Littérature scientifique sur le sujet « Analyse de logiciels malveillants »
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Articles de revues sur le sujet "Analyse de logiciels malveillants"
Deschâtelets, Gilles. « L’homo mediaticus vs l’interface masquée : un combat à finir ». Documentation et bibliothèques 31, no 2 (31 octobre 2018) : 55–66. http://dx.doi.org/10.7202/1053469ar.
Texte intégralBéland, Sébastien, David Magis et Gilles Raîche. « Estimation des paramètres d’item et de sujet à partir du modèle de Rasch ». Mesure et évaluation en éducation 36, no 1 (22 avril 2014) : 83–110. http://dx.doi.org/10.7202/1024466ar.
Texte intégralLangelier, Guilaume, Houari A. Sahraoui et Pierre Poulin. « Visualisation et analyse de logiciels de grande taille ». L'objet 11, no 1-2 (30 juin 2005) : 159–73. http://dx.doi.org/10.3166/objet.11.1-2.159-173.
Texte intégralHecquet, A., Martine Butel, Martine David, Catherine Bouyssou et Nicole Lemoine. « Analyse et expérimentation de logiciels pour des élèves ayant des difficultés linguistiques ». Migrants formation 70, no 1 (1987) : 87–91. http://dx.doi.org/10.3406/diver.1987.6569.
Texte intégralEmirkanian, Louisette, et Lorne H. Bouchard. « Conception et réalisation de logiciels : vers une plus grande intégration des connaissances de la langue ». Revue québécoise de linguistique 16, no 2 (12 mai 2009) : 189–220. http://dx.doi.org/10.7202/602599ar.
Texte intégralDésilets, Mario. « Une analyse de logiciels correcteurs à partir d'un point de vue didactique ». La Lettre de la DFLM 22, no 1 (1998) : 23–26. http://dx.doi.org/10.3406/airdf.1998.1330.
Texte intégralBaudoux, Gaëlle, Xaviéra Calixte et Pierre Leclercq. « Numérisation de l'idéation : analyse des méthodes de travail collaboratif instrumenté en conception intégrée ». SHS Web of Conferences 82 (2020) : 03002. http://dx.doi.org/10.1051/shsconf/20208203002.
Texte intégralAlbiges, Christophe. « Les sûretés et les biens immatériels en droit français : quelles sont les perspectives ? » Les Cahiers de droit 59, no 2 (12 juin 2018) : 333–50. http://dx.doi.org/10.7202/1048584ar.
Texte intégralSilberztein, Max. « Linguistique et Traitement Automatique des Langues : une coopération nécessaire ». Langues & ; Parole 5 (30 novembre 2020) : 43–66. http://dx.doi.org/10.5565/rev/languesparole.63.
Texte intégralDemazière, Didier, François Horn et Marc Zune. « La socialisation dans les « communautés » de développement de logiciels libres ». Sociologie et sociétés 41, no 1 (11 septembre 2009) : 217–38. http://dx.doi.org/10.7202/037914ar.
Texte intégralThèses sur le sujet "Analyse de logiciels malveillants"
Calvet, Joan. « Analyse Dynamique de Logiciels Malveillants ». Phd thesis, Université de Lorraine, 2013. http://tel.archives-ouvertes.fr/tel-00922384.
Texte intégralCalvet, Joan. « Analyse dynamique de logiciels malveillants ». Electronic Thesis or Diss., Université de Lorraine, 2013. http://www.theses.fr/2013LORR0083.
Texte intégralThe main goal of this thesis is the development of malware analysis methods to help human analysts better comprehend the threat it represents. The first achievement in this thesis is the large-scale and in-depth analysis of malware protection techniques. In particular, we have studied hundreds of malware samples, carefully selected according to their threat level. By automatically measuring a set of original characteristics, we have been able to demonstrate the existence of a particularly prevalent model of protection in these programmes that is based on self-modifying code and on a strict delimitation between protection code and payload code. Then, we have developed an identification method for cryptographic implementations adapted to protected machine language programmes. We have validated our approach by identifying several implementations of cryptographic algorithms ---the majority unidentified by existing tools--- and this even in particularly obscure malware protection schemes. Finally, we have developed what is, to our knowledge, the first emulation environment for botnets involving several thousands of machines. Thanks to this, we were able to validate the viability of the use of a vulnerability in the peer-to-peer protocol in the Waledac botnet to take over this network
Thierry, Aurélien. « Désassemblage et détection de logiciels malveillants auto-modifiants ». Electronic Thesis or Diss., Université de Lorraine, 2015. http://www.theses.fr/2015LORR0011.
