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001 | 9.854523 |
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003 | CaOODSP |
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005 | 20240221113057 |
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007 | cr ||||||||||| |
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008 | 180328s2017 quc ob f000 0 eng d |
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040 | |aCaOODSP|beng |
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043 | |an-cn--- |
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086 | 1 |aD68-10/118-2017E-PDF |
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245 | 00|aIntroduction to SinJAR (a new tool for reverse engineering Java applications) and tracing its malicious actions using hidden Markov models |h[electronic resource] / |cJaouhar Fattahi ... [et al.]. |
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260 | |a[Valcartier, QC] : |bDefence Research and Development Canada, |c2017. |
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300 | |a[17] p. |
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490 | 1 |aExternal literature (P) ; |vDRDC-RDDC-2017-P118 |
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500 | |aCover title. |
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500 | |a"Can unclassified." |
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500 | |a"December 2017." |
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500 | |aOriginally published in: Frontiers in artificial intelligence and applications, vol. 297, p. 441-453, Nov. 2017. |
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504 | |aIncludes bibliographical references. |
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520 | 3 |a"In this paper, we are proposing a new tool for reversing Java applications called SinJAR. SinJAR is a lightweight software written in Java aiming at inspecting bytecode at compile time and producing the structure tree of a targeted application. Besides, it is able to detect vulnerabilities and security weaknesses inside the Java code. SinJAR can be used for two purposes. The first one is sane and consists in using it to verify whether or not an application is safe and compliant with its specification. The second one is malicious and consists in spying applications through their bytecode and exploiting vulnerabilities that they may enclose. In this paper, we will show how to detect SinJAR malicious actions after showing the capabilities of the tool through few ad hoc attack scenarios conducted in a real military context”--Abstract. |
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692 | 07|2gccst|aComputer security |
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692 | 07|2gccst|aSoftware |
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693 | 4|aJava (Computer program language) |
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693 | 4|aMarkov processes |
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700 | 1 |aFattahi, Jaouhar. |
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710 | 1 |aDefence R&D Canada. |bValcartier Research Centre. |
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830 | #0|aExternal literature (P) (Defence R&D Canada)|vDRDC-RDDC-2017-P118.|w(CaOODSP)9.854437 |
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856 | 40|qPDF|s926 KB|uhttps://publications.gc.ca/collections/collection_2018/rddc-drdc/D68-10-118-2017-eng.pdf |
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