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17295
23/10/2017

Experience Report: log mining using natural language processing and application to anomaly detection

C.BERTERO, M.ROY, C.SAUVANAUD, G.TREDAN

TSF

Manifestation avec acte : International Symposium on Software Reliability Engineering ( ISSRE ) 2017 du 23 octobre au 26 octobre 2017, Toulouse (France), Octobre 2017, 10p. , N° 17295

Lien : https://hal.laas.fr/hal-01576291

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Abstract

Event logging is a key source of information on a system state. Reading logs provides insights on its activity, assess its correct state and allows to diagnose problems. However, reading does not scale: with the number of machines increasingly rising, and the complexification of systems, the task of auditing systems' health based on logfiles is becoming overwhelming for system administrators. This observation led to many proposals automating the processing of logs. However, most of these proposal still require some human intervention, for instance by tagging logs, parsing the source files generating the logs, etc. In this work, we target minimal human intervention for logfile processing and propose a new approach that considers logs as regular text (as opposed to related works that seek to exploit at best the little structure imposed by log formatting). This approach allows to leverage modern techniques from natural language processing. More specifically, we first apply a word embedding technique based on Google's word2vec algorithm: logfiles' words are mapped to a high dimensional metric space, that we then exploit as a feature space using standard classifiers. The resulting pipeline is very generic, computationally efficient, and requires very little intervention. We validate our approach by seeking stress patterns on an experimental platform. Results show a strong predictive performance (≈ 90% accuracy) using three out-of-the-box classifiers.

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17317
22/09/2017

Reliability enhancement of redundancy management in AFDX networks

M.LI, G.ZHU, Y.SAVARIA, M.LAUER

Ecole Montréal, TSF

Rapport LAAS N°17317, DOI: 10.1109/TII.2017.2732345 , Septembre 2017, 12p.

Lien : https://hal.laas.fr/hal-01585141

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Abstract

AFDX is a safety critical network in which a redundancy management mechanism is employed to enhance the reliability of the network. However, as stated in the ARINC664-P7 standard, there still exists a potential problem, which may fail redundant transmissions due to sequence inversion in the redundant channels. In this paper, we explore this phenomenon and provide its mathematical analysis. It is revealed that the variable jitter and the transmission latency difference between two successive frames are the two main sources of sequence inversion. Thus, two methods are proposed and investigated to mitigate the effects of jitter pessimism, which can eliminate the potential risk. A case study is carried out and the obtained results confirm the validity and applicability of the developed approaches.

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17189
12/09/2017

Confidence assessment framework for safety arguments

R.WANG, J.GUIOCHET, G.MOTET

TSF

Manifestation avec acte : International Conference on Computer Safety, Reliability and Security ( SafeComp ) 2017 du 12 septembre au 15 septembre 2017, Trento (Italie), Septembre 2017, 14p. , N° 17189

Lien : https://hal.archives-ouvertes.fr/hal-01533221

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Abstract

Confidence in safety critical systems is often justified by safety arguments. The excessive complexity of systems nowadays introduces more uncertainties for the arguments reviewing. This paper proposes a framework to support the argumentation assessment based on experts' decision and confidence in the decision for the lowest level claims of the arguments. Expert opinion is extracted and converted in a quantitative model based on Dempster-Shafer theory. Several types of argument and associated formulas are proposed. A preliminary validation of this framework is realized through a survey for safety experts.

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17230
08/09/2017

Toward an intrusion detection approach for IoT based on radio communications profiling

J.ROUX, E.ALATA, V.NICOMETTE, M.KAANICHE

TSF

Manifestation avec acte : European Dependable Computing Conference ( EDCC ) 2017 du 04 septembre au 08 septembre 2017, Genève (Suisse), Septembre 2017, 4p. , N° 17230

