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Dive into the research topics where Serge Fenet is active.

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Featured researches published by Serge Fenet.


Journal of Heuristics | 2006

A study of ACO capabilities for solving the maximum clique problem

Christine Solnon; Serge Fenet

This paper investigates the capabilities of the Ant Colony Optimization (ACO) meta-heuristic for solving the maximum clique problem, the goal of which is to find a largest set of pairwise adjacent vertices in a graph. We propose and compare two different instantiations of a generic ACO algorithm for this problem. Basically, the generic ACO algorithm successively generates maximal cliques through the repeated addition of vertices into partial cliques, and uses “pheromone trails” as a greedy heuristic to choose, at each step, the next vertex to enter the clique. The two instantiations differ in the way pheromone trails are laid and exploited, i.e., on edges or on vertices of the graph.We illustrate the behavior of the two ACO instantiations on a representative benchmark instance and we study the impact of pheromone on the solution process. We consider two measures—the re-sampling and the dispersion ratio—for providing an insight into the performance at run time. We also study the benefit of integrating a local search procedure within the proposed ACO algorithm, and we show that this improves the solution process. Finally, we compare ACO performance with that of three other representative heuristic approaches, showing that the former obtains competitive results.


Lecture Notes in Computer Science | 2003

Searching for maximum cliques with ant colony optimization

Serge Fenet; Christine Solnon

In this paper, we investigate the capabilities of Ant Colony Optimization (ACO) for solving the maximum clique problem. We describe Ant-Clique, an algorithm that successively generates maximal cliques through the repeated addition of vertices into partial cliques. ACO is used to choose, at each step, the vertex to add. We illustrate the behaviour of this algorithm on two representative benchmark instances and we study the impact of pheromone on the solution process. We also experimentally compare Ant-Clique with GLS, a Genetic Local Search approach, and we show that Ant-Clique finds larger cliques, on average, on a majority of DIMACS benchmark instances, even though it does not reach the best known results on some instances.


Molecular Ecology | 2013

Optimizing the trade‐off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual‐based sampling scheme

J. Prunier; Bernard Kaufmann; Serge Fenet; Damien Picard; François Pompanon; Pierre Joly; Jean-Paul Léna

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, that is, the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population‐based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic data sets to investigate the efficiency of an individual‐based sampling scheme (ISS) in detecting isolation‐by‐distance and isolation‐by‐barrier patterns. Provided that pseudo‐replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of interindividual measures of genotypic dissimilarity may efficiently replace interpopulation measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.


Electronic Notes in Theoretical Computer Science | 2002

A distributed Intrusion Detection and Response System based on mobile autonomous agents using social insects communication paradigm

Serge Fenet; Salima Hassas

Abstract The ever increasing connectivity of current computer environments makes traditional Intrusion and Detection Systems more and more inefficient. The ability of moving processes across networks brings new security problems, but also gives us new ways of dealing with these environments. In this paper, we propose an architecture for a distributed stealth Intrusion Detection and Response System (IDRS) based on mobile agents mimicking behaviors of social insects. We present the motivations of an approach that solves several problems actually unchallenged and offers many new ways of thinking future IDRSs. We also depict the foundations of our architecture, discuss its main points, and expose partial results obtained from a prototype. Finally, implementation issues and future work are presented.


international conference on big data | 2016

A framework for evaluating urban land use mix from crowd-sourcing data

Luciano Gervasoni; Martí Bosch; Serge Fenet; Peter F. Sturm

Population in urban areas has been increasing at an alarming rate in the last decades. This evidence, together with the rising availability of massive data from cities, has motivated research on sustainable urban development. In this paper we present a GIS-based land use mix analysis framework to help urban planners to compute indices for mixed uses development, which may be helpful towards developing sustainable cities. Residential and activities land uses are extracted using OpenStreetMap crowd-sourcing data. Kernel density estimation is performed for these land uses, and then used to compute the mixed uses indices. The framework is applied to several cities, analyzing the land use mix output.


Encyclopedia of Cryptography and Security (2nd Ed.) | 2011

Header Based Attacks

Serge Fenet

Header-based attacks are a form of computer offensive in which the attacker uses its ability to forge arbitrary header data to exploit a flaw in the target’s software that will process this header. This flaw can reside in the code making the processing, but also, more dangerously, in the protocol describing this processing. Although this kind of attack can be used with any level of the protocol stack, the term “Header Attack” is increasingly used to describe application-level attacks, like, for example, HTTP header attacks.


arXiv: Cryptography and Security | 2008

XML Rewriting Attacks: Existing Solutions and their Limitations

Azzedine Benameur; Faisal Abdul Kadir; Serge Fenet


Conservation Genetics | 2014

A 40-year-old divided highway does not prevent gene flow in the alpine newt Ichthyosaura alpestris

Prunier J; Bernard Kaufmann; Jean-Paul Léna; Serge Fenet; François Pompanon; Pierre Joly


high performance computing and communications | 2009

A Pattern-Based General Security Framework: An eBusiness Case Study

Azzedine Benameur; Serge Fenet; Ayda Saidane; Smriti Kumar Sinha


ieee international conference on data science and advanced analytics | 2018

Convolutional neural networks for disaggregated population mapping using open data

Luciano Gervasoni; Serge Fenet; Regis Perrier; Peter F. Sturm

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Peter F. Sturm

Cincinnati Children's Hospital Medical Center

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Christine Solnon

Institut national des sciences Appliquées de Lyon

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Martí Bosch

École Polytechnique Fédérale de Lausanne

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