Texte intégralThis dissertation explores tactics for analysis and disassembly of malwares using some obfuscation techniques such as self-modification and code overlapping. Most malwares found in the wild use self-modification in order to hide their payload from an analyst. We propose an hybrid analysis which uses an execution trace derived from a dynamic analysis. This analysis cuts the self-modifying binary into several non self-modifying parts that we can examine through a static analysis using the trace as a guide. This second analysis circumvents more protection techniques such as code overlapping in order to recover the control flow graph of the studied binary. Moreover we review a morphological malware detector which compares the control flow graph of the studied binary against those of known malwares. We provide a formalization of this graph comparison problem along with efficient algorithms that solve it and a use case in the software similarity field
Thierry, Aurélien. « Désassemblage et détection de logiciels malveillants auto-modifiants ». Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0011/document.
Texte intégralThis dissertation explores tactics for analysis and disassembly of malwares using some obfuscation techniques such as self-modification and code overlapping. Most malwares found in the wild use self-modification in order to hide their payload from an analyst. We propose an hybrid analysis which uses an execution trace derived from a dynamic analysis. This analysis cuts the self-modifying binary into several non self-modifying parts that we can examine through a static analysis using the trace as a guide. This second analysis circumvents more protection techniques such as code overlapping in order to recover the control flow graph of the studied binary. Moreover we review a morphological malware detector which compares the control flow graph of the studied binary against those of known malwares. We provide a formalization of this graph comparison problem along with efficient algorithms that solve it and a use case in the software similarity field
Palisse, Aurélien. « Analyse et détection de logiciels de rançon ». Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S003/document.
Texte intégralThis phD thesis takes a look at ransomware, presents an autonomous malware analysis platform and proposes countermeasures against these types of attacks. Our countermeasures are real-time and are deployed on a machine (i.e., end-hosts). In 2013, the ransomware become a hot subject of discussion again, before becoming one of the biggest cyberthreats beginning of 2015. A detailed state of the art for existing countermeasures is included in this thesis. This state of the art will help evaluate the contribution of this thesis in regards to the existing current publications. We will also present an autonomous malware analysis platform composed of bare-metal machines. Our aim is to avoid altering the behaviour of analysed samples. A first countermeasure based on the use of a cryptographic library is proposed, however it can easily be bypassed. It is why we propose a second generic and agnostic countermeasure. This time, compromission indicators are used to analyse the behaviour of process on the file system. We explain how we configured this countermeasure in an empiric way to make it useable and effective. One of the challenge of this thesis is to collate performance, detection rate and a small amount of false positive. To finish, results from a user experience are presented. This experience analyses the user's behaviour when faced with a threat. In the final part, I propose ways to enhance our contributions but also other avenues that could be explored
Beaucamps, Philippe. « Analyse de programmes malveillants par abstraction de comportements ». Electronic Thesis or Diss., Vandoeuvre-les-Nancy, INPL, 2011. http://www.theses.fr/2011INPL092N.