Lien : https://hal.laas.fr/hal-01561710

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Abstract

Nowadays, more and more Internet-of-Things (IoT) smart products, interconnected through various wireless communication technologies (Wifi, Bluetooth, Zigbee, Z-wave, etc.) are integrated in daily life, especially in homes, factories, cities, etc. Such IoT technologies have become very attractive with a large variety of new services offered to improve the quality of life of the endusers or to create new economic markets. However, the security of such connected objects is a real concern due to weak or flawed security designs, configuration errors or imperfect maintenance. Moreover, the vulnerabilities discovered in IoT products are often difficult to eliminate because, most of the time, they cannot be patched easily. Therefore, protection mechanisms are needed to mitigate the potential risks induced by such objects in private and public connected areas. In this paper, we propose a novel approach to detect potential attacks in smart places (e.g. smart homes) by detecting deviations from legitimate communication behavior, in particular at the physical layer. The proposed solution is based on the profiling and monitoring of the Radio Signal Strenght Indication (RSSI) associated to the wireless transmissions of the connected objects. A machine learning neural network algorithm is used to characterize legitimate communications and to identify suspiscious scenarios. We show the feasibility of this approach and discuss some possible application cases.

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17200
29/07/2017

Can robot navigation bugs be found in simulation? An exploratory study

T.SOTIROPOULOS, H.WAESELYNCK, J.GUIOCHET, F.INGRAND

TSF, RIS

Manifestation avec acte : IEEE International Conference on Software Quality, Reliability and Security ( QRS ) 2017 du 25 juillet au 29 juillet 2017, Prague (République Tchèque), Juillet 2017, 10p. , N° 17200

Lien : https://hal.archives-ouvertes.fr/hal-01534235

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Abstract

The ability to navigate in diverse and previously unknown environments is a critical service of autonomous robots. The validation of the navigation software typically involves test campaigns in the field, which are costly and potentially risky for the robot itself or its environment. An alternative approach is to perform simulation-based testing, by immersing the software in virtual worlds. A question is then whether the bugs revealed in real worlds can also be found in simulation. The paper reports on an exploratory study of bugs in an academic software for outdoor robots navigation. The detailed analysis of the triggers and effects of these bugs shows that most of them can be revealed in low-fidelity simulation. It also provides insights into interesting navigation scenarios to test as well as into how to address the test oracle problem.

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17224
01/06/2017

The many faces of graph dynamics

Y.A.PIGNOLET, M.ROY, S.SCHMID, G.TREDAN

ABB CRC, Switzerland, TSF, AAU

Revue Scientifique : Journal of Statistical Mechanics: Theory and Experiment, Vol.2017, N°6, 063401p., Juin 2017 , N° 17224

Lien : https://hal.archives-ouvertes.fr/hal-01559708

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Abstract

The topological structure of complex networks has fascinated researchers for several decades, resulting in the discovery of many universal properties and reoccurring characteristics of different kinds of networks. However, much less is known today about the network dynamics: indeed, complex networks in reality are not static, but rather dynamically evolve over time. Our paper is motivated by the empirical observation that network evolution patterns seem far from random, but exhibit structure. Moreover, the specific patterns appear to depend on the network type, contradicting the existence of a " one fits it all " model. However, we still lack observables to quantify these intuitions, as well as metrics to compare graph evolutions. Such observables and metrics are needed for extrapolating or predicting evolutions, as well as for interpolating graph evolutions. To explore the many faces of graph dynamics and to quantify temporal changes, this paper suggests to build upon the concept of centrality, a measure of node importance in a network. In particular, we introduce the notion of centrality distance, a natural similarity measure for two graphs which depends on a given centrality, characterizing the graph type. Intuitively, centrality distances reflect the extent to which (non-anonymous) node roles are different or, in case of dynamic graphs, have changed over time, between two graphs. We evaluate the centrality distance approach for five evolutionary models and seven real-world social and physical networks. Our results empirically show the usefulness of centrality distances for characterizing graph dynamics compared to a null-model of random evolution, and highlight the differences between the considered scenarios. Interestingly, our approach allows us to compare the dynamics of very different networks, in terms of scale and evolution speed.

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17120
29/05/2017

L'aspect topologique des recommandations

E.LE MERRER, G.TREDAN

Technicolor France, TSF

Manifestation avec acte : Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications ( ALGOTEL ) 2017 du 29 mai au 02 juin 2017, Quiberon (France), Mai 2017, 4p. , N° 17120

