromegas chambers as active elements is considered in this paper. Compared to traditional detectors using wires or resistive plates, Micromegas is free of space charge effects and could therefore show superior calorimetric performance. To test this concept, a prototype of 1×1 m2 equipped with 9216 readout pads of 1×1 cm2 has been built. Its technical and basic operational characteristics are reported