Literatura científica selecionada sobre o tema "Détection de logiciels malveillants"
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Artigos de revistas sobre o assunto "Détection de logiciels malveillants"
Moreno, Matthieu, e Sarah Gebeile-Chauty. "Étude comparative de deux logiciels de détection de points de repère céphalométriques par intelligence artificielle". L Orthodontie Française 93, n.º 1 (1 de março de 2022): 41–61. http://dx.doi.org/10.1684/orthodfr.2022.73.
Texto completo da fonteAmanfu, William, S. Sediadie, K. V. Masupu, A. Benkirane, R. Geiger e François Thiaucourt. "Validation de terrain d'un test ELISA de compétition pour la détection de la péripneumonie contagieuse des bovins au Botswana". Revue d’élevage et de médecine vétérinaire des pays tropicaux 51, n.º 3 (1 de março de 1998): 189–93. http://dx.doi.org/10.19182/remvt.9620.
Texto completo da fonteDarnoux, Camille, e Laurine Leriche. "Qualification d’un procédé multi technique en alternative au ressuage". e-journal of nondestructive testing 28, n.º 9 (setembro de 2023). http://dx.doi.org/10.58286/28503.
Texto completo da fonteFoucher, Fabrice, Sébastien Lonné, Philippe Dubois, Stéphane Leberre, Pierre Calmon, Michael Enright e Yasin Zaman. "Apports d’une cosimulation “END – Tolérance aux dommages” dans la réduction des risques de rupture". e-journal of nondestructive testing 28, n.º 9 (setembro de 2023). http://dx.doi.org/10.58286/28527.
Texto completo da fonteIthurralde, Guillaume, e Franck Maurel. "Inspection Ultrasonore Robotisée de Pièces Composites". e-journal of nondestructive testing 28, n.º 9 (setembro de 2023). http://dx.doi.org/10.58286/28516.
Texto completo da fonteTeses / dissertações sobre o assunto "Détection de logiciels malveillants"
Thierry, Aurélien. "Désassemblage et détection de logiciels malveillants auto-modifiants". Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0011/document.
Texto completo da fonteThis 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.
Texto completo da fonteThis 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
Khoury, Raphaël. "Détection du code malicieux : système de type à effets et instrumentation du code". Thesis, Université Laval, 2005. http://www.theses.ulaval.ca/2005/23250/23250.pdf.
Texto completo da fonteThe purpose of this thesis is twofold. In the first place it presents a comparative study of the advantages and drawbacks of several approaches to insure software safety and security. It then focuses more particularly on combining static analyses and dynamic monitoring in order to produce a more powerful security architecture. The first chapters of the thesis present an analytical review of the various static, dynamic and hybrid approaches that can be used to secure a potentially malicious code. The advantages and drawbacks of each approach are thereby analyzed and the field of security properties that can be enforced by using it are identified. The thesis then focuses on the possibility of combining static and dynamic analysis through a new hybrid approach. This approach consists in a code instrumentation, that only alters those parts of a program where it is necessary to do so to insure the respect of a user-defined security policy expressed in a set of modal μ-calculus properties. this instrumentation is guided by a static analysis based on a type and effect system. The effects represent the accesses made to pretested system ressources.
Lespérance, Pierre-Luc. "Détection des variations d'attaques à l'aide d'une logique temporelle". Thesis, Université Laval, 2006. http://www.theses.ulaval.ca/2006/23481/23481.pdf.
Texto completo da fonteTa, Thanh Dinh. "Modèle de protection contre les codes malveillants dans un environnement distribué". Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0040/document.
Texto completo da fonteThe thesis consists in two principal parts: the first one discusses the message for- mat extraction and the second one discusses the behavioral obfuscation of malwares and the detection. In the first part, we study the problem of “binary code coverage” and “input message format extraction”. For the first problem, we propose a new technique based on “smart” dynamic tainting analysis and reverse execution. For the second one, we propose a new method using an idea of classifying input message values by the corresponding execution traces received by executing the program with these input values. In the second part, we propose an abstract model for system calls interactions between malwares and the operating system at a host. We show that, in many cases, the behaviors of a malicious program can imitate ones of a benign program, and in these cases a behavioral detector cannot distinguish between the two programs
El, Hatib Souad. "Une approche sémantique de détection de maliciel Android basée sur la vérification de modèles et l'apprentissage automatique". Master's thesis, Université Laval, 2020. http://hdl.handle.net/20.500.11794/66322.
Texto completo da fonteThe ever-increasing number of Android malware is accompanied by a deep concern about security issues in the mobile ecosystem. Unquestionably, Android malware detection has received much attention in the research community and therefore it becomes a crucial aspect of software security. Actually, malware proliferation goes hand in hand with the sophistication and complexity of malware. To illustrate, more elaborated malware like polymorphic and metamorphic malware, make use of code obfuscation techniques to build new variants that preserve the semantics of the original code but modify it’s syntax and thus escape the usual detection methods. In the present work, we propose a model-checking based approach that combines static analysis and machine learning. Mainly, from a given Android application we extract an abstract model expressed in terms of LNT, a process algebra language. Afterwards, security related Android behaviours specified by temporal logic formulas are checked against this model, the satisfaction of a specific formula is considered as a feature, finally machine learning algorithms are used to classify the application as malicious or not.
