dc.creatorGregio A.R.A.
dc.creatorAfonso V.M.
dc.creatorFilho D.S.F.
dc.creatorDe Geus P.L.
dc.creatorJino M.
dc.creatorDos Santos R.D.C.
dc.date2012
dc.date2015-06-26T20:29:36Z
dc.date2015-11-26T14:26:03Z
dc.date2015-06-26T20:29:36Z
dc.date2015-11-26T14:26:03Z
dc.date.accessioned2018-03-28T21:28:54Z
dc.date.available2018-03-28T21:28:54Z
dc.identifier9783642311277
dc.identifierLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). , v. 7336 LNCS, n. PART 4, p. 274 - 285, 2012.
dc.identifier3029743
dc.identifier10.1007/978-3-642-31128-4_20
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84863904235&partnerID=40&md5=e8fa7f3e954a1a5f565f80bfd5cce789
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/97097
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/97097
dc.identifier2-s2.0-84863904235
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1245950
dc.descriptionMalicious programs pose a major threat to Internet-connected systems, increasing the importance of studying their behavior in order to fight against them. In this paper, we propose definitions to the different types of behavior that a program can present during its execution. Based on those definitions, we define suspicious behavior as the group of actions that change the state of a target system. We also propose a set of network and system-level dangerous activities that can be used to denote the malignity in suspicious behaviors, which were extracted from a large set of malware samples. In addition, we evaluate the malware samples according to their suspicious behavior. Moreover, we developed filters to translate from lower-level execution traces to the observed dangerous activities and evaluated them in the context of actual malware. © 2012 Springer-Verlag.
dc.description7336 LNCS
dc.descriptionPART 4
dc.description274
dc.description285
dc.descriptionUniversidade Federal da Bahia (UFBA),Universidade Federal do Reconcavo da Bahia (UFRB),Universidade Estadual de Feira de Santana (UEFS),University of Perugia,University of Basilicata (UB)
dc.descriptionNorman Sandbox, , http://www.norman.com/security_center/security_tools/
dc.descriptionhttp://www.threatexpert.com/Afonso, V.M., Filho, D.S.F., Grégio, A.R.A., De Geus, P.L., Jino, M., A hybrid framework to analyze web and os malware Proceedings of the 2012 IEEE International Conference on Communications (ICC) (June 2012)
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dc.descriptionEgele, M., Kruegel, C., Kirda, E., Yin, H., Song, D., Dynamic Spyware Analysis (2007) Proceedings of the USENIX Annual Technical Conference, , USENIX Association, Berkeley
dc.descriptionFiliol, E., Malware pattern scanning schemes secure against black-box analysis (2006) Journal in Computer Virology, 2 (1), pp. 35-50
dc.descriptionFiliol, E., Jacob, G., Le Liard, M., Evaluation methodology and theoretical model for antiviral behavioural detection strategies (2007) Journal in Computer Virology, 3 (1), pp. 23-37
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dc.descriptionJacob, G., Debar, H., Filiol, E., Malware Behavioral Detection by Attribute- Automata Using Abstraction from Platform and Language (2009) LNCS, 5758, pp. 81-100. , Kirda, E., Jha, S., Balzarotti, D. (eds.) RAID 2009. Springer, Heidelberg
dc.descriptionKruegel, C., Kirda, E., Bayer, U., TTAnalyze: A tool for analyzing malware Proceedings of the 15th European Institute for Computer Antivirus Research (EICAR 2006) Annual Conference (April 2006)
dc.descriptionKruegel, C., Kirda, E., Bayer, U., Balzarotti, D., Habibi, I., Insights into current malware behavior 2nd USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET), Boston (April 2009)
dc.descriptionMartignoni, L., Stinson, E., Fredrikson, M., Jha, S., Mitchell, J.C., A Layered Architecture for Detecting Malicious Behaviors (2008) LNCS, 5230, pp. 78-97. , Lippmann, R., Kirda, E., Trachtenberg, A. (eds.) RAID 2008. Springer, Heidelberg
dc.descriptionProvos, N., Holz, T., (2007) Virtual Honeypots: From Botnet Tracking to Intrusion Detection, , 1st edn. Addison-Wesley Professional
dc.descriptionRules for Naming Detected Objects, , http://www.securelist.com/en/%20threats/detect?chapter=136
dc.descriptionWillems, C., Holz, T., Freiling, F., Toward Automated Dynamic Malware Analysis Using CWSandbox (2007) IEEE Security and Privacy, 5, pp. 32-39
dc.languageen
dc.publisher
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsfechado
dc.sourceScopus
dc.titlePinpointing Malicious Activities Through Network And System-level Malware Execution Behavior
dc.typeActas de congresos


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