dc.creatorGregio A.R.A.
dc.creatorBaruque A.O.C.
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.accessioned2018-03-28T21:28:55Z
dc.date.available2018-03-28T21:28:55Z
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. 302 - 313, 2012.
dc.identifier3029743
dc.identifier10.1007/978-3-642-31128-4_22
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84863928210&partnerID=40&md5=451350b793e81a44286f3b310d586727
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/97098
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/97098
dc.identifier2-s2.0-84863928210
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1245953
dc.descriptionMalicious software attacks can disrupt information systems, violating security principles of availability, confidentiality and integrity. Attackers use malware to gain control, steal data, keep access and cover traces left on the compromised systems. The dynamic analysis of malware is useful to obtain an execution trace that can be used to assess the extent of an attack, to do incident response and to point to adequate counter-measures. An analysis of the captured malware can provide analysts with information about its behavior, allowing them to review the malicious actions performed during its execution on the target. The behavioral data gathered during the analysis consists of filesystem and network activity traces; a security analyst would have a hard time sieving through a maze of textual event data in search of relevant information. We present a behavioral event visualization framework that allows for an easier realization of the malicious chain of events and for quickly spotting interesting actions performed during a security compromise. Also, we analyzed more than 400 malware samples from different families and showed that they can be classified based on their visual signature. Finally, we distribute one of our tools to be freely used by the community. © 2012 Springer-Verlag.
dc.description7336 LNCS
dc.descriptionPART 4
dc.description302
dc.description313
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.descriptionBuehlmann, S., Liebchen, C., Joebox: A Secure Sandbox Application for Windows to Analyse the Behaviour of Malware, , http://www.joebox.org
dc.descriptionClam Antivirus, , http://www.clamav.net
dc.descriptionConti, G., Dean, E., Sinda, M., Sangster, B., Visual Reverse Engineering of Binary and Data Files (2008) LNCS, 5210, pp. 1-17. , Goodall, J.R., Conti, G., Ma, K.-L. (eds.) VizSec 2008. Springer, Heidelberg
dc.descriptionEick, S.G., Steffen, J.L., Sumner Jr., E.E., Seesoft-A Tool for Visualizing Line Oriented Software Statistics (1992) IEEE Transactions on Software Engineering, 18 (11), pp. 957-968
dc.descriptionGrégio, A.R.A., Oliveira, I.L., Dos Santos, R.D.C., Cansian, A.M., De Geus, P.L., Malware distributed collection and pre-classification system using honeypot technology (2009) Proceedings of SPIE, 7344, pp. 73440B-73440B10
dc.descriptionGrégio, A.R.A., Fernandes Filho, D.S., Afonso, V.M., Dos Santos, R.D.C., Jino, M., De Geus, P.L., Behavioral analysis of malicious code through network traffic and system call monitoring (2011) Proceedings of SPIE, 8059, pp. 80590O-80590O10
dc.descriptionhttp://dionaea.carnivore.it, The Honeynet ProjectKruegel, 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 (2006)
dc.descriptionMBS Tool. Malicious Behavior's Spiral - Beta Version, , http://www.las.ic.unicamp.br/~gregio/mbs
dc.descriptionProvos, N., Holz, T., (2007) Virtual Honeypots: From Botnet Tracking to Intrusion Detection, , Addison-Wesley Professional
dc.descriptionProvos, N., Honeyd - A Virtual Honeypot Daemon 10th DFNCERT Workshop (2003)
dc.descriptionQuist, D., Liebrock, L., Visualizing Compiled Executables for Malware Analysis (2009) Proceedings of the Workshop on Visualization for Cyber Security, pp. 27-32
dc.descriptionRead, H., Xynos, K., Blyth, A., Presenting DEViSE: Data Exchange for Visualizing Security Events (2009) IEEE Computer Graphics and Applications, 29, pp. 6-11
dc.descriptionhttp://www.threatexpert.comTrinius, P., Holz, T., Gobel, J., Freiling, F.C., Visual analysis of malware behavior using treemaps and thread graphs (2009) International Workshop on Visualization for Cyber Security(VizSec), pp. 33-38
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.titleInteractive, Visual-aided Tools To Analyze Malware Behavior
dc.typeActas de congresos


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