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.
Texto completo da fonteAngoustures, Mark. "Extraction automatique de caractéristiques malveillantes et méthode de détection de malware dans un environnement réel". Electronic Thesis or Diss., Paris, CNAM, 2018. http://www.theses.fr/2018CNAM1221.
Texto completo da fonteTo cope with the large volume of malware, researchers have developed automatic dynamic tools for the analysis of malware like the Cuckoo sandbox. This analysis is partially automatic because it requires the intervention of a human expert in security to detect and extract suspicious behaviour. In order to avoid this tedious work, we propose a methodology to automatically extract dangerous behaviors. First of all, we generate activity reports from malware from the sandbox Cuckoo. Then, we group malware that are part of the same family using the Avclass algorithm. We then weight the the most singular behaviors of each malware family obtained previously. Finally, we aggregate malware families with similar behaviors by the LSA method.In addition, we detail a method to detect malware from the same type of behaviors found previously. Since this detection isperformed in real environment, we have developed probes capable of generating traces of program behaviours in continuous execution. From these traces obtained, we let’s build a graph that represents the tree of programs in execution with their behaviors. This graph is updated incrementally because the generation of new traces. To measure the dangerousness of programs, we execute the personalized PageRank algorithm on this graph as soon as it is updated. The algorithm gives a dangerousness ranking processes according to their suspicious behaviour. These scores are then reported on a time series to visualize the evolution of this dangerousness score for each program. Finally, we have developed several alert indicators of dangerous programs in execution on the system
Angoustures, Mark. "Extraction automatique de caractéristiques malveillantes et méthode de détection de malware dans un environnement réel". Thesis, Paris, CNAM, 2018. http://www.theses.fr/2018CNAM1221.
Texto completo da fonteTo cope with the large volume of malware, researchers have developed automatic dynamic tools for the analysis of malware like the Cuckoo sandbox. This analysis is partially automatic because it requires the intervention of a human expert in security to detect and extract suspicious behaviour. In order to avoid this tedious work, we propose a methodology to automatically extract dangerous behaviors. First of all, we generate activity reports from malware from the sandbox Cuckoo. Then, we group malware that are part of the same family using the Avclass algorithm. We then weight the the most singular behaviors of each malware family obtained previously. Finally, we aggregate malware families with similar behaviors by the LSA method.In addition, we detail a method to detect malware from the same type of behaviors found previously. Since this detection isperformed in real environment, we have developed probes capable of generating traces of program behaviours in continuous execution. From these traces obtained, we let’s build a graph that represents the tree of programs in execution with their behaviors. This graph is updated incrementally because the generation of new traces. To measure the dangerousness of programs, we execute the personalized PageRank algorithm on this graph as soon as it is updated. The algorithm gives a dangerousness ranking processes according to their suspicious behaviour. These scores are then reported on a time series to visualize the evolution of this dangerousness score for each program. Finally, we have developed several alert indicators of dangerous programs in execution on the system
Calvet, Joan. "Analyse Dynamique de Logiciels Malveillants". Phd thesis, Université de Lorraine, 2013. http://tel.archives-ouvertes.fr/tel-00922384.
Texto completo da fonteLivros sobre o assunto "Détection de logiciels malveillants"
Inc, ebrary, ed. Malware analyst's cookbook and dvd: Tools and techniques for fighting malicious code. Indianapolis, Ind: Wiley Pub., Inc, 2011.
Encontre o texto completo da fonteBowden, Mark. Worm: The first digital world war. New York: Grove, 2013.
Encontre o texto completo da fonteWriting solid code: Microsoft's techniques for developing bug-free C programs. Redmond, Wash: Microsoft Press, 1993.
Encontre o texto completo da fonteDunham, Ken, Shane Hartman e Manu Quintans. Android Malware and Analysis. Taylor & Francis Group, 2014.
Encontre o texto completo da fonteMorales, Jose Andre, Tim Strazzere, Ken Dunham, Shane Hartman e Manu Quintans. Android Malware and Analysis. Auerbach Publishers, Incorporated, 2014.
Encontre o texto completo da fonteMorales, Jose Andre, Tim Strazzere, Ken Dunham, Shane Hartman e Manu Quintans. Android Malware and Analysis. Auerbach Publishers, Incorporated, 2014.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Détection de logiciels malveillants"
Eck, Nadine. "Chapitre 18. Utiliser des logiciels de détection de plagiat : l’envers du décor". In L'urgence de l'intégrité académique, 309–25. EMS Editions, 2021. http://dx.doi.org/10.3917/ems.berga.2021.01.0309.
Texto completo da fonte