Texte intégralTraditional behavior analysis usually operates at the implementation level of malicious behaviors. Yet, it is mostly concerned with the identification of given functionalities and is therefore more naturally defined at a functional level. In this thesis, we define a form of program behavior analysis which operates on the function realized by a program rather than on its elementary interactions with the system. This function is extracted from program traces, a process we call abstraction. We define in a simple, intuitive and formal way the basic functionalities to abstract and the behaviors to detect, then we propose an abstraction mechanism applicable both to a static or to a dynamic analysis setting, with practical algorithms of reasonable complexity, finally we describe a behavior analysis technique integrating this abstraction mechanism. Our method is particularly suited to the analysis of programs written in high level languages or with a known source code, for which static analysis is facilitated: mobile applications for .NET or Java, scripts, browser addons, off-the-shelf components.The formalism we propose for behavior analysis by abstraction relies on the theory of string and terms rewriting, word and tree languages and model checking. It allows an efficient identification of functionalities in traces and thus the construction of a represen- tation of traces at a functional level; it defines functionalities and behaviors in a natural way, using temporal logic formulas, which assure their simplicity and their flexibility and enables the use of model checking techniques for behavior detection; it operates on an unrestricted set of execution traces; it handles the data flow in execution traces; and it allows the consideration of uncertainty in the identification of functionalities, with no complexity overhead. Experiments have been conducted in a dynamic and static analysis setting
Beaucamps, Philippe. « Analyse de Programmes Malveillants par Abstraction de Comportements ». Phd thesis, Institut National Polytechnique de Lorraine - INPL, 2011. http://tel.archives-ouvertes.fr/tel-00646395.
Texte intégralLebel, Bernard. « Analyse de maliciels sur Android par l'analyse de la mémoire vive ». Master's thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/29851.
Texte intégralMobile devices are at the core of modern society. Their versatility has allowed third-party developers to generate a rich experience for the user through mobile apps of all types (e.g. productivity, games, communications). As mobile platforms have become connected devices that gather nearly all of our personal and professional information, they are seen as a lucrative market by malware developers. Android is an open-sourced operating system from Google targeting specifically the mobile market and has been targeted by malicious activity due the widespread adoption of the latter by the consumers. As Android malwares threaten many consumers, it is essential that research in malware analysis address specifically this mobile platform. The work conducted during this Master’s focuses on the analysis of malwares on the Android platform. This was achieved through a literature review of the current malware trends and the approaches in static and dynamic analysis that exists to mitigate them. It was also proposed to explore live memory forensics applied to the analysis of malwares as a complement to existing methods. To demonstrate the applicability of the approach and its relevance to the Android malwares, a case study was proposed where an experimental malware has been designed to express malicious behaviours difficult to detect through current methods. The approach explored is called differential live memory analysis. It consists of analyzing the difference in the content of the live memory before and after the deployment of the malware. The results of the study have shown that this approach is promising and should be explored in future studies as a complement to current approaches.
Puodzius, Cassius. « Data-driven malware classification assisted by machine learning methods ». Electronic Thesis or Diss., Rennes 1, 2022. https://ged.univ-rennes1.fr/nuxeo/site/esupversions/3dabb48c-b635-46a5-bcbe-23992a2512ec.
Texte intégralHistorically, malware (MW) analysis has heavily resorted to human savvy for manual signature creation to detect and classify MW. This procedure is very costly and time consuming, thus unable to cope with modern cyber threat scenario. The solution is to widely automate MW analysis. Toward this goal, MW classification allows optimizing the handling of large MW corpora by identifying resemblances across similar instances. Consequently, MW classification figures as a key activity related to MW analysis, which is paramount in the operation of computer security as a whole. This thesis addresses the problem of MW classification taking an approach in which human intervention is spared as much as possible. Furthermore, we steer clear of subjectivity inherent to human analysis by designing MW classification solely on data directly extracted from MW analysis, thus taking a data-driven approach. Our objective is to improve the automation of malware analysis and to combine it with machine learning methods that are able to autonomously spot and reveal unwitting commonalities within data. We phased our work in three stages. Initially we focused on improving MW analysis and its automation, studying new ways of leveraging symbolic execution in MW analysis and developing a distributed framework to scale up our computational power. Then we concentrated on the representation of MW behavior, with painstaking attention to its accuracy and robustness. Finally, we fixed attention on MW clustering, devising a methodology that has no restriction in the combination of syntactical and behavioral features and remains scalable in practice. As for our main contributions, we revamp the use of symbolic execution for MW analysis with special attention to the optimal use of SMT solver tactics and hyperparameter settings; we conceive a new evaluation paradigm for MW analysis systems; we formulate a compact graph representation of behavior, along with a corresponding function for pairwise similarity computation, which is accurate and robust; and we elaborate a new MW clustering strategy based on ensemble clustering that is flexible with respect to the combination of syntactical and behavioral features
Nisi, Dario. « Unveiling and mitigating common pitfalls in malware analysis ». Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS528.