Lien : https://hal.archives-ouvertes.fr/hal-01517738

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Résumé

La recommandation joue un rôle central dans le e-commerce et dans l'industrie du divertissement. L'intérêt croissant pour la transparence algorithmique nous motive dans cet article à observer les résultats de recommandations sous la forme d'un graphe capturant les navigations proposées dans l'espace des items. Nous argumentons qu'une telle approche en "boite noire" est utile dans le cas d'une exploration limitée à un utilisateur: nous illustrons une topologie tirée de recommandations à un utilisateur de Youtube, fournissons ses caractéristiques clés, et montrons qu'elle renseigne sur la connaissance de cet utilisateur par le système. Nous montrons ensuite que l'analyse de cette topologie d'aborder la question du \text{biais} potentiel dans ces recommandations. Nous postulons que les systèmes de recommandation produisent naturellement des topologies cohérentes, et qu'une manipulation de ces résultats par l'ajout de liens biaisés a toutes les chances de violer cette cohérence (à la manières des liens longs d'un modèle "petit monde"). Ce postulat est supporté par l'analyse d'un modèle génératif basé sur les kNN et par l'exploitation du crawl Youtube, en ciblant la prédiction de liens "Recommandé pour vous" (i.e., biaisés ou non par Youtube).

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17229
19/05/2017

Détection d'Intrusion dans l'Internet des Objets : Problématiques de sécurité au sein des domiciles

J.ROUX

TSF

Manifestation avec acte : Rendez-vous de la Recherche et de l'Enseignement de la Sécurité des Systèmes d'Information ( RESSI ) 2017 du 17 mai au 19 mai 2017, Grenoble (France), Mai 2017, 4p. , N° 17229

Lien : https://hal.laas.fr/hal-01561720

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Résumé

Afin de comprendre les enjeux à l'Internet des Objets, nous présentons un état de l'art des problématiques de sécurité de ce domaine, notamment au sein des domiciles. Celui-ci décrit les surfaces d'attaque de ces objets présents dans les domiciles ainsi que les moyens de protection existants. Finalement, cet état de l'art nous permet d'identifier les insuffisances de ces solutions et de commencer à analyser les potentielles améliorations notamment l'utilisation de méthodes de détection d'intrusion en opération et d'analyse comportementale via des mécanismes d'apprentissage.

140503
17222
19/05/2017

Early decision and stopping in synchronous consensus: A predicate-based guided tour

A.CASTANEDA, Y.MOSES, M.RAYNAL, M.ROY

UNAM, TECHNION, IRISA, TSF

Manifestation avec acte : International Conference on NETwork sYStems ( NETYS ) 2017 du 17 mai au 19 mai 2017, Marrakech (Maroc), Mai 2017, pp.167-221 , N° 17222

Lien : https://hal.archives-ouvertes.fr/hal-01559723

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Abstract

Consensus is the most basic agreement problem encountered in fault-tolerant distributed computing: each process proposes a value and non-faulty processes must agree on the same value, which has to be one of the proposed values. While this problem is impossible to solve in asynchronous systems prone to process crash failures, it can be solved in synchronous (round-based) systems where all but one process might crash in any execution. It is well-known that (t + 1) rounds are necessary and sufficient in the worst case execution scenario for the processes to decide and stop executing, where t < n is a system parameter denoting the maximum number of allowed process crashes and n denotes the number of processes in the system. Early decision and stopping considers the case where f < t processes actually crash, f not being known by processes. It has been shown that the number of rounds that have to be executed in the worst case is then min(f + 2, t + 1). Following Castañeda, Gonczarowski and Moses (DISC 2014), the paper shows that this value is an upper bound attained only in worst execution scenarios. To this end, it investigates a sequence of three early deciding/stopping predicates P1 = Pcount, P2 = P dif and P3 = P pref0 , of increasing power, which differ in the information obtained by the processes from the actual failure, communication and data pattern. It is shown that each predicate Pi is better than the previous one Pi−1, i ∈ {2, 3}, in the sense that there are executions where Pi allows processes to reach a decision earlier than Pi−1, while Pi−1 never allows a process to decide earlier than Pi. Moreover, P3 = P pref0 is an unbeatable predicate in the sense that it cannot be strictly improved: if there is an early deciding/stopping predicate P that improves the decision time of a process with respect to P pref0 in a given execution , then there is at least one execution in which a process decides with P strictly later than with P pref0 .

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17139
05/05/2017

Livrable 1.2. Modélisationpréliminaire en cas d'utilisation (UML) du projet ALFS

K.CABRERA CASTILLOS, J.GUIOCHET

TSF

Rapport de Contrat : Mai 2017, 32p. , N° 17139

Lien : Projet ALFS

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