Lexicographic Inference for Partially Ordered Belief Bases

International audienceCoherence-based approaches are quite popular to reason under inconsistency. Most of them are defined with respect to totally preordered belief bases such as the lexicographic inference which is known to have desirable properties from theoretical, practical and psychological points of view. However, partially preordered belief bases offer much more flexibility to represent efficiently incomplete knowledge and to avoid comparing unrelated pieces of information. In this paper, we propose a lexicographic inference for partially preordered belief bases that extends the classical one. On one hand, we define a natural inference relation which con- sists in applying classical lexicographic inference from all compatible totally preordered belief bases. On the other hand, we propose a novel cardinality-based preorder between consistent subbases. This cardinality- based preorder can be indifferently applied on partially or totally preordered belief bases. Then, applying classical inference on the preferred consistent subbases, according to this preorder, provides another lexicographic inference relation for partially preordered belief bases. Interestingly enough, we show that the second inference is covered by the first one. Lastly, a semantic characterization of these two definitions is provided

Toward an efficient ontology-based event correlation in SIEM

Cooperative intrusion detection use several intrusion detection systems (IDS) and analyzers in order to build a reliable overview of the monitored system trough a central security information and event management system (SIEM). In such environment, the definition of a shared vocabulary describing the exchanged information between tools is prominent. Since these pieces of information are structured, we propose in this paper to use an ontological representation based on Description Logics (DLs) which is a powerful tool for knowledge representation. Moreover, DLs are able to ensure a decidable reasoning. An alert correlation prototype is presented using this ontology, and an illustrative attack scenario is carried out to show the usefulness of the proposed ontolog

Reasoning under inconsistency : from the compilation of stratified belief bases to reasoningfrom partially preordered belief bases

Nous nous intéressons dans cette thèse aux approches basées sur la restauration de la cohérence à partir de bases de croyances stratifiées ainsi qu'à partir de bases de croyances partiellement préordonnées (BCPP). Dans le premier cas, nous nous attaquons aux problèmes de complexité en proposant trois nouvelles approches de compilation que nous qualifions de flexibles en étant paramétrées par n'importe quel langage cible de compilation. La première concerne l'inférence possibiliste et s'adapte facilement à l'inférence linéaire. La seconde approche se rapporte à l'inférence lexicographique et se base sur la notion de contraintes de cardinalité Booléennes. Nous introduisons aussi une nouvelle compilation pour l'inférence MSP (pour Minimum de Specificity Principle). En ce qui concerne le raisonnement à partir de BCPPs qui offrent plus de flexibilité dans de nombreuses situations, notre première contribution consiste en l'introduction d'une extension de l'inférence lexicographique classique qui revêt un vif intérêt. La seconde contribution dans ce même cadre, est l'étude comparative des différentes relations d'inférence à partir de BCPPs relativement à la complexité, les propriétés logiques et la prudence. Une dernière contribution est l'application du raisonnement en présence d'incohérence dans le cadre de la détection d'intrusions coopérative. En effet, nous proposons une nouvelle approche de corrélation d'alertes. Cette approche se base sur le raisonnement à partir de BCPPs exprimées en logiques de description qui sont bien adaptées à la représentation des informations structurées tout en garantissant la décidabilité du raisonnement.In this thesis, we are interested in coherence based approaches from both stratified belief bases and partially preordered belief bases (PPBB). In the first case, we tackle the complexity problems by proposing three new compilation approaches. The first one is about the possibilistic inference and applies easily to linear inference. The second approach is relative to lexicographic inference and is based on Boolean cardinality constraints. We also introduce a novel compilation approach for MSP entailment (MSP for Minimum Specificity Principle). As to reasoning from PPBBs which offer much more flexibility in many situations, our first contribution consists in extending the lexicographic inference which has interesting properties. The second contribution is a comparative study of the different inference relations from PPBBs with respect to three key dimensions, namely the complexity, the logical properties and the cautiousness. The last contribution is the application of reasoning under inconsistency in the case of intrusion detection. More precisely, we propose a new correlation approach. This latter is based on reasoning from PPBBs expressed in description logics, which are suitable to represent structured informations by ensuring the decidability of reasoning

Constrained Value-Based Argumentation Framework

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Constrained Value-Based Argumentation Framework

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Etude comparative des relations d'inférence à partir de bases de croyances partiellement préordonnées

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De l'utilisation des logiques de description à la gestion d'incohérences en détection d'intrusion coopérative

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Cooperative Bees Swarm for Solving the Maximum Weighted Satisfiability Problem

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Bridging possibilistic conditional knowledge bases and partially ordered bases

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A New Default Theories Compilation for MSP-entailment

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