Texte intégralAs the importance of computer systems in modern-day societies grows, so does the damage that malicious software causes. The security industry and malware authors engaged in an arms race, in which the first creates better detection systems while the second try to evade them. In fact, any wrong assumption (no matter how subtle) in the design of an anti-malware tool may create new avenues for evading detection. This thesis focuses on two often overlooked aspects of modern malware analysis techniques: the use of API-level information to encode malicious behavior and the reimplementation of parsing routines for executable file formats in security-oriented tools. We show that taking advantage of these practices is possible on a large and automated scale. Moreover, we study the feasibility of fixing these problems at their roots, measuring the difficulties that anti-malware architects may encounter and providing strategies to solve them
Livres sur le sujet "Analyse de logiciels malveillants"
Ligh, Michael W. Malware analyst's cookbook and dvd : Tools and techniques for fighting malicious code. Indianapolis, Ind : Wiley Pub., Inc, 2011.
Trouver le texte intégralHerman, Jacques. Analyse de données qualitatives. Paris : Masson, 1986.
Trouver le texte intégralBowden, Mark. Worm : The first digital world war. New York : Grove, 2013.
Trouver le texte intégralCarle, André. Analyse coûts-bénéfices de la méthode d'inventaire d'intervention en forêt feuillue : Projet no. 4066. Québec, Qué : Service d'extension en foresterie de l'Est-du-Québec, 1996.
Trouver le texte intégralVallet, Gilles. Techniques de planification de projets. 2e éd. Paris : Dunod, 1996.
Trouver le texte intégralCarricano, Manu. Analyse de donne es avec SPSS. Paris : Pearson Education France, 2008.
Trouver le texte intégralPlaksin, Anna Viktoria Katrin. Modelle zur computergestützten Analyse von Überlieferungen der Mensuralmusik : Empirische Textforschung im Kontext phylogenetischer Verfahren. Münster] : WWU Münster, 2021.
Trouver le texte intégralGröhn, Andreas. Netzwerkeffekte und Wettbewerbspolitik : Eine ökonomische Analyse des Softwaremarktes. Tübingen : Mohr Siebeck, 1999.
Trouver le texte intégralMerrien, Jean-Louis. Analyse numérique avec Matlab : Rappels de cours, méthodes, exercices et problèmes avec corrigés détaillés. Paris : Dunod, 2007.
Trouver le texte intégralChris, Phillips. Computational numerical methods. Chichester [West Sussex] : Ellis Horwood, 1986.
Trouver le texte intégralChapitres de livres sur le sujet "Analyse de logiciels malveillants"
Lebraty, Jean-Fabrice, Katia Lobre-Lebraty et Stéphane Trébucq. « Chapitre 16. Logiciels et analyse de données qualitatives ». Dans Les méthodes de recherche du DBA, 283. EMS Editions, 2018. http://dx.doi.org/10.3917/ems.cheva.2018.01.0283.
Texte intégralActes de conférences sur le sujet "Analyse de logiciels malveillants"
Moïse, Alexandre. « Analyse des logiciels d'application spécialisée pour le courtage en épargne collective ». Dans the 18th international conference. New York, New York, USA : ACM Press, 2006. http://dx.doi.org/10.1145/1132736.1132754.
Texte intégralRapports d'organisations sur le sujet "Analyse de logiciels malveillants"
Nédellec, Claire, Adeline Nazarenko, Francis André, Catherine Balivo, Béatrice Daille, Anastasia Drouot, Jorge Flores et al. Recommandations sur l’analyse automatique de documents : acquisition, gestion, exploration. Ministère de l'enseignement supérieur et de la recherche, septembre 2019. http://dx.doi.org/10.52949/10.
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